system

Abstract

We provide the system. [Solution] Means of collecting risk information from reliable sources, A means for monitoring communication data in a communication device in real time, A means of analyzing risk based on past leaked information data, A means of issuing a warning to the user based on the analysis results, A display means that shows recommended actions based on risk assessment, A system that includes this.

Description

Technical Field

[0001] The technology of this disclosure relates to a system.

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In recent years, leakage of personal information through communication devices and malicious communications have become social problems. Such problems particularly have a great impact on users who are not familiar with technology, and as a result, may cause great inconvenience and economic losses. Therefore, it is required to provide an environment in which users can communicate with confidence and prevent information leakage and nuisance communications in advance.

Means for Solving the Problems

[0005] This invention provides a system that collects risk information from reliable sources and monitors communication data in communication devices in real time. This system analyzes risks based on past data breaches and includes a mechanism for issuing warnings to users, thereby creating an environment where users can communicate with peace of mind. Furthermore, it includes a mechanism for continuously updating risk information and improving analysis accuracy, enabling it to always respond to the latest threats. In addition, it includes a guidance mechanism that presents specific countermeasures based on user actions, supporting a swift and appropriate response to risks that arise.

[0006] A "highly reliable institution" is an institution that possesses public or widely recognized credibility regarding security and information protection, and is capable of providing risk information.

[0007] "Risk information" refers to information about security threats to communication devices, websites, businesses, and other risks that may negatively impact users' personal information.

[0008] "Communication equipment" refers to electronic devices used for sending and receiving information, and mainly includes smartphones and similar devices.

[0009] "Communication data" refers to all information transmitted and received via communication devices, including phone calls, messages, and internet browsing history.

[0010] "Real-time monitoring" means immediately monitoring and analyzing the data at the very moment it is sent or received.

[0011] "Leaked information data" refers to recorded data related to past personal information leak incidents, and is used for risk analysis.

[0012] "Risk analysis" involves identifying current security threats and dangers based on collected data and assessing their likelihood.

[0013] "Issuing a warning" means sending a notification to inform the user that there is a security risk.

[0014] A "guidance tool" is a support function that shows users countermeasures and methods for dealing with specific risks they face. [Brief explanation of the drawing]

[0015] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0017] First, the language used in the following description will be explained.

[0018] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0019] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0028] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0035] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0036] This invention relates to a security system for secure communication via communication devices. This system consists of multiple servers, terminals, and users.

[0037] The server continuously collects risk information from reliable sources. This ensures that the latest threat information is reflected in the database and that it is constantly updated. The server also receives communication data transmitted in real time from each terminal and analyzes this data by comparing it with past leaked information data. The server uses AI to perform this analysis and determine the level of risk associated with the user's communication.

[0038] The terminal is installed on the user's communication device and monitors the user's daily operations. Each time communication occurs, the terminal sends information to the server, using a lightweight and efficient protocol to avoid performance degradation. Upon receiving instructions from the server, the terminal displays a warning message to the user and, if necessary, provides guidance suggesting specific corrective actions. This guidance includes actions to take immediately and suggestions for configuration changes.

[0039] Users can take quick and appropriate action based on real-time warnings and guidance from their devices. For example, if an untrusted application is installed, the device will display a warning such as, "This app has caused security risks in the past. We recommend removing it."

[0040] In this way, the present invention provides a comprehensive solution to enhance the security of users' digital environments and proactively prevent risks such as the leakage of personal information and spam communications.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The server collects threat information from reliable sources and stores it in a database. This ensures that the system always maintains the most up-to-date threat information.

[0044] Step 2:

[0045] The device monitors user calls, messages, and app usage, and temporarily records data related to each action. The monitoring is designed not to impact user performance.

[0046] Step 3:

[0047] The terminal periodically sends recorded data to the server. This data transfer uses a secure and efficient protocol to prevent delays and excessive bandwidth consumption.

[0048] Step 4:

[0049] The server analyzes the received communication data and compares it with past data breaches and risk information. Using AI, it assesses the data's risk level and generates immediate warnings as needed.

[0050] Step 5:

[0051] The server sends instructions to the terminal based on the analysis results. These instructions include a decision on whether or not to take a specific action.

[0052] Step 6:

[0053] The device displays a warning message to the user, following instructions from the server. The warning includes details of the detected risk and recommended actions.

[0054] Step 7:

[0055] Users choose the necessary action based on the warnings and guidance provided by their device. This may include deleting apps, stopping communication, or changing settings.

[0056] Step 8:

[0057] The server analyzes user behavior and newly collected data to update the AI ​​model, thereby improving the accuracy of future risk assessment and detection.

[0058] (Example 1)

[0059] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0060] Conventional security systems have been insufficient in collecting risk information during communications and analyzing communication data, making it difficult to quickly detect the risk of information leaks and unauthorized access. Furthermore, the lack of means to provide users with specific warnings and countermeasures in a timely manner meant that users missed opportunities to take appropriate action themselves.

[0061] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0062] In this invention, the server includes means for acquiring risk information from a reliable data source, means for monitoring data communication in the information processing device in real time, and means for evaluating risk based on past information leakage data. This makes it possible to quickly and efficiently detect the latest threats and immediately propose specific countermeasures to users.

[0063] A "highly reliable data source" refers to an information provider whose reliability and credibility are guaranteed in order to provide security information and risk information.

[0064] An "information processing device" refers to an electronic device used for communication and data processing.

[0065] "Data communication" refers to the process of sending and receiving information over a network.

[0066] "Information leakage data" refers to records and information related to the unauthorized leakage or disclosure of data that has occurred in the past.

[0067] "Means of risk assessment" refers to methods or processes for determining the extent to which communications or data pose a security risk.

[0068] A "lightweight and efficient communication protocol" refers to a protocol designed to improve communication efficiency and enable rapid data transmission and reception.

[0069] "Means of proposing specific countermeasures" refers to a mechanism that indicates the actions or changes that users should take in response to specific security risks.

[0070] This invention is a security system for secure communication, and is mainly composed of a server, a terminal, and a user.

[0071] The server acquires risk information from reliable data sources and stores it in a database. The database utilizes a cloud-based storage system and is always accessible. The server also employs generative AI models to analyze communication data transmitted from terminals. This allows it to assess communication risks based on past data breaches.

[0072] The terminal is a software application installed on the user's device, responsible for monitoring the user's communications in real time. By using lightweight and efficient communication protocols such as MQTT, the terminal can quickly send data to the server. Furthermore, based on the evaluation results from the server, the terminal provides the user with necessary warnings and specific countermeasures. This process enables the user to take timely and appropriate action.

[0073] Through this system, users can receive real-time warnings and guidance to protect the security of their digital environment. For example, if a suspicious application is installed, the device will warn, "This app has caused security risks in the past. We recommend removing it," allowing users to take immediate action. Furthermore, by using a prompt such as "How can I display a warning when installing an untrusted app?" as an example of a prompt to input into the generating AI model, more specific advice and information can be obtained.

[0074] In this way, the present invention provides an effective means for users to safely utilize the digital environment.

[0075] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0076] Step 1:

[0077] The server acquires threat information from reliable external data sources. It receives threat information periodically via an API as input and stores it in a database in JSON format. As part of data processing, it integrates the received information into an existing data structure to maintain up-to-date threat information.

[0078] Step 2:

[0079] The terminal operates on the user's communication device and monitors communication data in real time. Specifically, it captures network traffic and formats it into the required format. As input, it collects relevant data (e.g., IP address and port number) each time communication occurs and sends it to the server. The output is this communication data, sent using the lightweight MQTT protocol.

[0080] Step 3:

[0081] The server receives communication data sent from the terminal and performs data analysis using a generating AI model. The input is communication data from the terminal, which the AI ​​model analyzes, compares with past data breaches, and calculates a risk score. The output of this analysis is a risk assessment result, and further actions are decided based on this result.

[0082] Step 4:

[0083] The server immediately sends a warning message to the terminal if the risk score exceeds a certain threshold. Specifically, it retrieves the relevant warning message from the database and notifies the terminal using the MQTT protocol. The input is the risk assessment result, and the output is the warning message.

[0084] Step 5:

[0085] The terminal displays a notification to the user based on a warning message received from the server. Specifically, it displays a warning as a pop-up on the user screen via a GUI. The input is a warning message from the server, and the output is a visual warning display to the user. Additional countermeasures are also displayed at this point to suggest appropriate actions to the user.

[0086] Step 6:

[0087] The user receives warnings from the device and chooses appropriate action based on the guidance provided. Specific actions include uninstalling suspicious applications and changing settings. The input is the warnings and guidance from the device, while the output is the actual action taken by the user to mitigate security risks.

[0088] (Application Example 1)

[0089] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0090] Security threats in the digital environment are increasing, and users are required to recognize and act quickly and appropriately on these risks. However, conventional systems are insufficient in providing real-time threat recognition and specific countermeasures guidance. Therefore, there is a need for a method to quickly assess potential communication risks faced by users and provide accurate guidance on action.

[0091] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0092] In this invention, the server includes means for collecting risk information from a reliable source, means for monitoring communication data in a communication device in real time, and means for analyzing risk based on past leaked information data. This allows users to immediately assess the risks associated with communication and receive real-time guidance for taking appropriate action.

[0093] A "highly reliable organization" is a professional organization that guarantees the accuracy and timeliness of its information and provides data on security threats.

[0094] "Means for collecting risk information" refers to methods and devices for efficiently obtaining security-related information provided by reliable organizations.

[0095] A "communication device" is an electronic device that transmits and receives information and is connected to other devices via data communication.

[0096] "Means of monitoring communication data in real time" refers to systems and methods for immediately observing transmitted and received data to determine whether there are any threats or anomalies.

[0097] "Past data breaches" refers to data obtained from past data breaches, which are accumulated records and information used for security analysis.

[0098] "Means of risk analysis" refer to calculation methods and algorithms used to compare communication data with leaked information data and identify potential security risks.

[0099] "Means of issuing warnings to users based on analysis results" refers to methods of informing users of potential hazards based on the results of risk analysis and providing notifications to ensure their safety.

[0100] A "display means for showing recommended actions based on risk assessment" refers to a method or device that visually presents specific action guidelines to the user according to the risk level determined by the analysis.

[0101] "Means of providing real-time guidance on user behavior" refers to a system that provides instructions to prompt appropriate actions immediately based on the user's current actions and circumstances.

[0102] The system for implementing the present invention mainly consists of a server, terminals, and users. The server continuously collects security risk information from reliable sources and maintains the latest threat information by updating its database in real time. The server also immediately monitors communication data transmitted from each terminal and analyzes the risk by comparing it with past leaked information data.

[0103] The terminal is installed on the user's communication device and detects the user's daily communication activities. The terminal forwards incoming and outgoing data packets to the server using a lightweight and efficient protocol. The server receives this data and, through an AI-based risk assessment algorithm, verifies the security of the communication and decides whether or not to send a warning to the user.

[0104] Users can take immediate action against suspicious communications by following warning messages and guidance from their devices. This system enhances security by displaying recommended actions based on risk assessments on the user's device and providing visually clear instructions.

[0105] For example, if a user connects to public Wi-Fi, the system immediately assesses the risk and provides a warning and countermeasures such as, "This network may have a low level of security. Please choose another network or use a VPN."

[0106] By utilizing generative AI models, it is possible to learn patterns in threat intelligence and generate highly accurate warnings. For example, a prompt such as, "Develop an AI model to assess the security risks of newly installed applications. Describe a mechanism that scores the risk level based on past data breach incidents and displays a warning to the user," could be used.

[0107] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0108] Step 1:

[0109] The server regularly collects security risk information from reliable sources. During this process, new security incident information is added to the database via an API, updating the training dataset for the AI ​​model. The input is the latest security risk data obtained from the sources, and the output is the updated database.

[0110] Step 2:

[0111] The terminal monitors communication data in real time using the user's communication device. Here, it captures incoming and outgoing data packets and sends them to the server using a lightweight protocol. The input is the user's real-time communication data, and the output is the transfer of data packets to the server.

[0112] Step 3:

[0113] The server analyzes the received communication data based on a risk assessment algorithm. An AI model compares the communication data with past data breaches to calculate the threat level. The input is the communication data sent from the terminal, and the output is the calculated risk score.

[0114] Step 4:

[0115] The server will issue a warning to the user if necessary, based on the risk score. Specifically, it will generate a warning message based on the result and send it to the terminal. The input is the risk score, and the output is the warning message to the user.

[0116] Step 5:

[0117] The device displays received warning messages to the user and provides appropriate guidance. Here, recommended actions and changes to security settings are communicated via a notification screen. The input is the warning message from the server, and the output is a notification prompting user action.

[0118] Step 6:

[0119] The user selects actions based on warnings through their device and modifies communication device settings as needed. This includes actions such as selecting a new network or removing threatening applications. The input is the notification content from the device, and the output is the security action performed by the user.

[0120] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0121] This invention relates to a system that enhances the security of personal information in communication devices and enables flexible responses based on the user's emotional state. This system mainly consists of a server, a terminal, an emotion engine, and a user.

[0122] The server continuously collects the latest risk information from highly reliable sources. This allows the server to continuously update its database and assess risks with the most reliable information. The server also analyzes communication data transmitted from terminals and, along with past data breaches, analyzes the user's risk based on these analysis results.

[0123] The terminal is installed on the user's communication device and monitors normal operations such as making calls and sending / receiving messages. The terminal sends data about the user's actions to a server and waits for instructions from the server. Upon receiving instructions from the server, the terminal displays a warning to the user and, if necessary, provides specific countermeasures using guidance mechanisms.

[0124] The emotion engine is used to recognize the user's emotional state during operation. This engine analyzes data such as the user's facial expressions, voice tone, and operation speed to determine their current emotion. The emotion engine's data helps select accurate and appropriately tailored warning content and presentation methods. For example, if the user is feeling anxious, the emotion engine can display more detailed and reassuring guidance.

[0125] Users can follow the instructions on their device and take appropriate action based on guidance from the emotion engine. For example, if a risk is detected in the app when the user is in a hurry, the emotion engine will provide a flexible notification such as, "It's not urgent, but please be careful next time you use it."

[0126] In this way, the present invention aims to enhance the safety and convenience of individual users by providing security measures and enabling optimized responses that respond to the user's emotions.

[0127] The following describes the processing flow.

[0128] Step 1:

[0129] The server collects threat information from reliable sources and regularly updates its database. This ensures that it always maintains the latest threat information.

[0130] Step 2:

[0131] The device monitors the user's calls, messages, and app usage in real time, and records the data for each activity.

[0132] Step 3:

[0133] The terminal transmits the collected data to the server at regular intervals for use in risk analysis. The transmission protocol is lightweight and efficient.

[0134] Step 4:

[0135] The server analyzes the risks by comparing the received user operation data with risk information and past data breach information. AI is used to improve the accuracy of this analysis.

[0136] Step 5:

[0137] The emotion engine collects the user's facial expressions and voice during operation and evaluates their current emotional state. For example, it uses data obtained through the camera and microphone.

[0138] Step 6:

[0139] Based on the analysis results and the evaluation of the sentiment engine, the server generates individually optimized warning messages and suggested countermeasures.

[0140] Step 7:

[0141] The device displays warnings and guidance to the user based on instructions from the server. The displayed content is adjusted according to the user's emotional state.

[0142] Step 8:

[0143] Users should follow the instructions on their device and take necessary measures. For example, this might include deleting specific apps or stopping dangerous communications.

[0144] Step 9:

[0145] The server continuously updates its AI model based on user feedback and newly collected data, improving the accuracy of subsequent analyses.

[0146] (Example 2)

[0147] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0148] In recent years, the risk of personal information leaks and cyberattacks has increased when using communication devices. However, conventional security systems have often failed to provide warnings and guidance that take into account the user's emotional state, causing anxiety and burden. This can deprive users of the opportunity to make appropriate decisions, and there is a need for more flexible and individualized security responses.

[0149] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0150] In this invention, the server includes means for collecting risk information from a reliable external organization, means for monitoring communication data in communication equipment in real time, means for analyzing risks based on past leak information data and risk information collected in real time, means for issuing warnings according to the user's emotional state based on the analyzed risk assessment results, and means for analyzing the emotional state based on the user's actions and providing guidance according to the results. This enables flexible and personalized security responses according to the user's emotional state.

[0151] A "highly reliable external organization" generally refers to a public institution or professional organization that has a high level of credibility in ensuring the authenticity and security of data.

[0152] "Risk information" refers to information related to cybersecurity threats and the risk of personal information leakage, including virus detection information and warnings of unauthorized access.

[0153] "Communication equipment" refers to electronic devices used by users to make voice calls, send messages, access the internet, and perform other similar activities.

[0154] "Communication data" refers to all digital information transmitted and received through communication devices, and includes text messages, voice data, and internet browsing history.

[0155] "Past data breaches" refers to stored data related to past personal information breaches, which are used to assess the risk of similar new breaches.

[0156] "Means of risk analysis" refers to algorithms and processes that use collected data to detect and evaluate potential hazards from that data.

[0157] "Emotional state" refers to the psychological tendencies and emotional responses that a user exhibits during operation, and this is analyzed from data such as facial expressions and voice tone.

[0158] A "warning" refers to a notification or message that informs a user of a potential danger, allowing the user to recognize the risk.

[0159] "Guidance" refers to specific instructions and advice provided to help users take appropriate action.

[0160] The system of this invention is for securely and efficiently managing user communications. Its main components include a server, a terminal, an emotion engine, and the user.

[0161] Server Role

[0162] The server continuously collects the latest risk information from reliable external sources via API communication and stores this data in a database. Based on this information, the server analyzes the data using machine learning algorithms to assess the user's risk. Risk assessment is performed by comparing past data breaches with real-time data. This process makes it possible to generate appropriate warnings for individual users.

[0163] Terminal role

[0164] The terminal is installed on the user's communication device and monitors the user's communication data in real time, sending it to a server. The data is transmitted encrypted, and warnings are displayed to the user in response to instructions from the server. In this display, the terminal provides information using a display or voice assistant.

[0165] The role of the emotional engine

[0166] The emotion engine analyzes the user's facial expressions, voice tone, and operation speed to evaluate the user's emotional state in real time. It collects emotional data using image analysis software and speech recognition technology, and uses this data to adjust appropriate warnings and guidance. If the user is feeling anxious, for example, detailed guidance is provided to reassure them.

[0167] Specific application examples for users

[0168] For example, if a server detects a potential security risk while a user is using public Wi-Fi, the server sends a warning to the device saying, "There is a risk to your current network connection." If the emotion engine detects that the user is feeling anxious, it adds guidance such as, "Please review these steps to ensure your safety."

[0169] Examples of prompts for generative AI models

[0170] "Please suggest guidance for users who receive a security alert while using public Wi-Fi. The guidance should be considerate and designed to help users remain calm and follow the instructions."

[0171] By combining these elements, the system aims to improve user safety and convenience by providing flexible and personalized security responses based on user actions and emotional states.

[0172] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0173] Step 1:

[0174] The server collects risk information from reliable external sources. It receives risk information data obtained from the external source's API as input and stores it in a database. The output is the most recent stored risk information data. This data is then used to prepare the server for risk analysis using machine learning algorithms.

[0175] Step 2:

[0176] The terminal monitors the user's communication data in real time and sends it to the server as needed. It receives data from the user's calls and messages as input and checks for any anomalies. If an anomaly is detected, it encrypts the data and sends it to the server. The output is the address of the destination server and the encrypted data to be sent. This allows the server to receive data for user risk assessment.

[0177] Step 3:

[0178] The server performs a risk assessment based on communication data received from the terminal. The inputs used are encrypted user communication data and risk information and past data breach information stored in the database. This data is analyzed using an algorithm to calculate the risk level. The output is the calculated risk assessment result. Based on this result, the server generates a warning message.

[0179] Step 4:

[0180] The emotion engine analyzes the user's facial expressions, voice tone, and operation speed to evaluate the user's emotional state. It receives user behavior data collected by the device as input. Using image analysis and speech recognition technology, it determines the user's emotional state. The output is information about the evaluated emotional state. Based on this, the emotion engine instructs the server to adjust the warning content.

[0181] Step 5:

[0182] The server sends warnings and guidance generated according to the user's emotional state to the terminal. It receives risk assessment results and emotional state information as input, and determines appropriate warning content based on this. The output is the warning message and guidance sent to the user's terminal. This allows the user to obtain the information necessary to appropriately adjust their behavior.

[0183] Step 6:

[0184] The user selects an action based on the warnings and guidance received from the terminal. The input is the warning messages and guidance displayed on the terminal screen, which the user understands. The output is the action the user chooses, such as whether to continue or disconnect the network connection. The terminal feeds the user's selection back to the server to help with further improvements.

[0185] (Application Example 2)

[0186] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0187] Current communication devices lack sufficient means to ensure the security of personal information, and in particular, they have a challenge in that they cannot respond flexibly to the emotional state of the user. Furthermore, there is a need for mechanisms that ensure appropriate security without causing users unnecessary anxiety.

[0188] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0189] In this invention, the server includes means for collecting risk information from reliable sources, means for monitoring communication information in communication devices in real time, and means for analyzing risks based on past leakage information. This allows for the detection of the user's emotional state and the adjustment of warning content based on that emotion, thereby enhancing the security of personal information and enabling flexible responses that respond to the user's emotions.

[0190] A "highly reliable source of information" is an organization or service whose information is recognized for its accuracy and reliability, and it plays an important role in gathering information on potential risks.

[0191] "Communication information" refers to all data and signals transmitted and received through a user's communication device, and is subject to security monitoring.

[0192] "Past data breaches" refers to data from past data breaches and is used as a comparative standard for analyzing risk.

[0193] "Means of risk analysis" refers to methods and processes for evaluating potential security risks based on collected information and past data breaches.

[0194] "Means of detecting emotional state" refers to technologies and systems that analyze data such as the user's facial expressions, voice, and operation speed to determine their current emotions.

[0195] "Adjusting warning content" refers to the act of flexibly changing the content and format of warnings presented according to the user's emotional state.

[0196] "Flexible response" refers to the ability to take optimized responses and actions according to the situation and conditions.

[0197] The system that realizes this invention consists of a server, a terminal, and an emotion engine. The server collects risk information from reliable sources and updates its database to keep it constantly up-to-date. This makes it possible to assess risk by comparing it with past leaks. The terminal is installed on the user's communication device and monitors communication information in real time. This allows for an assessment of whether the user's actions are safe and, if necessary, receives warning instructions from the server.

[0198] The emotion engine analyzes data such as the user's facial expressions, voice, and operation speed to determine their current emotional state. This emotion data is used to adjust the content of warnings presented according to the user's emotions. For example, if the user is showing anxiety, more detailed and reassuring information will be provided.

[0199] For example, when a user is using a banking app on their smartphone, the server monitors communication information through the device and detects potential security risks. The emotion engine reads the user's voice to indicate anxiety and, if the risk level is low, displays a flexible warning message on the device such as, "Don't worry, the risk is low. Please be careful next time."

[0200] The programs in this system are written in Python and use the emotion_recognition library for emotion recognition. The SecurityServer module is responsible for risk assessment and risk information gathering, and provides appropriate guidance to the user. By utilizing a generative AI model, it is possible to incorporate more human-like elements into the responses. An example of a prompt message is, "Generate a notification message if the user shows anxiety while using the app and the risk level is 3."

[0201] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0202] Step 1:

[0203] The device monitors the user's communication information in real time. The input is communication data from each application the user is running on their smartphone. The output is a report of detected abnormal communication to the server. This process involves analyzing the communication protocol and extracting data that deviates from normal patterns.

[0204] Step 2:

[0205] The server collects threat information from reliable sources and updates the database. The input is the latest threat information obtained from reliable sources. The output is the updated database information. In this step, the latest threat information is obtained using external APIs or data feeds and integrated into the internal database.

[0206] Step 3:

[0207] The server compares communication data reported from terminals with past data breaches to analyze the risk. The inputs are the communication data received from the terminals and existing data breaches. The output is the analyzed risk level. Here, a statistical model is used to evaluate the correlation with past data and calculate the degree of risk.

[0208] Step 4:

[0209] The emotion engine detects the user's emotional state. Inputs include user facial expression data, voice data, and operation speed data. The detected emotional state is sent to the server as output. This process uses the emotion_recognition library to perform emotion recognition by combining image and voice analysis.

[0210] Step 5:

[0211] The server adjusts the warning content based on risk level and sentiment data and sends it to the terminal. The input is the analyzed risk level and detected sentiment state. The output is the adjusted warning message for display to the user. A specific generative AI model is used to generate flexible, sentiment-sensitive responses.

[0212] Step 6:

[0213] The user receives a warning message from their device and takes the necessary action. The input is the warning message displayed on the device. The output is the action taken by the user. In this step, the user can ensure their safety by deciding on actual actions based on the information presented and following the guidance.

[0214] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0215] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0216] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0217] [Second Embodiment]

[0218] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0219] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0220] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0221] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0222] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0223] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0224] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0225] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0226] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0227] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0228] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0229] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0230] This invention relates to a security system for secure communication via communication devices. This system consists of multiple servers, terminals, and users.

[0231] The server continuously collects risk information from reliable sources. This ensures that the latest threat information is reflected in the database and that it is constantly updated. The server also receives communication data transmitted in real time from each terminal and analyzes this data by comparing it with past leaked information data. The server uses AI to perform this analysis and determine the level of risk associated with the user's communication.

[0232] The terminal is installed on the user's communication device and monitors the user's daily operations. Each time communication occurs, the terminal sends information to the server, using a lightweight and efficient protocol to avoid performance degradation. Upon receiving instructions from the server, the terminal displays a warning message to the user and, if necessary, provides guidance suggesting specific corrective actions. This guidance includes actions to take immediately and suggestions for configuration changes.

[0233] Users can take quick and appropriate action based on real-time warnings and guidance from their devices. For example, if an untrusted application is installed, the device will display a warning such as, "This app has caused security risks in the past. We recommend removing it."

[0234] In this way, the present invention provides a comprehensive solution to enhance the security of users' digital environments and proactively prevent risks such as the leakage of personal information and spam communications.

[0235] The following describes the processing flow.

[0236] Step 1:

[0237] The server collects threat information from reliable sources and stores it in a database. This ensures that the system always maintains the most up-to-date threat information.

[0238] Step 2:

[0239] The device monitors user calls, messages, and app usage, and temporarily records data related to each action. The monitoring is designed not to impact user performance.

[0240] Step 3:

[0241] The terminal periodically sends recorded data to the server. This data transfer uses a secure and efficient protocol to prevent delays and excessive bandwidth consumption.

[0242] Step 4:

[0243] The server analyzes the received communication data and compares it with past data breaches and risk information. Using AI, it assesses the data's risk level and generates immediate warnings as needed.

[0244] Step 5:

[0245] The server sends instructions to the terminal based on the analysis results. These instructions include a decision on whether or not to take a specific action.

[0246] Step 6:

[0247] The device displays a warning message to the user, following instructions from the server. The warning includes details of the detected risk and recommended actions.

[0248] Step 7:

[0249] Users choose the necessary action based on the warnings and guidance provided by their device. This may include deleting apps, stopping communication, or changing settings.

[0250] Step 8:

[0251] The server analyzes user behavior and newly collected data to update the AI ​​model, thereby improving the accuracy of future risk assessment and detection.

[0252] (Example 1)

[0253] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0254] Conventional security systems have been insufficient in collecting risk information during communications and analyzing communication data, making it difficult to quickly detect the risk of information leaks and unauthorized access. Furthermore, the lack of means to provide users with specific warnings and countermeasures in a timely manner meant that users missed opportunities to take appropriate action themselves.

[0255] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0256] In this invention, the server includes means for acquiring risk information from a reliable data source, means for monitoring data communication in the information processing device in real time, and means for evaluating risk based on past information leakage data. This makes it possible to quickly and efficiently detect the latest threats and immediately propose specific countermeasures to users.

[0257] A "highly reliable data source" refers to an information provider whose reliability and credibility are guaranteed in order to provide security information and risk information.

[0258] An "information processing device" refers to an electronic device used for communication and data processing.

[0259] "Data communication" refers to the process of sending and receiving information over a network.

[0260] "Information leakage data" refers to records and information related to the unauthorized leakage or disclosure of data that has occurred in the past.

[0261] "Means of risk assessment" refers to methods or processes for determining the extent to which communications or data pose a security risk.

[0262] A "lightweight and efficient communication protocol" refers to a protocol designed to improve communication efficiency and enable rapid data transmission and reception.

[0263] "Means of proposing specific countermeasures" refers to a mechanism that indicates the actions or changes that users should take in response to specific security risks.

[0264] This invention is a security system for secure communication, and is mainly composed of a server, a terminal, and a user.

[0265] The server acquires risk information from reliable data sources and stores it in a database. The database utilizes a cloud-based storage system and is always accessible. The server also employs generative AI models to analyze communication data transmitted from terminals. This allows it to assess communication risks based on past data breaches.

[0266] The terminal is a software application installed on the user's device, responsible for monitoring the user's communications in real time. By using lightweight and efficient communication protocols such as MQTT, the terminal can quickly send data to the server. Furthermore, based on the evaluation results from the server, the terminal provides the user with necessary warnings and specific countermeasures. This process enables the user to take timely and appropriate action.

[0267] Through this system, users can receive real-time warnings and guidance to protect the security of their digital environment. For example, if a suspicious application is installed, the device will warn, "This app has caused security risks in the past. We recommend removing it," allowing users to take immediate action. Furthermore, by using a prompt such as "How can I display a warning when installing an untrusted app?" as an example of a prompt to input into the generating AI model, more specific advice and information can be obtained.

[0268] In this way, the present invention provides an effective means for users to safely utilize the digital environment.

[0269] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0270] Step 1:

[0271] The server acquires threat information from reliable external data sources. It receives threat information periodically via an API as input and stores it in a database in JSON format. As part of data processing, it integrates the received information into an existing data structure to maintain up-to-date threat information.

[0272] Step 2:

[0273] The terminal operates on the user's communication device and monitors communication data in real time. Specifically, it captures network traffic and formats it into the required format. As input, it collects relevant data (e.g., IP address and port number) each time communication occurs and sends it to the server. The output is this communication data, sent using the lightweight MQTT protocol.

[0274] Step 3:

[0275] The server receives communication data sent from the terminal and performs data analysis using a generating AI model. The input is communication data from the terminal, which the AI ​​model analyzes, compares with past data breaches, and calculates a risk score. The output of this analysis is a risk assessment result, and further actions are decided based on this result.

[0276] Step 4:

[0277] The server immediately sends a warning message to the terminal if the risk score exceeds a certain threshold. Specifically, it retrieves the relevant warning message from the database and notifies the terminal using the MQTT protocol. The input is the risk assessment result, and the output is the warning message.

[0278] Step 5:

[0279] Based on the warning message received from the server, the terminal displays a notification to the user. Specifically, a warning is popped up on the user screen via the GUI. There is a warning message from the server as input, and the output is a visual warning display to the user. At this point, additional countermeasure information is also displayed to present the user with a course of action according to the situation.

[0280] Step 6:

[0281] The user receives the warning from the terminal and selects an appropriate action based on the presented guidance. Specific actions include uninstalling a suspicious application or changing settings. The input is the warning and guidance from the terminal, and the output is the actual action taken by the user to reduce the security risk.

[0282] (Application Example 1)

[0283] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0284] In the digital environment, security threats are increasing, and users are required to quickly and appropriately recognize and act on those risks. However, conventional systems are insufficient in providing real-time threat recognition and specific countermeasure guidance. Therefore, there is a need for a method to quickly evaluate the potential communication risks faced by users and provide accurate action guidelines.

[0285] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0286] In this invention, the server includes means for collecting danger information from highly reliable institutions, means for monitoring communication data in a communication device in real time, and means for analyzing risks based on past leakage information data. As a result, users can immediately evaluate the risks associated with communication and receive guidance in real time for taking appropriate actions.

[0287] A "highly reliable institution" is a specialized organization that guarantees the accuracy and up-to-dateness of information and provides data related to security threats.

[0288] The "means for collecting danger information" is a method or device for efficiently acquiring security-related information provided by highly reliable institutions.

[0289] A "communication device" is an electronic device that transmits and receives information and is connected to other devices via data communication.

[0290] The "means for monitoring communication data in real time" is a system or method for immediately observing the transmitted and received data and determining whether there are threats or abnormalities.

[0291] "Past leakage information data" is data obtained from previous information leakage cases and is accumulated records and information used for security analysis.

[0292] The "means for analyzing risks" is a calculation method or algorithm for comparing communication data with leakage information data and identifying potential security risks.

[0293] The "means for issuing a warning to the user based on the analysis result" is a method for informing the user of the danger based on the result of the risk analysis and providing a notification for ensuring safety.

[0294] The "display means for displaying recommended actions based on risk assessment" is a method or device for visually presenting specific action guidelines to the user according to the risk level determined by the analysis.

[0295] "Means of providing real-time guidance on user behavior" refers to a system that provides instructions to prompt appropriate actions immediately based on the user's current actions and circumstances.

[0296] The system for implementing the present invention mainly consists of a server, terminals, and users. The server continuously collects security risk information from reliable sources and maintains the latest threat information by updating its database in real time. The server also immediately monitors communication data transmitted from each terminal and analyzes the risk by comparing it with past leaked information data.

[0297] The terminal is installed on the user's communication device and detects the user's daily communication activities. The terminal forwards incoming and outgoing data packets to the server using a lightweight and efficient protocol. The server receives this data and, through an AI-based risk assessment algorithm, verifies the security of the communication and decides whether or not to send a warning to the user.

[0298] Users can take immediate action against suspicious communications by following warning messages and guidance from their devices. This system enhances security by displaying recommended actions based on risk assessments on the user's device and providing visually clear instructions.

[0299] For example, if a user connects to public Wi-Fi, the system immediately assesses the risk and provides a warning and countermeasures such as, "This network may have a low level of security. Please choose another network or use a VPN."

[0300] By utilizing the generative AI model, it is possible to learn the patterns of threat information and generate highly accurate warnings. For example, it is conceivable to use a prompt sentence such as "Please develop an AI model for evaluating the security risks of newly installed applications. Based on past data leakage incidents, explain the mechanism for scoring the degree of danger and displaying warnings to users."

[0301] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0302] Step 1:

[0303] The server regularly collects threat information from highly reliable institutions. At this time, new security incident information is added to the database through the API, and the training dataset for the AI model is updated. The input is the latest threat information data obtained from the institution, and the output is the updated database.

[0304] Step 2:

[0305] The terminal monitors communication data in real time on the user's communication device. Here, the transmitted and received data packets are captured and sent to the server using a lightweight protocol. The input is the user's real-time communication data, and the output is the transfer of data packets to the server.

[0306] Step 3:

[0307] The server analyzes the received communication data based on a risk assessment algorithm. The AI model compares the communication data with past leakage information and calculates the threat level. The input is the communication data transmitted from the terminal, and the output is the calculated risk score.

[0308] Step 4:

[0309] The server will issue a warning to the user if necessary, based on the risk score. Specifically, it will generate a warning message based on the result and send it to the terminal. The input is the risk score, and the output is the warning message to the user.

[0310] Step 5:

[0311] The device displays received warning messages to the user and provides appropriate guidance. Here, recommended actions and changes to security settings are communicated via a notification screen. The input is the warning message from the server, and the output is a notification prompting user action.

[0312] Step 6:

[0313] The user selects actions based on warnings through their device and modifies communication device settings as needed. This includes actions such as selecting a new network or removing threatening applications. The input is the notification content from the device, and the output is the security action performed by the user.

[0314] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0315] This invention relates to a system that enhances the security of personal information in communication devices and enables flexible responses based on the user's emotional state. This system mainly consists of a server, a terminal, an emotion engine, and a user.

[0316] The server continuously collects the latest risk information from highly reliable sources. This allows the server to continuously update its database and assess risks with the most reliable information. The server also analyzes communication data transmitted from terminals and, along with past data breaches, analyzes the user's risk based on these analysis results.

[0317] The terminal is installed on the user's communication device and monitors normal operations such as making calls and sending / receiving messages. The terminal sends data about the user's actions to a server and waits for instructions from the server. Upon receiving instructions from the server, the terminal displays a warning to the user and, if necessary, provides specific countermeasures using guidance mechanisms.

[0318] The emotion engine is used to recognize the user's emotional state during operation. This engine analyzes data such as the user's facial expressions, voice tone, and operation speed to determine their current emotion. The emotion engine's data helps select accurate and appropriately tailored warning content and presentation methods. For example, if the user is feeling anxious, the emotion engine can display more detailed and reassuring guidance.

[0319] Users can follow the instructions on their device and take appropriate action based on guidance from the emotion engine. For example, if a risk is detected in the app when the user is in a hurry, the emotion engine will provide a flexible notification such as, "It's not urgent, but please be careful next time you use it."

[0320] In this way, the present invention aims to enhance the safety and convenience of individual users by providing security measures and enabling optimized responses that respond to the user's emotions.

[0321] The following describes the processing flow.

[0322] Step 1:

[0323] The server collects threat information from reliable sources and regularly updates its database. This ensures that it always maintains the latest threat information.

[0324] Step 2:

[0325] The device monitors the user's calls, messages, and app usage in real time, and records the data for each activity.

[0326] Step 3:

[0327] The terminal transmits the collected data to the server at regular intervals for use in risk analysis. The transmission protocol is lightweight and efficient.

[0328] Step 4:

[0329] The server analyzes the risks by comparing the received user operation data with risk information and past data breach information. AI is used to improve the accuracy of this analysis.

[0330] Step 5:

[0331] The emotion engine collects the user's facial expressions and voice during operation and evaluates their current emotional state. For example, it uses data obtained through the camera and microphone.

[0332] Step 6:

[0333] Based on the analysis results and the evaluation of the sentiment engine, the server generates individually optimized warning messages and suggested countermeasures.

[0334] Step 7:

[0335] The device displays warnings and guidance to the user based on instructions from the server. The displayed content is adjusted according to the user's emotional state.

[0336] Step 8:

[0337] Users should follow the instructions on their device and take necessary measures. For example, this might include deleting specific apps or stopping dangerous communications.

[0338] Step 9:

[0339] The server continuously updates its AI model based on user feedback and newly collected data, improving the accuracy of subsequent analyses.

[0340] (Example 2)

[0341] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0342] In recent years, the risk of personal information leaks and cyberattacks has increased when using communication devices. However, conventional security systems have often failed to provide warnings and guidance that take into account the user's emotional state, causing anxiety and burden. This can deprive users of the opportunity to make appropriate decisions, and there is a need for more flexible and individualized security responses.

[0343] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0344] In this invention, the server includes means for collecting risk information from a reliable external organization, means for monitoring communication data in communication equipment in real time, means for analyzing risks based on past leak information data and risk information collected in real time, means for issuing warnings according to the user's emotional state based on the analyzed risk assessment results, and means for analyzing the emotional state based on the user's actions and providing guidance according to the results. This enables flexible and personalized security responses according to the user's emotional state.

[0345] A "highly reliable external organization" generally refers to a public institution or professional organization that has a high level of credibility in ensuring the authenticity and security of data.

[0346] "Risk information" refers to information related to cybersecurity threats and the risk of personal information leakage, including virus detection information and warnings of unauthorized access.

[0347] "Communication equipment" refers to electronic devices used by users to make voice calls, send messages, access the internet, and perform other similar activities.

[0348] "Communication data" refers to all digital information transmitted and received through communication devices, and includes text messages, voice data, and internet browsing history.

[0349] "Past data breaches" refers to stored data related to past personal information breaches, which are used to assess the risk of similar new breaches.

[0350] "Means of risk analysis" refers to algorithms and processes that use collected data to detect and evaluate potential hazards from that data.

[0351] "Emotional state" refers to the psychological tendencies and emotional responses that a user exhibits during operation, and this is analyzed from data such as facial expressions and voice tone.

[0352] A "warning" refers to a notification or message that informs a user of a potential danger, allowing the user to recognize the risk.

[0353] "Guidance" refers to specific instructions and advice provided to help users take appropriate action.

[0354] The system of this invention is for securely and efficiently managing user communications. Its main components include a server, a terminal, an emotion engine, and the user.

[0355] Server Role

[0356] The server continuously collects the latest risk information from reliable external sources via API communication and stores this data in a database. Based on this information, the server analyzes the data using machine learning algorithms to assess the user's risk. Risk assessment is performed by comparing past data breaches with real-time data. This process makes it possible to generate appropriate warnings for individual users.

[0357] Terminal role

[0358] The terminal is installed on the user's communication device and monitors the user's communication data in real time, sending it to a server. The data is transmitted encrypted, and warnings are displayed to the user in response to instructions from the server. In this display, the terminal provides information using a display or voice assistant.

[0359] The role of the emotional engine

[0360] The emotion engine analyzes the user's facial expressions, voice tone, and operation speed to evaluate the user's emotional state in real time. It collects emotional data using image analysis software and speech recognition technology, and uses this data to adjust appropriate warnings and guidance. If the user is feeling anxious, for example, detailed guidance is provided to reassure them.

[0361] Specific application examples for users

[0362] For example, if a server detects a potential security risk while a user is using public Wi-Fi, the server sends a warning to the device saying, "There is a risk to your current network connection." If the emotion engine detects that the user is feeling anxious, it adds guidance such as, "Please review these steps to ensure your safety."

[0363] Examples of prompts for generative AI models

[0364] "Please suggest guidance for users who receive a security alert while using public Wi-Fi. The guidance should be considerate and designed to help users remain calm and follow the instructions."

[0365] By combining these elements, the system aims to improve user safety and convenience by providing flexible and personalized security responses based on user actions and emotional states.

[0366] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0367] Step 1:

[0368] The server collects risk information from reliable external sources. It receives risk information data obtained from the external source's API as input and stores it in a database. The output is the most recent stored risk information data. This data is then used to prepare the server for risk analysis using machine learning algorithms.

[0369] Step 2:

[0370] The terminal monitors the user's communication data in real time and sends it to the server as needed. It receives data from the user's calls and messages as input and checks for any anomalies. If an anomaly is detected, it encrypts the data and sends it to the server. The output is the address of the destination server and the encrypted data to be sent. This allows the server to receive data for user risk assessment.

[0371] Step 3:

[0372] The server performs a risk assessment based on communication data received from the terminal. The inputs used are encrypted user communication data and risk information and past data breach information stored in the database. This data is analyzed using an algorithm to calculate the risk level. The output is the calculated risk assessment result. Based on this result, the server generates a warning message.

[0373] Step 4:

[0374] The emotion engine analyzes the user's facial expressions, voice tone, and operation speed to evaluate the user's emotional state. It receives user behavior data collected by the device as input. Using image analysis and speech recognition technology, it determines the user's emotional state. The output is information about the evaluated emotional state. Based on this, the emotion engine instructs the server to adjust the warning content.

[0375] Step 5:

[0376] The server sends warnings and guidance generated according to the user's emotional state to the terminal. It receives risk assessment results and emotional state information as input, and determines appropriate warning content based on this. The output is the warning message and guidance sent to the user's terminal. This allows the user to obtain the information necessary to appropriately adjust their behavior.

[0377] Step 6:

[0378] The user selects an action based on the warnings and guidance received from the terminal. The input is the warning messages and guidance displayed on the terminal screen, which the user understands. The output is the action the user chooses, such as whether to continue or disconnect the network connection. The terminal feeds the user's selection back to the server to help with further improvements.

[0379] (Application Example 2)

[0380] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0381] Current communication devices lack sufficient means to ensure the security of personal information, and in particular, they have a challenge in that they cannot respond flexibly to the emotional state of the user. Furthermore, there is a need for mechanisms that ensure appropriate security without causing users unnecessary anxiety.

[0382] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0383] In this invention, the server includes means for collecting risk information from reliable sources, means for monitoring communication information in communication devices in real time, and means for analyzing risks based on past leakage information. This allows for the detection of the user's emotional state and the adjustment of warning content based on that emotion, thereby enhancing the security of personal information and enabling flexible responses that respond to the user's emotions.

[0384] A "highly reliable source of information" is an organization or service whose information is recognized for its accuracy and reliability, and it plays an important role in gathering information on potential risks.

[0385] "Communication information" refers to all data and signals transmitted and received through a user's communication device, and is subject to security monitoring.

[0386] "Past data breaches" refers to data from past data breaches and is used as a comparative standard for analyzing risk.

[0387] "Means of risk analysis" refers to methods and processes for evaluating potential security risks based on collected information and past data breaches.

[0388] "Means of detecting emotional state" refers to technologies and systems that analyze data such as the user's facial expressions, voice, and operation speed to determine their current emotions.

[0389] "Adjusting warning content" refers to the act of flexibly changing the content and format of warnings presented according to the user's emotional state.

[0390] "Flexible response" refers to the ability to take optimized responses and actions according to the situation and conditions.

[0391] The system that realizes this invention consists of a server, a terminal, and an emotion engine. The server collects risk information from reliable sources and updates its database to keep it constantly up-to-date. This makes it possible to assess risk by comparing it with past leaks. The terminal is installed on the user's communication device and monitors communication information in real time. This allows for an assessment of whether the user's actions are safe and, if necessary, receives warning instructions from the server.

[0392] The emotion engine analyzes data such as the user's facial expressions, voice, and operation speed to determine their current emotional state. This emotion data is used to adjust the content of warnings presented according to the user's emotions. For example, if the user is showing anxiety, more detailed and reassuring information will be provided.

[0393] For example, when a user is using a banking app on their smartphone, the server monitors communication information through the device and detects potential security risks. The emotion engine reads the user's voice to indicate anxiety and, if the risk level is low, displays a flexible warning message on the device such as, "Don't worry, the risk is low. Please be careful next time."

[0394] The programs in this system are written in Python and use the emotion_recognition library for emotion recognition. The SecurityServer module is responsible for risk assessment and risk information gathering, and provides appropriate guidance to the user. By utilizing a generative AI model, it is possible to incorporate more human-like elements into the responses. An example of a prompt message is, "Generate a notification message if the user shows anxiety while using the app and the risk level is 3."

[0395] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0396] Step 1:

[0397] The device monitors the user's communication information in real time. The input is communication data from each application the user is running on their smartphone. The output is a report of detected abnormal communication to the server. This process involves analyzing the communication protocol and extracting data that deviates from normal patterns.

[0398] Step 2:

[0399] The server collects threat information from reliable sources and updates the database. The input is the latest threat information obtained from reliable sources. The output is the updated database information. In this step, the latest threat information is obtained using external APIs or data feeds and integrated into the internal database.

[0400] Step 3:

[0401] The server compares communication data reported from terminals with past data breaches to analyze the risk. The inputs are the communication data received from the terminals and existing data breaches. The output is the analyzed risk level. Here, a statistical model is used to evaluate the correlation with past data and calculate the degree of risk.

[0402] Step 4:

[0403] The emotion engine detects the user's emotional state. Inputs include user facial expression data, voice data, and operation speed data. The detected emotional state is sent to the server as output. This process uses the emotion_recognition library to perform emotion recognition by combining image and voice analysis.

[0404] Step 5:

[0405] The server adjusts the warning content based on risk level and sentiment data and sends it to the terminal. The input is the analyzed risk level and detected sentiment state. The output is the adjusted warning message for display to the user. A specific generative AI model is used to generate flexible, sentiment-sensitive responses.

[0406] Step 6:

[0407] The user receives a warning message from their device and takes the necessary action. The input is the warning message displayed on the device. The output is the action taken by the user. In this step, the user can ensure their safety by deciding on actual actions based on the information presented and following the guidance.

[0408] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0409] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0410] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0411] [Third Embodiment]

[0412] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0413] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0414] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0415] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0416] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0417] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0418] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0419] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0420] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0421] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0422] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0423] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0424] This invention relates to a security system for secure communication via communication devices. This system consists of multiple servers, terminals, and users.

[0425] The server continuously collects risk information from reliable sources. This ensures that the latest threat information is reflected in the database and that it is constantly updated. The server also receives communication data transmitted in real time from each terminal and analyzes this data by comparing it with past leaked information data. The server uses AI to perform this analysis and determine the level of risk associated with the user's communication.

[0426] The terminal is installed on the user's communication device and monitors the user's daily operations. Each time communication occurs, the terminal sends information to the server, using a lightweight and efficient protocol to avoid performance degradation. Upon receiving instructions from the server, the terminal displays a warning message to the user and, if necessary, provides guidance suggesting specific corrective actions. This guidance includes actions to take immediately and suggestions for configuration changes.

[0427] Users can take quick and appropriate action based on real-time warnings and guidance from their devices. For example, if an untrusted application is installed, the device will display a warning such as, "This app has caused security risks in the past. We recommend removing it."

[0428] In this way, the present invention provides a comprehensive solution to enhance the security of users' digital environments and proactively prevent risks such as the leakage of personal information and spam communications.

[0429] The following describes the processing flow.

[0430] Step 1:

[0431] The server collects threat information from reliable sources and stores it in a database. This ensures that the system always maintains the most up-to-date threat information.

[0432] Step 2:

[0433] The device monitors user calls, messages, and app usage, and temporarily records data related to each action. The monitoring is designed not to impact user performance.

[0434] Step 3:

[0435] The terminal periodically sends recorded data to the server. This data transfer uses a secure and efficient protocol to prevent delays and excessive bandwidth consumption.

[0436] Step 4:

[0437] The server analyzes the received communication data and compares it with past data breaches and risk information. Using AI, it assesses the data's risk level and generates immediate warnings as needed.

[0438] Step 5:

[0439] The server sends instructions to the terminal based on the analysis results. These instructions include a decision on whether or not to take a specific action.

[0440] Step 6:

[0441] The device displays a warning message to the user, following instructions from the server. The warning includes details of the detected risk and recommended actions.

[0442] Step 7:

[0443] Users choose the necessary action based on the warnings and guidance provided by their device. This may include deleting apps, stopping communication, or changing settings.

[0444] Step 8:

[0445] The server analyzes user behavior and newly collected data to update the AI ​​model, thereby improving the accuracy of future risk assessment and detection.

[0446] (Example 1)

[0447] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0448] Conventional security systems have been insufficient in collecting risk information during communications and analyzing communication data, making it difficult to quickly detect the risk of information leaks and unauthorized access. Furthermore, the lack of means to provide users with specific warnings and countermeasures in a timely manner meant that users missed opportunities to take appropriate action themselves.

[0449] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0450] In this invention, the server includes means for acquiring risk information from a reliable data source, means for monitoring data communication in the information processing device in real time, and means for evaluating risk based on past information leakage data. This makes it possible to quickly and efficiently detect the latest threats and immediately propose specific countermeasures to users.

[0451] A "highly reliable data source" refers to an information provider whose reliability and credibility are guaranteed in order to provide security information and risk information.

[0452] An "information processing device" refers to an electronic device used for communication and data processing.

[0453] "Data communication" refers to the process of sending and receiving information over a network.

[0454] "Information leakage data" refers to records and information related to the unauthorized leakage or disclosure of data that has occurred in the past.

[0455] "Means of risk assessment" refers to methods or processes for determining the extent to which communications or data pose a security risk.

[0456] A "lightweight and efficient communication protocol" refers to a protocol designed to improve communication efficiency and enable rapid data transmission and reception.

[0457] "Means of proposing specific countermeasures" refers to a mechanism that indicates the actions or changes that users should take in response to specific security risks.

[0458] This invention is a security system for secure communication, and is mainly composed of a server, a terminal, and a user.

[0459] The server acquires risk information from reliable data sources and stores it in a database. The database utilizes a cloud-based storage system and is always accessible. The server also employs generative AI models to analyze communication data transmitted from terminals. This allows it to assess communication risks based on past data breaches.

[0460] The terminal is a software application installed on the user's device, responsible for monitoring the user's communications in real time. By using lightweight and efficient communication protocols such as MQTT, the terminal can quickly send data to the server. Furthermore, based on the evaluation results from the server, the terminal provides the user with necessary warnings and specific countermeasures. This process enables the user to take timely and appropriate action.

[0461] Through this system, users can receive real-time warnings and guidance to protect the security of their digital environment. For example, if a suspicious application is installed, the device will warn, "This app has caused security risks in the past. We recommend removing it," allowing users to take immediate action. Furthermore, by using a prompt such as "How can I display a warning when installing an untrusted app?" as an example of a prompt to input into the generating AI model, more specific advice and information can be obtained.

[0462] In this way, the present invention provides an effective means for users to safely utilize the digital environment.

[0463] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0464] Step 1:

[0465] The server acquires threat information from reliable external data sources. It receives threat information periodically via an API as input and stores it in a database in JSON format. As part of data processing, it integrates the received information into an existing data structure to maintain up-to-date threat information.

[0466] Step 2:

[0467] The terminal operates on the user's communication device and monitors communication data in real time. Specifically, it captures network traffic and formats it into the required format. As input, it collects relevant data (e.g., IP address and port number) each time communication occurs and sends it to the server. The output is this communication data, sent using the lightweight MQTT protocol.

[0468] Step 3:

[0469] The server receives communication data sent from the terminal and performs data analysis using a generating AI model. The input is communication data from the terminal, which the AI ​​model analyzes, compares with past data breaches, and calculates a risk score. The output of this analysis is a risk assessment result, and further actions are decided based on this result.

[0470] Step 4:

[0471] The server immediately sends a warning message to the terminal if the risk score exceeds a certain threshold. Specifically, it retrieves the relevant warning message from the database and notifies the terminal using the MQTT protocol. The input is the risk assessment result, and the output is the warning message.

[0472] Step 5:

[0473] The terminal displays a notification to the user based on a warning message received from the server. Specifically, it displays a warning as a pop-up on the user screen via a GUI. The input is a warning message from the server, and the output is a visual warning display to the user. Additional countermeasures are also displayed at this point to suggest appropriate actions to the user.

[0474] Step 6:

[0475] The user receives warnings from the device and chooses appropriate action based on the guidance provided. Specific actions include uninstalling suspicious applications and changing settings. The input is the warnings and guidance from the device, while the output is the actual action taken by the user to mitigate security risks.

[0476] (Application Example 1)

[0477] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0478] Security threats in the digital environment are increasing, and users are required to recognize and act quickly and appropriately on these risks. However, conventional systems are insufficient in providing real-time threat recognition and specific countermeasures guidance. Therefore, there is a need for a method to quickly assess potential communication risks faced by users and provide accurate guidance on action.

[0479] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0480] In this invention, the server includes means for collecting risk information from a reliable source, means for monitoring communication data in a communication device in real time, and means for analyzing risk based on past leaked information data. This allows users to immediately assess the risks associated with communication and receive real-time guidance for taking appropriate action.

[0481] A "highly reliable organization" is a professional organization that guarantees the accuracy and timeliness of its information and provides data on security threats.

[0482] "Means for collecting risk information" refers to methods and devices for efficiently obtaining security-related information provided by reliable organizations.

[0483] A "communication device" is an electronic device that transmits and receives information and is connected to other devices via data communication.

[0484] "Means of monitoring communication data in real time" refers to systems and methods for immediately observing transmitted and received data to determine whether there are any threats or anomalies.

[0485] "Past data breaches" refers to data obtained from past data breaches, which are accumulated records and information used for security analysis.

[0486] "Means of risk analysis" refer to calculation methods and algorithms used to compare communication data with leaked information data and identify potential security risks.

[0487] "Means of issuing warnings to users based on analysis results" refers to methods of informing users of potential hazards based on the results of risk analysis and providing notifications to ensure their safety.

[0488] A "display means for showing recommended actions based on risk assessment" refers to a method or device that visually presents specific action guidelines to the user according to the risk level determined by the analysis.

[0489] "Means of providing real-time guidance on user behavior" refers to a system that provides instructions to prompt appropriate actions immediately based on the user's current actions and circumstances.

[0490] The system for implementing the present invention mainly consists of a server, terminals, and users. The server continuously collects security risk information from reliable sources and maintains the latest threat information by updating its database in real time. The server also immediately monitors communication data transmitted from each terminal and analyzes the risk by comparing it with past leaked information data.

[0491] The terminal is installed on the user's communication device and detects the user's daily communication activities. The terminal forwards incoming and outgoing data packets to the server using a lightweight and efficient protocol. The server receives this data and, through an AI-based risk assessment algorithm, verifies the security of the communication and decides whether or not to send a warning to the user.

[0492] Users can take immediate action against suspicious communications by following warning messages and guidance from their devices. This system enhances security by displaying recommended actions based on risk assessments on the user's device and providing visually clear instructions.

[0493] For example, if a user connects to public Wi-Fi, the system immediately assesses the risk and provides a warning and countermeasures such as, "This network may have a low level of security. Please choose another network or use a VPN."

[0494] By utilizing generative AI models, it is possible to learn patterns in threat intelligence and generate highly accurate warnings. For example, a prompt such as, "Develop an AI model to assess the security risks of newly installed applications. Describe a mechanism that scores the risk level based on past data breach incidents and displays a warning to the user," could be used.

[0495] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0496] Step 1:

[0497] The server regularly collects security risk information from reliable sources. During this process, new security incident information is added to the database via an API, updating the training dataset for the AI ​​model. The input is the latest security risk data obtained from the sources, and the output is the updated database.

[0498] Step 2:

[0499] The terminal monitors communication data in real time using the user's communication device. Here, it captures incoming and outgoing data packets and sends them to the server using a lightweight protocol. The input is the user's real-time communication data, and the output is the transfer of data packets to the server.

[0500] Step 3:

[0501] The server analyzes the received communication data based on a risk assessment algorithm. An AI model compares the communication data with past data breaches to calculate the threat level. The input is the communication data sent from the terminal, and the output is the calculated risk score.

[0502] Step 4:

[0503] The server will issue a warning to the user if necessary, based on the risk score. Specifically, it will generate a warning message based on the result and send it to the terminal. The input is the risk score, and the output is the warning message to the user.

[0504] Step 5:

[0505] The device displays received warning messages to the user and provides appropriate guidance. Here, recommended actions and changes to security settings are communicated via a notification screen. The input is the warning message from the server, and the output is a notification prompting user action.

[0506] Step 6:

[0507] The user selects actions based on warnings through their device and modifies communication device settings as needed. This includes actions such as selecting a new network or removing threatening applications. The input is the notification content from the device, and the output is the security action performed by the user.

[0508] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0509] This invention relates to a system that enhances the security of personal information in communication devices and enables flexible responses based on the user's emotional state. This system mainly consists of a server, a terminal, an emotion engine, and a user.

[0510] The server continuously collects the latest risk information from highly reliable sources. This allows the server to continuously update its database and assess risks with the most reliable information. The server also analyzes communication data transmitted from terminals and, along with past data breaches, analyzes the user's risk based on these analysis results.

[0511] The terminal is installed on the user's communication device and monitors normal operations such as making calls and sending / receiving messages. The terminal sends data about the user's actions to a server and waits for instructions from the server. Upon receiving instructions from the server, the terminal displays a warning to the user and, if necessary, provides specific countermeasures using guidance mechanisms.

[0512] The emotion engine is used to recognize the user's emotional state during operation. This engine analyzes data such as the user's facial expressions, voice tone, and operation speed to determine their current emotion. The emotion engine's data helps select accurate and appropriately tailored warning content and presentation methods. For example, if the user is feeling anxious, the emotion engine can display more detailed and reassuring guidance.

[0513] Users can follow the instructions on their device and take appropriate action based on guidance from the emotion engine. For example, if a risk is detected in the app when the user is in a hurry, the emotion engine will provide a flexible notification such as, "It's not urgent, but please be careful next time you use it."

[0514] In this way, the present invention aims to enhance the safety and convenience of individual users by providing security measures and enabling optimized responses that respond to the user's emotions.

[0515] The following describes the processing flow.

[0516] Step 1:

[0517] The server collects threat information from reliable sources and regularly updates its database. This ensures that it always maintains the latest threat information.

[0518] Step 2:

[0519] The device monitors the user's calls, messages, and app usage in real time, and records the data for each activity.

[0520] Step 3:

[0521] The terminal transmits the collected data to the server at regular intervals for use in risk analysis. The transmission protocol is lightweight and efficient.

[0522] Step 4:

[0523] The server analyzes the risks by comparing the received user operation data with risk information and past data breach information. AI is used to improve the accuracy of this analysis.

[0524] Step 5:

[0525] The emotion engine collects the user's facial expressions and voice during operation and evaluates their current emotional state. For example, it uses data obtained through the camera and microphone.

[0526] Step 6:

[0527] Based on the analysis results and the evaluation of the sentiment engine, the server generates individually optimized warning messages and suggested countermeasures.

[0528] Step 7:

[0529] The device displays warnings and guidance to the user based on instructions from the server. The displayed content is adjusted according to the user's emotional state.

[0530] Step 8:

[0531] Users should follow the instructions on their device and take necessary measures. For example, this might include deleting specific apps or stopping dangerous communications.

[0532] Step 9:

[0533] The server continuously updates its AI model based on user feedback and newly collected data, improving the accuracy of subsequent analyses.

[0534] (Example 2)

[0535] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0536] In recent years, the risk of personal information leaks and cyberattacks has increased when using communication devices. However, conventional security systems have often failed to provide warnings and guidance that take into account the user's emotional state, causing anxiety and burden. This can deprive users of the opportunity to make appropriate decisions, and there is a need for more flexible and individualized security responses.

[0537] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0538] In this invention, the server includes means for collecting risk information from a reliable external organization, means for monitoring communication data in communication equipment in real time, means for analyzing risks based on past leak information data and risk information collected in real time, means for issuing warnings according to the user's emotional state based on the analyzed risk assessment results, and means for analyzing the emotional state based on the user's actions and providing guidance according to the results. This enables flexible and personalized security responses according to the user's emotional state.

[0539] A "highly reliable external organization" generally refers to a public institution or professional organization that has a high level of credibility in ensuring the authenticity and security of data.

[0540] "Risk information" refers to information related to cybersecurity threats and the risk of personal information leakage, including virus detection information and warnings of unauthorized access.

[0541] "Communication equipment" refers to electronic devices used by users to make voice calls, send messages, access the internet, and perform other similar activities.

[0542] "Communication data" refers to all digital information transmitted and received through communication devices, and includes text messages, voice data, and internet browsing history.

[0543] "Past data breaches" refers to stored data related to past personal information breaches, which are used to assess the risk of similar new breaches.

[0544] "Means of risk analysis" refers to algorithms and processes that use collected data to detect and evaluate potential hazards from that data.

[0545] "Emotional state" refers to the psychological tendencies and emotional responses that a user exhibits during operation, and this is analyzed from data such as facial expressions and voice tone.

[0546] A "warning" refers to a notification or message that informs a user of a potential danger, allowing the user to recognize the risk.

[0547] "Guidance" refers to specific instructions and advice provided to help users take appropriate action.

[0548] The system of this invention is for securely and efficiently managing user communications. Its main components include a server, a terminal, an emotion engine, and the user.

[0549] Server Role

[0550] The server continuously collects the latest risk information from reliable external sources via API communication and stores this data in a database. Based on this information, the server analyzes the data using machine learning algorithms to assess the user's risk. Risk assessment is performed by comparing past data breaches with real-time data. This process makes it possible to generate appropriate warnings for individual users.

[0551] Terminal role

[0552] The terminal is installed on the user's communication device and monitors the user's communication data in real time, sending it to a server. The data is transmitted encrypted, and warnings are displayed to the user in response to instructions from the server. In this display, the terminal provides information using a display or voice assistant.

[0553] The role of the emotional engine

[0554] The emotion engine analyzes the user's facial expressions, voice tone, and operation speed to evaluate the user's emotional state in real time. It collects emotional data using image analysis software and speech recognition technology, and uses this data to adjust appropriate warnings and guidance. If the user is feeling anxious, for example, detailed guidance is provided to reassure them.

[0555] Specific application examples for users

[0556] For example, if a server detects a potential security risk while a user is using public Wi-Fi, the server sends a warning to the device saying, "There is a risk to your current network connection." If the emotion engine detects that the user is feeling anxious, it adds guidance such as, "Please review these steps to ensure your safety."

[0557] Examples of prompts for generative AI models

[0558] "Please suggest guidance for users who receive a security alert while using public Wi-Fi. The guidance should be considerate and designed to help users remain calm and follow the instructions."

[0559] By combining these elements, the system aims to improve user safety and convenience by providing flexible and personalized security responses based on user actions and emotional states.

[0560] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0561] Step 1:

[0562] The server collects risk information from reliable external sources. It receives risk information data obtained from the external source's API as input and stores it in a database. The output is the most recent stored risk information data. This data is then used to prepare the server for risk analysis using machine learning algorithms.

[0563] Step 2:

[0564] The terminal monitors the user's communication data in real time and sends it to the server as needed. It receives data from the user's calls and messages as input and checks for any anomalies. If an anomaly is detected, it encrypts the data and sends it to the server. The output is the address of the destination server and the encrypted data to be sent. This allows the server to receive data for user risk assessment.

[0565] Step 3:

[0566] The server performs a risk assessment based on communication data received from the terminal. The inputs used are encrypted user communication data and risk information and past data breach information stored in the database. This data is analyzed using an algorithm to calculate the risk level. The output is the calculated risk assessment result. Based on this result, the server generates a warning message.

[0567] Step 4:

[0568] The emotion engine analyzes the user's facial expressions, voice tone, and operation speed to evaluate the user's emotional state. It receives user behavior data collected by the device as input. Using image analysis and speech recognition technology, it determines the user's emotional state. The output is information about the evaluated emotional state. Based on this, the emotion engine instructs the server to adjust the warning content.

[0569] Step 5:

[0570] The server sends warnings and guidance generated according to the user's emotional state to the terminal. It receives risk assessment results and emotional state information as input, and determines appropriate warning content based on this. The output is the warning message and guidance sent to the user's terminal. This allows the user to obtain the information necessary to appropriately adjust their behavior.

[0571] Step 6:

[0572] The user selects an action based on the warnings and guidance received from the terminal. The input is the warning messages and guidance displayed on the terminal screen, which the user understands. The output is the action the user chooses, such as whether to continue or disconnect the network connection. The terminal feeds the user's selection back to the server to help with further improvements.

[0573] (Application Example 2)

[0574] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0575] Current communication devices lack sufficient means to ensure the security of personal information, and in particular, they have a challenge in that they cannot respond flexibly to the emotional state of the user. Furthermore, there is a need for mechanisms that ensure appropriate security without causing users unnecessary anxiety.

[0576] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0577] In this invention, the server includes means for collecting risk information from reliable sources, means for monitoring communication information in communication devices in real time, and means for analyzing risks based on past leakage information. This allows for the detection of the user's emotional state and the adjustment of warning content based on that emotion, thereby enhancing the security of personal information and enabling flexible responses that respond to the user's emotions.

[0578] A "highly reliable source of information" is an organization or service whose information is recognized for its accuracy and reliability, and it plays an important role in gathering information on potential risks.

[0579] "Communication information" refers to all data and signals transmitted and received through a user's communication device, and is subject to security monitoring.

[0580] "Past data breaches" refers to data from past data breaches and is used as a comparative standard for analyzing risk.

[0581] "Means of risk analysis" refers to methods and processes for evaluating potential security risks based on collected information and past data breaches.

[0582] "Means of detecting emotional state" refers to technologies and systems that analyze data such as the user's facial expressions, voice, and operation speed to determine their current emotions.

[0583] "Adjusting warning content" refers to the act of flexibly changing the content and format of warnings presented according to the user's emotional state.

[0584] "Flexible response" refers to the ability to take optimized responses and actions according to the situation and conditions.

[0585] The system that realizes this invention consists of a server, a terminal, and an emotion engine. The server collects risk information from reliable sources and updates its database to keep it constantly up-to-date. This makes it possible to assess risk by comparing it with past leaks. The terminal is installed on the user's communication device and monitors communication information in real time. This allows for an assessment of whether the user's actions are safe and, if necessary, receives warning instructions from the server.

[0586] The emotion engine analyzes data such as the user's facial expressions, voice, and operation speed to determine their current emotional state. This emotion data is used to adjust the content of warnings presented according to the user's emotions. For example, if the user is showing anxiety, more detailed and reassuring information will be provided.

[0587] For example, when a user is using a banking app on their smartphone, the server monitors communication information through the device and detects potential security risks. The emotion engine reads the user's voice to indicate anxiety and, if the risk level is low, displays a flexible warning message on the device such as, "Don't worry, the risk is low. Please be careful next time."

[0588] The programs in this system are written in Python and use the emotion_recognition library for emotion recognition. The SecurityServer module is responsible for risk assessment and risk information gathering, and provides appropriate guidance to the user. By utilizing a generative AI model, it is possible to incorporate more human-like elements into the responses. An example of a prompt message is, "Generate a notification message if the user shows anxiety while using the app and the risk level is 3."

[0589] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0590] Step 1:

[0591] The device monitors the user's communication information in real time. The input is communication data from each application the user is running on their smartphone. The output is a report of detected abnormal communication to the server. This process involves analyzing the communication protocol and extracting data that deviates from normal patterns.

[0592] Step 2:

[0593] The server collects threat information from reliable sources and updates the database. The input is the latest threat information obtained from reliable sources. The output is the updated database information. In this step, the latest threat information is obtained using external APIs or data feeds and integrated into the internal database.

[0594] Step 3:

[0595] The server compares communication data reported from terminals with past data breaches to analyze the risk. The inputs are the communication data received from the terminals and existing data breaches. The output is the analyzed risk level. Here, a statistical model is used to evaluate the correlation with past data and calculate the degree of risk.

[0596] Step 4:

[0597] The emotion engine detects the user's emotional state. Inputs include user facial expression data, voice data, and operation speed data. The detected emotional state is sent to the server as output. This process uses the emotion_recognition library to perform emotion recognition by combining image and voice analysis.

[0598] Step 5:

[0599] The server adjusts the warning content based on risk level and sentiment data and sends it to the terminal. The input is the analyzed risk level and detected sentiment state. The output is the adjusted warning message for display to the user. A specific generative AI model is used to generate flexible, sentiment-sensitive responses.

[0600] Step 6:

[0601] The user receives a warning message from their device and takes the necessary action. The input is the warning message displayed on the device. The output is the action taken by the user. In this step, the user can ensure their safety by deciding on actual actions based on the information presented and following the guidance.

[0602] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0603] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0604] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0605] [Fourth Embodiment]

[0606] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0607] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0608] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0609] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0610] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0611] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0612] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0613] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0614] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0615] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0616] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0617] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0618] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0619] This invention relates to a security system for secure communication via communication devices. This system consists of multiple servers, terminals, and users.

[0620] The server continuously collects risk information from reliable sources. This ensures that the latest threat information is reflected in the database and that it is constantly updated. The server also receives communication data transmitted in real time from each terminal and analyzes this data by comparing it with past leaked information data. The server uses AI to perform this analysis and determine the level of risk associated with the user's communication.

[0621] The terminal is installed on the user's communication device and monitors the user's daily operations. Each time communication occurs, the terminal sends information to the server, using a lightweight and efficient protocol to avoid performance degradation. Upon receiving instructions from the server, the terminal displays a warning message to the user and, if necessary, provides guidance suggesting specific corrective actions. This guidance includes actions to take immediately and suggestions for configuration changes.

[0622] Users can take quick and appropriate action based on real-time warnings and guidance from their devices. For example, if an untrusted application is installed, the device will display a warning such as, "This app has caused security risks in the past. We recommend removing it."

[0623] In this way, the present invention provides a comprehensive solution to enhance the security of users' digital environments and proactively prevent risks such as the leakage of personal information and spam communications.

[0624] The following describes the processing flow.

[0625] Step 1:

[0626] The server collects threat information from reliable sources and stores it in a database. This ensures that the system always maintains the most up-to-date threat information.

[0627] Step 2:

[0628] The device monitors user calls, messages, and app usage, and temporarily records data related to each action. The monitoring is designed not to impact user performance.

[0629] Step 3:

[0630] The terminal periodically sends recorded data to the server. This data transfer uses a secure and efficient protocol to prevent delays and excessive bandwidth consumption.

[0631] Step 4:

[0632] The server analyzes the received communication data and compares it with past data breaches and risk information. Using AI, it assesses the data's risk level and generates immediate warnings as needed.

[0633] Step 5:

[0634] The server sends instructions to the terminal based on the analysis results. These instructions include a decision on whether or not to take a specific action.

[0635] Step 6:

[0636] The device displays a warning message to the user, following instructions from the server. The warning includes details of the detected risk and recommended actions.

[0637] Step 7:

[0638] Users choose the necessary action based on the warnings and guidance provided by their device. This may include deleting apps, stopping communication, or changing settings.

[0639] Step 8:

[0640] The server analyzes user behavior and newly collected data to update the AI ​​model, thereby improving the accuracy of future risk assessment and detection.

[0641] (Example 1)

[0642] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0643] Conventional security systems have been insufficient in collecting risk information during communications and analyzing communication data, making it difficult to quickly detect the risk of information leaks and unauthorized access. Furthermore, the lack of means to provide users with specific warnings and countermeasures in a timely manner meant that users missed opportunities to take appropriate action themselves.

[0644] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0645] In this invention, the server includes means for acquiring risk information from a reliable data source, means for monitoring data communication in the information processing device in real time, and means for evaluating risk based on past information leakage data. This makes it possible to quickly and efficiently detect the latest threats and immediately propose specific countermeasures to users.

[0646] A "highly reliable data source" refers to an information provider whose reliability and credibility are guaranteed in order to provide security information and risk information.

[0647] An "information processing device" refers to an electronic device used for communication and data processing.

[0648] "Data communication" refers to the process of sending and receiving information over a network.

[0649] "Information leakage data" refers to records and information related to the unauthorized leakage or disclosure of data that has occurred in the past.

[0650] "Means of risk assessment" refers to methods or processes for determining the extent to which communications or data pose a security risk.

[0651] A "lightweight and efficient communication protocol" refers to a protocol designed to improve communication efficiency and enable rapid data transmission and reception.

[0652] "Means of proposing specific countermeasures" refers to a mechanism that indicates the actions or changes that users should take in response to specific security risks.

[0653] This invention is a security system for secure communication, and is mainly composed of a server, a terminal, and a user.

[0654] The server acquires risk information from reliable data sources and stores it in a database. The database utilizes a cloud-based storage system and is always accessible. The server also employs generative AI models to analyze communication data transmitted from terminals. This allows it to assess communication risks based on past data breaches.

[0655] The terminal is a software application installed on the user's device, responsible for monitoring the user's communications in real time. By using lightweight and efficient communication protocols such as MQTT, the terminal can quickly send data to the server. Furthermore, based on the evaluation results from the server, the terminal provides the user with necessary warnings and specific countermeasures. This process enables the user to take timely and appropriate action.

[0656] Through this system, users can receive real-time warnings and guidance to protect the security of their digital environment. For example, if a suspicious application is installed, the device will warn, "This app has caused security risks in the past. We recommend removing it," allowing users to take immediate action. Furthermore, by using a prompt such as "How can I display a warning when installing an untrusted app?" as an example of a prompt to input into the generating AI model, more specific advice and information can be obtained.

[0657] In this way, the present invention provides an effective means for users to safely utilize the digital environment.

[0658] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0659] Step 1:

[0660] The server acquires threat information from reliable external data sources. It receives threat information periodically via an API as input and stores it in a database in JSON format. As part of data processing, it integrates the received information into an existing data structure to maintain up-to-date threat information.

[0661] Step 2:

[0662] The terminal operates on the user's communication device and monitors communication data in real time. Specifically, it captures network traffic and formats it into the required format. As input, it collects relevant data (e.g., IP address and port number) each time communication occurs and sends it to the server. The output is this communication data, sent using the lightweight MQTT protocol.

[0663] Step 3:

[0664] The server receives communication data sent from the terminal and performs data analysis using a generating AI model. The input is communication data from the terminal, which the AI ​​model analyzes, compares with past data breaches, and calculates a risk score. The output of this analysis is a risk assessment result, and further actions are decided based on this result.

[0665] Step 4:

[0666] The server immediately sends a warning message to the terminal if the risk score exceeds a certain threshold. Specifically, it retrieves the relevant warning message from the database and notifies the terminal using the MQTT protocol. The input is the risk assessment result, and the output is the warning message.

[0667] Step 5:

[0668] The terminal displays a notification to the user based on a warning message received from the server. Specifically, it displays a warning as a pop-up on the user screen via a GUI. The input is a warning message from the server, and the output is a visual warning display to the user. Additional countermeasures are also displayed at this point to suggest appropriate actions to the user.

[0669] Step 6:

[0670] The user receives warnings from the device and chooses appropriate action based on the guidance provided. Specific actions include uninstalling suspicious applications and changing settings. The input is the warnings and guidance from the device, while the output is the actual action taken by the user to mitigate security risks.

[0671] (Application Example 1)

[0672] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0673] Security threats in the digital environment are increasing, and users are required to recognize and act quickly and appropriately on these risks. However, conventional systems are insufficient in providing real-time threat recognition and specific countermeasures guidance. Therefore, there is a need for a method to quickly assess potential communication risks faced by users and provide accurate guidance on action.

[0674] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0675] In this invention, the server includes means for collecting risk information from a reliable source, means for monitoring communication data in a communication device in real time, and means for analyzing risk based on past leaked information data. This allows users to immediately assess the risks associated with communication and receive real-time guidance for taking appropriate action.

[0676] A "highly reliable organization" is a professional organization that guarantees the accuracy and timeliness of its information and provides data on security threats.

[0677] "Means for collecting risk information" refers to methods and devices for efficiently obtaining security-related information provided by reliable organizations.

[0678] A "communication device" is an electronic device that transmits and receives information and is connected to other devices via data communication.

[0679] "Means of monitoring communication data in real time" refers to systems and methods for immediately observing transmitted and received data to determine whether there are any threats or anomalies.

[0680] "Past data breaches" refers to data obtained from past data breaches, which are accumulated records and information used for security analysis.

[0681] "Means of risk analysis" refer to calculation methods and algorithms used to compare communication data with leaked information data and identify potential security risks.

[0682] "Means of issuing warnings to users based on analysis results" refers to methods of informing users of potential hazards based on the results of risk analysis and providing notifications to ensure their safety.

[0683] A "display means for showing recommended actions based on risk assessment" refers to a method or device that visually presents specific action guidelines to the user according to the risk level determined by the analysis.

[0684] "Means of providing real-time guidance on user behavior" refers to a system that provides instructions to prompt appropriate actions immediately based on the user's current actions and circumstances.

[0685] The system for implementing the present invention mainly consists of a server, terminals, and users. The server continuously collects security risk information from reliable sources and maintains the latest threat information by updating its database in real time. The server also immediately monitors communication data transmitted from each terminal and analyzes the risk by comparing it with past leaked information data.

[0686] The terminal is installed on the user's communication device and detects the user's daily communication activities. The terminal forwards incoming and outgoing data packets to the server using a lightweight and efficient protocol. The server receives this data and, through an AI-based risk assessment algorithm, verifies the security of the communication and decides whether or not to send a warning to the user.

[0687] Users can take immediate action against suspicious communications by following warning messages and guidance from their devices. This system enhances security by displaying recommended actions based on risk assessments on the user's device and providing visually clear instructions.

[0688] For example, if a user connects to public Wi-Fi, the system immediately assesses the risk and provides a warning and countermeasures such as, "This network may have a low level of security. Please choose another network or use a VPN."

[0689] By utilizing generative AI models, it is possible to learn patterns in threat intelligence and generate highly accurate warnings. For example, a prompt such as, "Develop an AI model to assess the security risks of newly installed applications. Describe a mechanism that scores the risk level based on past data breach incidents and displays a warning to the user," could be used.

[0690] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0691] Step 1:

[0692] The server regularly collects security risk information from reliable sources. During this process, new security incident information is added to the database via an API, updating the training dataset for the AI ​​model. The input is the latest security risk data obtained from the sources, and the output is the updated database.

[0693] Step 2:

[0694] The terminal monitors communication data in real time using the user's communication device. Here, it captures incoming and outgoing data packets and sends them to the server using a lightweight protocol. The input is the user's real-time communication data, and the output is the transfer of data packets to the server.

[0695] Step 3:

[0696] The server analyzes the received communication data based on a risk assessment algorithm. An AI model compares the communication data with past data breaches to calculate the threat level. The input is the communication data sent from the terminal, and the output is the calculated risk score.

[0697] Step 4:

[0698] The server will issue a warning to the user if necessary, based on the risk score. Specifically, it will generate a warning message based on the result and send it to the terminal. The input is the risk score, and the output is the warning message to the user.

[0699] Step 5:

[0700] The device displays received warning messages to the user and provides appropriate guidance. Here, recommended actions and changes to security settings are communicated via a notification screen. The input is the warning message from the server, and the output is a notification prompting user action.

[0701] Step 6:

[0702] The user selects actions based on warnings through their device and modifies communication device settings as needed. This includes actions such as selecting a new network or removing threatening applications. The input is the notification content from the device, and the output is the security action performed by the user.

[0703] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0704] This invention relates to a system that enhances the security of personal information in communication devices and enables flexible responses based on the user's emotional state. This system mainly consists of a server, a terminal, an emotion engine, and a user.

[0705] The server continuously collects the latest risk information from highly reliable sources. This allows the server to continuously update its database and assess risks with the most reliable information. The server also analyzes communication data transmitted from terminals and, along with past data breaches, analyzes the user's risk based on these analysis results.

[0706] The terminal is installed on the user's communication device and monitors normal operations such as making calls and sending / receiving messages. The terminal sends data about the user's actions to a server and waits for instructions from the server. Upon receiving instructions from the server, the terminal displays a warning to the user and, if necessary, provides specific countermeasures using guidance mechanisms.

[0707] The emotion engine is used to recognize the user's emotional state during operation. This engine analyzes data such as the user's facial expressions, voice tone, and operation speed to determine their current emotion. The emotion engine's data helps select accurate and appropriately tailored warning content and presentation methods. For example, if the user is feeling anxious, the emotion engine can display more detailed and reassuring guidance.

[0708] Users can follow the instructions on their device and take appropriate action based on guidance from the emotion engine. For example, if a risk is detected in the app when the user is in a hurry, the emotion engine will provide a flexible notification such as, "It's not urgent, but please be careful next time you use it."

[0709] In this way, the present invention aims to enhance the safety and convenience of individual users by providing security measures and enabling optimized responses that respond to the user's emotions.

[0710] The following describes the processing flow.

[0711] Step 1:

[0712] The server collects threat information from reliable sources and regularly updates its database. This ensures that it always maintains the latest threat information.

[0713] Step 2:

[0714] The device monitors the user's calls, messages, and app usage in real time, and records the data for each activity.

[0715] Step 3:

[0716] The terminal transmits the collected data to the server at regular intervals for use in risk analysis. The transmission protocol is lightweight and efficient.

[0717] Step 4:

[0718] The server analyzes the risks by comparing the received user operation data with risk information and past data breach information. AI is used to improve the accuracy of this analysis.

[0719] Step 5:

[0720] The emotion engine collects the user's facial expressions and voice during operation and evaluates their current emotional state. For example, it uses data obtained through the camera and microphone.

[0721] Step 6:

[0722] Based on the analysis results and the evaluation of the sentiment engine, the server generates individually optimized warning messages and suggested countermeasures.

[0723] Step 7:

[0724] The device displays warnings and guidance to the user based on instructions from the server. The displayed content is adjusted according to the user's emotional state.

[0725] Step 8:

[0726] Users should follow the instructions on their device and take necessary measures. For example, this might include deleting specific apps or stopping dangerous communications.

[0727] Step 9:

[0728] The server continuously updates its AI model based on user feedback and newly collected data, improving the accuracy of subsequent analyses.

[0729] (Example 2)

[0730] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0731] In recent years, the risk of personal information leaks and cyberattacks has increased when using communication devices. However, conventional security systems have often failed to provide warnings and guidance that take into account the user's emotional state, causing anxiety and burden. This can deprive users of the opportunity to make appropriate decisions, and there is a need for more flexible and individualized security responses.

[0732] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0733] In this invention, the server includes means for collecting risk information from a reliable external organization, means for monitoring communication data in communication equipment in real time, means for analyzing risks based on past leak information data and risk information collected in real time, means for issuing warnings according to the user's emotional state based on the analyzed risk assessment results, and means for analyzing the emotional state based on the user's actions and providing guidance according to the results. This enables flexible and personalized security responses according to the user's emotional state.

[0734] A "highly reliable external organization" generally refers to a public institution or professional organization that has a high level of credibility in ensuring the authenticity and security of data.

[0735] "Risk information" refers to information related to cybersecurity threats and the risk of personal information leakage, including virus detection information and warnings of unauthorized access.

[0736] "Communication equipment" refers to electronic devices used by users to make voice calls, send messages, access the internet, and perform other similar activities.

[0737] "Communication data" refers to all digital information transmitted and received through communication devices, and includes text messages, voice data, and internet browsing history.

[0738] "Past data breaches" refers to stored data related to past personal information breaches, which are used to assess the risk of similar new breaches.

[0739] "Means of risk analysis" refers to algorithms and processes that use collected data to detect and evaluate potential hazards from that data.

[0740] "Emotional state" refers to the psychological tendencies and emotional responses that a user exhibits during operation, and this is analyzed from data such as facial expressions and voice tone.

[0741] A "warning" refers to a notification or message that informs a user of a potential danger, allowing the user to recognize the risk.

[0742] "Guidance" refers to specific instructions and advice provided to help users take appropriate action.

[0743] The system of this invention is for securely and efficiently managing user communications. Its main components include a server, a terminal, an emotion engine, and the user.

[0744] Server Role

[0745] The server continuously collects the latest risk information from reliable external sources via API communication and stores this data in a database. Based on this information, the server analyzes the data using machine learning algorithms to assess the user's risk. Risk assessment is performed by comparing past data breaches with real-time data. This process makes it possible to generate appropriate warnings for individual users.

[0746] Terminal role

[0747] The terminal is installed on the user's communication device and monitors the user's communication data in real time, sending it to a server. The data is transmitted encrypted, and warnings are displayed to the user in response to instructions from the server. In this display, the terminal provides information using a display or voice assistant.

[0748] The role of the emotional engine

[0749] The emotion engine analyzes the user's facial expressions, voice tone, and operation speed to evaluate the user's emotional state in real time. It collects emotional data using image analysis software and speech recognition technology, and uses this data to adjust appropriate warnings and guidance. If the user is feeling anxious, for example, detailed guidance is provided to reassure them.

[0750] Specific application examples for users

[0751] For example, if a server detects a potential security risk while a user is using public Wi-Fi, the server sends a warning to the device saying, "There is a risk to your current network connection." If the emotion engine detects that the user is feeling anxious, it adds guidance such as, "Please review these steps to ensure your safety."

[0752] Examples of prompts for generative AI models

[0753] "Please suggest guidance for users who receive a security alert while using public Wi-Fi. The guidance should be considerate and designed to help users remain calm and follow the instructions."

[0754] By combining these elements, the system aims to improve user safety and convenience by providing flexible and personalized security responses based on user actions and emotional states.

[0755] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0756] Step 1:

[0757] The server collects risk information from reliable external sources. It receives risk information data obtained from the external source's API as input and stores it in a database. The output is the most recent stored risk information data. This data is then used to prepare the server for risk analysis using machine learning algorithms.

[0758] Step 2:

[0759] The terminal monitors the user's communication data in real time and sends it to the server as needed. It receives data from the user's calls and messages as input and checks for any anomalies. If an anomaly is detected, it encrypts the data and sends it to the server. The output is the address of the destination server and the encrypted data to be sent. This allows the server to receive data for user risk assessment.

[0760] Step 3:

[0761] The server performs a risk assessment based on communication data received from the terminal. The inputs used are encrypted user communication data and risk information and past data breach information stored in the database. This data is analyzed using an algorithm to calculate the risk level. The output is the calculated risk assessment result. Based on this result, the server generates a warning message.

[0762] Step 4:

[0763] The emotion engine analyzes the user's facial expressions, voice tone, and operation speed to evaluate the user's emotional state. It receives user behavior data collected by the device as input. Using image analysis and speech recognition technology, it determines the user's emotional state. The output is information about the evaluated emotional state. Based on this, the emotion engine instructs the server to adjust the warning content.

[0764] Step 5:

[0765] The server sends warnings and guidance generated according to the user's emotional state to the terminal. It receives risk assessment results and emotional state information as input, and determines appropriate warning content based on this. The output is the warning message and guidance sent to the user's terminal. This allows the user to obtain the information necessary to appropriately adjust their behavior.

[0766] Step 6:

[0767] The user selects an action based on the warnings and guidance received from the terminal. The input is the warning messages and guidance displayed on the terminal screen, which the user understands. The output is the action the user chooses, such as whether to continue or disconnect the network connection. The terminal feeds the user's selection back to the server to help with further improvements.

[0768] (Application Example 2)

[0769] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0770] Current communication devices lack sufficient means to ensure the security of personal information, and in particular, they have a challenge in that they cannot respond flexibly to the emotional state of the user. Furthermore, there is a need for mechanisms that ensure appropriate security without causing users unnecessary anxiety.

[0771] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0772] In this invention, the server includes means for collecting risk information from reliable sources, means for monitoring communication information in communication devices in real time, and means for analyzing risks based on past leakage information. This allows for the detection of the user's emotional state and the adjustment of warning content based on that emotion, thereby enhancing the security of personal information and enabling flexible responses that respond to the user's emotions.

[0773] A "highly reliable source of information" is an organization or service whose information is recognized for its accuracy and reliability, and it plays an important role in gathering information on potential risks.

[0774] "Communication information" refers to all data and signals transmitted and received through a user's communication device, and is subject to security monitoring.

[0775] "Past data breaches" refers to data from past data breaches and is used as a comparative standard for analyzing risk.

[0776] "Means of risk analysis" refers to methods and processes for evaluating potential security risks based on collected information and past data breaches.

[0777] "Means of detecting emotional state" refers to technologies and systems that analyze data such as the user's facial expressions, voice, and operation speed to determine their current emotions.

[0778] "Adjusting warning content" refers to the act of flexibly changing the content and format of warnings presented according to the user's emotional state.

[0779] "Flexible response" refers to the ability to take optimized responses and actions according to the situation and conditions.

[0780] The system that realizes this invention consists of a server, a terminal, and an emotion engine. The server collects risk information from reliable sources and updates its database to keep it constantly up-to-date. This makes it possible to assess risk by comparing it with past leaks. The terminal is installed on the user's communication device and monitors communication information in real time. This allows for an assessment of whether the user's actions are safe and, if necessary, receives warning instructions from the server.

[0781] The emotion engine analyzes data such as the user's facial expressions, voice, and operation speed to determine their current emotional state. This emotion data is used to adjust the content of warnings presented according to the user's emotions. For example, if the user is showing anxiety, more detailed and reassuring information will be provided.

[0782] For example, when a user is using a banking app on their smartphone, the server monitors communication information through the device and detects potential security risks. The emotion engine reads the user's voice to indicate anxiety and, if the risk level is low, displays a flexible warning message on the device such as, "Don't worry, the risk is low. Please be careful next time."

[0783] The programs in this system are written in Python and use the emotion_recognition library for emotion recognition. The SecurityServer module is responsible for risk assessment and risk information gathering, and provides appropriate guidance to the user. By utilizing a generative AI model, it is possible to incorporate more human-like elements into the responses. An example of a prompt message is, "Generate a notification message if the user shows anxiety while using the app and the risk level is 3."

[0784] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0785] Step 1:

[0786] The device monitors the user's communication information in real time. The input is communication data from each application the user is running on their smartphone. The output is a report of detected abnormal communication to the server. This process involves analyzing the communication protocol and extracting data that deviates from normal patterns.

[0787] Step 2:

[0788] The server collects threat information from reliable sources and updates the database. The input is the latest threat information obtained from reliable sources. The output is the updated database information. In this step, the latest threat information is obtained using external APIs or data feeds and integrated into the internal database.

[0789] Step 3:

[0790] The server compares communication data reported from terminals with past data breaches to analyze the risk. The inputs are the communication data received from the terminals and existing data breaches. The output is the analyzed risk level. Here, a statistical model is used to evaluate the correlation with past data and calculate the degree of risk.

[0791] Step 4:

[0792] The emotion engine detects the user's emotional state. Inputs include user facial expression data, voice data, and operation speed data. The detected emotional state is sent to the server as output. This process uses the emotion_recognition library to perform emotion recognition by combining image and voice analysis.

[0793] Step 5:

[0794] The server adjusts the warning content based on risk level and sentiment data and sends it to the terminal. The input is the analyzed risk level and detected sentiment state. The output is the adjusted warning message for display to the user. A specific generative AI model is used to generate flexible, sentiment-sensitive responses.

[0795] Step 6:

[0796] The user receives a warning message from their device and takes the necessary action. The input is the warning message displayed on the device. The output is the action taken by the user. In this step, the user can ensure their safety by deciding on actual actions based on the information presented and following the guidance.

[0797] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0798] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0799] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0800] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0801] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0802] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0803] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0804] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0805] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0806] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0807] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0808] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0809] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0810] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0811] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0812] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0813] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0814] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0815] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0816] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0817] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0818] The following is further disclosed regarding the embodiments described above.

[0819] (Claim 1)

[0820] Means of collecting risk information from reliable sources,

[0821] A means for monitoring communication data in a communication device in real time,

[0822] A means of analyzing risk based on past leaked information data,

[0823] A means of issuing a warning to the user based on the analysis results,

[0824] A system that includes this.

[0825] (Claim 2)

[0826] The system according to claim 1, comprising means for continuously updating hazard information and improving the accuracy of the system's analysis.

[0827] (Claim 3)

[0828] The system according to claim 1, comprising guidance means for presenting recommended actions based on user actions.

[0829] "Example 1"

[0830] (Claim 1)

[0831] Means of obtaining risk information from reliable data sources,

[0832] A means for monitoring data communication in an information processing device in real time,

[0833] A means of assessing risk based on past data breaches,

[0834] A means of notifying users of warnings based on evaluation results,

[0835] A means of using lightweight and efficient communication protocols,

[0836] A means of proposing specific countermeasures in response to user actions,

[0837] A system that includes this.

[0838] (Claim 2)

[0839] The system according to claim 1, comprising means for continuously updating hazard information and improving the system's risk assessment capability.

[0840] (Claim 3)

[0841] The system according to claim 1, comprising guidance means for presenting recommended protective measures based on user behavior.

[0842] "Application Example 1"

[0843] (Claim 1)

[0844] Means of collecting risk information from reliable sources,

[0845] A means for monitoring communication data in a communication device in real time,

[0846] A means of analyzing risk based on past leaked information data,

[0847] A means of issuing a warning to the user based on the analysis results,

[0848] A display means that shows recommended actions based on risk assessment,

[0849] A system that includes this.

[0850] (Claim 2)

[0851] The system according to claim 1, comprising means for continuously updating hazard information and improving the accuracy of the system's analysis.

[0852] (Claim 3)

[0853] The system according to claim 1, comprising means for providing real-time guidance on user behavior.

[0854] "Example 2 of combining an emotion engine"

[0855] (Claim 1)

[0856] Means of collecting risk information from reliable external organizations,

[0857] A means of monitoring communication data in communication equipment in real time,

[0858] A means of analyzing risk based on past leaked information data and risk information collected in real time,

[0859] Based on the analyzed risk assessment results, a means of issuing warnings tailored to the user's emotional state,

[0860] A means for analyzing the emotional state based on user actions and providing guidance according to the results,

[0861] A system that includes this.

[0862] (Claim 2)

[0863] The system according to claim 1, comprising means for continuously updating risk information, improving the accuracy of system analysis, and adjusting warning content based on the user's emotional state.

[0864] (Claim 3)

[0865] The system according to claim 1, comprising guidance means for flexibly suggesting countermeasures based on user actions and analyzed emotional states.

[0866] "Application example 2 when combining with an emotional engine"

[0867] (Claim 1)

[0868] Means of collecting risk information from reliable sources,

[0869] A means for monitoring communication information in a communication device in real time,

[0870] A means of analyzing risks based on past leaked information,

[0871] A means of issuing warnings to users based on the analysis results,

[0872] A means for detecting the user's emotional state and adjusting the warning content based on that emotion,

[0873] A system that includes this.

[0874] (Claim 2)

[0875] The system according to claim 1, comprising means for continuously updating hazard information and improving the accuracy of the system's analysis.

[0876] (Claim 3)

[0877] The system according to claim 1, which includes a guidance means that presents recommended measures based on the user's behavior, enabling flexible responses according to the user's emotional state. [Explanation of Symbols]

[0878] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Means of collecting risk information from reliable sources, A means for monitoring communication data in a communication device in real time, A means of analyzing risk based on past leaked information data, A means of issuing a warning to the user based on the analysis results, A display means that shows recommended actions based on risk assessment, A system that includes this.

2. The system according to claim 1, comprising means for continuously updating hazard information and improving the accuracy of the system's analysis.

3. The system according to claim 1, comprising means for providing real-time guidance on user behavior.

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