Telephone fraud protection system

Abstract

The invention relates to a telephone fraud protection system, which is a system based on artificial intelligence and aims to prevent telephone fraud communication. When the user cannot answer the call or the caller is not identified, the system can automatically answer the call, and verifies the identity of the caller through real-time conversation by using natural language processing and semantic analysis. The system dynamically analyzes the conversation content to detect potential fraud or phishing activities and classifies the conversation into risk categories such as secure, suspicious, or dangerous. Based on this classification, the system performs appropriate operations, such as providing dialog abstracts, recording suspicious calls for further analysis, or terminating and blocking dangerous calls, while reporting events to a management mechanism. Moreover, the system can also be integrated into external services, such as calendar and message platforms, to automatically schedule events and efficiently manage communications. And the user can monitor the conversation in real time and intervene when necessary, so that the safety and the control right of conversation interaction are ensured.

Description

Technical Field

[0001] This invention relates to telecommunications and security technologies, and more specifically, to telephone fraud prevention systems, systems and methods for preventing telephone fraud using artificial intelligence (AI) and machine learning technologies. Background Technology

[0002] With the widespread adoption of telecommunications technology, the number of telephone interactions has increased significantly, encompassing both personal and business communications. However, this growth has also been accompanied by an increase in fraudulent activities, such as phishing, caller ID spoofing, and other deceptive tactics designed to manipulate individuals or organizations for illegal profit.

[0003] Traditional call handling systems (including caller ID and call blocking services) primarily rely on existing databases of known fraudulent numbers or patterns to identify and reduce unwanted or malicious calls. These systems typically filter calls based on predetermined criteria and do not engage in real-time analysis or verification of the caller's intent. Therefore, they often fail to detect sophisticated or novel scams that do not conform to known signatures or patterns.

[0004] Telephone fraud continues to pose a significant risk to individuals and organizations, resulting in financial losses, breaches of personal information, and erosion of public trust in telecommunications services. While existing solutions are helpful, they are insufficient to address the complexity and evolving nature of modern fraud tactics. There is a clear need for a smart, proactive, and integrated approach to preventing telecommunications fraud, providing comprehensive protection against a wide range of fraudulent activities. Summary of the Invention

[0005] This invention provides a telephone fraud prevention system, utilizing advanced artificial intelligence technology to prevent telephone fraud. The system includes several key components, including a communication interface, an artificial intelligence module, an audio output interface, a user intervention interface, a data storage component, and an integration module.

[0006] The communication interface is configured to receive and transmit telephone calls. When an incoming call is detected, if the user is unable to answer or the caller is not identified, the AI ​​module will automatically answer the call on the user's behalf. This AI module uses natural language processing and semantic analysis to engage in real-time dialogue with the caller to verify the caller's identity and assess the legitimacy of the call.

[0007] During the conversation, the AI ​​module analyzes the content in real time, detecting potential scams by identifying suspicious keywords or patterns related to fraud. Calls are categorized into at least three risk levels: safe, suspicious, and dangerous. For calls classified as dangerous, the system automatically terminates the call, blocks the caller's number, and reports the incident to the relevant authorities.

[0008] The audio output interface allows users to monitor ongoing conversations in real time. The user intervention interface provides users with the ability to intervene and control the call, allowing them to take over the call if necessary. The data storage component securely stores conversation summaries, categorized data, and records of suspicious or dangerous calls, and ensures user privacy through encryption.

[0009] The integration module extracts relevant information from conversations and integrates it into external services, including calendars and messaging platforms. This feature allows for the automatic scheduling of events in a user's calendar based on information extracted from conversations, thereby improving user convenience and organizational efficiency.

[0010] In some embodiments, such as when making calls using VoIP or messaging apps like LINE, the AI ​​module performs real-time phishing assessments on any URLs or websites mentioned by the caller, comparing them against known blacklists. The AI ​​module can also use image recognition and optical character recognition (OCR) technologies to analyze visual content provided by the caller. The AI ​​module continuously updates its fraud detection algorithm based on past interaction data and external threat intelligence sources, and adjusts its operating parameters based on user feedback and detected patterns to improve the accuracy of fraud detection. Multi-language support for dialogue and analysis enhances the system's applicability to different regions and user groups.

[0011] Methods for preventing telephone fraud include similar steps performed by various components of the system. These steps include receiving incoming calls, automatically answering calls, conducting real-time conversations to verify the caller's identity, analyzing potential fraudulent activities in the conversation, classifying call risks, and taking appropriate action based on the classification. The method also encompasses allowing users to monitor and intervene, securely storing relevant data, and integrating extracted information into external services.

[0012] Overall, this invention provides a proactive and adaptive solution to prevent telephone fraud by combining real-time AI-driven call processing, advanced fraud detection technology, user interaction features, and tight integration with external services, while ensuring strong security and user privacy protection.

[0013] To make the above features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0014] Various embodiments will now be described with reference to the accompanying drawings, which are illustrative and not intended to limit the scope in any way, wherein similar reference numerals denote similar components, and the figures are simply explained below: Figure 1 The diagram shown is a block diagram of one embodiment of the telephone fraud prevention system of the present invention.

[0015] Figure 2 The diagram shown is a block diagram of another embodiment of the telephone fraud prevention system of the present invention.

[0016] Figure 3 This demonstrates how the telephone fraud prevention system handles secure incoming calls.

[0017] Figure 4 The demonstration showed how the telephone fraud prevention system handles suspicious incoming calls.

[0018] Figure 5 The demonstration showed how the telephone fraud prevention system handles dangerous incoming calls.

[0019] Figure 6 The diagram shows the operation flow of the telephone fraud prevention system in a personal use scenario.

[0020] Figure 7 The diagram shows the operation flow of the telephone fraud prevention system in a personal use scenario. Detailed Implementation

[0021] This invention relates to a telephone fraud prevention system and method. It is an advanced system and method designed using artificial intelligence and machine learning technologies to prevent fraudulent telephone communications. The telephone fraud prevention system can be tightly integrated into existing telecommunications infrastructure, providing real-time call processing, fraud detection, and user interaction functions. This system is specifically designed to defend against various fraudulent activities, including phishing, caller ID spoofing, and social engineering attacks, thereby enhancing security at both the individual and enterprise levels.

[0022] Please refer to Figure 1 , Figure 1 The diagram illustrates a block diagram of one embodiment of the telephone fraud prevention system of the present invention. The telephone fraud prevention system 100 includes multiple interconnected modules and components that work together to provide comprehensive fraud prevention capabilities. Key components include a communication interface 110, an artificial intelligence module (hereinafter referred to as AI module 120), an audio output interface 130, a data storage component 140, an integration module 150, and a user intervention interface 160.

[0023] Communication interface 110 is responsible for receiving and transmitting telephone calls, enabling the telephone fraud prevention system 100 to interact with callers 10 and users. AI module 120 handles call interaction, fraud detection, and decision-making processes. Audio output interface 130 allows users to monitor ongoing conversations via hands-free devices, providing real-time interactive awareness. Data storage component 140 securely stores conversation summaries, classification data, and records of suspicious or dangerous calls. Integration module 150 connects the telephone fraud prevention system 100 to external services 20 (such as calendars and messaging platforms) for automatic data synchronization. Finally, user intervention interface 160 provides users with the ability to override AI module 120's actions or directly participate in conversations when necessary. This telephone fraud prevention system 100 can operate as a standalone solution or be integrated into existing telecommunications systems in personal devices or enterprise environments.

[0024] The core function of the telephone fraud prevention system 100 is its AI-based call handling capability, which automates the management of incoming calls. First, when an incoming call is detected, the communication interface 110 establishes a connection with the caller 10. If the user is unable to answer (e.g., while driving, attending a meeting, or the caller 10 is not identified), the AI ​​module 120 automatically answers the call on behalf of the user. During the call, the user can listen to the conversation in real time through the audio output interface 130 (typically a hands-free device). This dual-channel communication ensures the user remains informed about the interaction and provides flexibility to intervene or take over the call if necessary. The AI ​​module 120 uses natural language processing to engage in meaningful dialogue with the caller 10, aiming to verify the caller's identity and assess the legitimacy of the call.

[0025] The Telephone Fraud Prevention System 100 employs an advanced call analysis and classification method to assess incoming calls based on risk level. The AI ​​module 120 analyzes conversation content in real time, using semantic analysis and keyword detection to identify potential fraud or phishing activities. The Telephone Fraud Prevention System 100 categorizes each incoming call into one of three risk categories: safe, suspicious, or dangerous.

[0026] Calls falling under the security category are identified as legitimate communications from trusted institutions or routine reminders. These calls undergo real-time authentication to ensure the authenticity of the caller 10. Upon successful authentication, the AI ​​module 120 generates a brief conversation summary, stores relevant information, and can automatically schedule events related to the call in the user's calendar via the integration module 150. Please also refer to... Figure 3 , Figure 3The demonstration showcased how the phone fraud prevention system handles incoming calls. The main interface on the smartphone 50's screen displayed an incoming call from "Taipei Veterans General Hospital." Below the caller ID, there was an icon labeled "AI Secretary" (representing AI module 120), indicating that if the user did not manually swipe to answer, AI module 120 would automatically handle the call. Figure 3 The right side shows that the AI ​​module 120 automatically answers the call after a three-second delay (step S310) and begins a conversation driven by the AI ​​module 120 (step S320). Figure 3 An icon of a hospital nurse was displayed, demonstrating the AI ​​module 120's ability to interact with a real person (i.e., a hospital nurse), especially in a medical setting. After the call ends, the phone fraud prevention system 100 condenses the conversation into a text summary (message summarization, step S330), and automatically adds relevant events to the user's calendar using intelligent scheduling (step S340) (step S350), sets reminders (set alarm, step S360), and manages unread messages (unread messages, step S370) or stores important information. Furthermore, Figure 3 Additional features shown include the ability of the telephone fraud prevention system 100 to adjust the call listening mode according to the situation in environments where it is inconvenient to answer the call (speaker listening, step S380) or in a meeting environment (silent answering, step S390).

[0027] exist Figure 3 In this system, the telephone fraud prevention system 100 uses a traffic light classification system to categorize incoming calls. A green light (safe) indicates a safe call from a trusted entity, such as regulatory agencies, educational institutions, medical institutions, financial institutions, non-profit organizations, technology companies, news media, social networking sites, software and application vendors, trusted e-commerce platforms, travel and transportation services, and professional associations. These entities can be recorded in a whitelist 142 of the data storage component 140, allowing the telephone fraud prevention system 100 to quickly identify trusted entities. Furthermore, the category of "registered and verified organizations" is part of a collaborative effort with regulatory agencies to enhance call screening and fraud prevention.

[0028] Additionally, calls falling into the suspicious category that display inconsistent or unverifiable information will be flagged for further review. These interactions will be logged and stored for subsequent analysis, allowing for manual review or additional verification steps to determine the legitimacy of the call. Please also refer to... Figure 4 , Figure 4 This demonstrates how a telephone fraud prevention system manages suspicious incoming calls. The screen of smartphone 50 displays a call from an unknown number, 0912-345-678 (illustrated only, not a real phone number), which is not recorded in the whitelist 142 or blacklist 144 of the data storage component 140. Figure 3 The standard operation is similar; if the user does not manually swipe to answer, the AI ​​module 120 will automatically answer the call after three seconds (step S410). After answering, the AI ​​module 120 will begin a conversation with the unknown caller, attempting to identify and verify the caller's identity (step S420). In this scenario, the phone fraud prevention system 100 marks the caller as unknown because it cannot immediately verify their identity. The AI ​​module 120 will analyze the conversation and mark potential risks or anomalies (step S430). If it still cannot confirm, it will classify the call as yellow (representing "suspicious"). In addition, the phone fraud prevention system 100 may call back to confirm (step S440) to further verify the caller's identity.

[0029] After the call ends, the telephone fraud prevention system will transcribe the conversation into a text summary. Figure 4 If the message is displayed as "Organizing Messages" (step S450), and the user does not listen to the call immediately, the message will be stored in the unread messages (step S460). For example, the text summary may include details about the Uber driver, informing the user that Mr. Wang will be ten minutes late (Uber driver Mr. Wang will be ten minutes late due to traffic).

[0030] exist Figure 4 In this system, the Telephone Fraud Prevention System 100 uses a yellow light to indicate potentially suspicious calls, which may originate from sources such as extremist websites, dating platforms, extreme sports websites, dangerous challenge websites, or newly registered domains. The Telephone Fraud Prevention System 100 uses an AI module 120 to detect and categorize unsafe calls, and, if necessary, upgrades them for further review or action by the user.

[0031] Additionally, calls categorized as dangerous are detected by identifying sensitive keywords or malicious patterns indicating fraudulent intent, revealing scam or phishing content. AI module 120 automatically terminates these calls to prevent potential harm. Furthermore, the telephone fraud prevention system 100 blocks the caller's number 10 and reports the incident to the management agency 30 via integration module 150 to strengthen overall fraud prevention measures. This classification system allows the telephone fraud prevention system 100 to dynamically adjust its response and actions based on assessed risk, providing a flexible and adaptive approach to fraud prevention. Please refer to... Figure 5 , Figure 5This demonstrates how the telephone fraud prevention system manages dangerous calls, focusing on the classification and response mechanism of the telephone fraud prevention system 100 for high-risk calls. A smartphone screen displays an incoming call labeled "Financial Fraud Call," with the phone number 0912-345-678 (illustrated, not a real phone number). In one scenario, similar to other call types mentioned above, if the user does not manually swipe to answer, the AI ​​module 120 will automatically answer the call after three seconds (as shown in step S510). After answering, the AI ​​module 120 will engage in a conversation with the caller, analyzing the content to detect potential fraudulent activities (as shown in step S540). In this scenario, the call is identified as a red light (representing dangerous or high-risk content) based on the analysis of the conversation content. Alternatively, as shown in step S530, the telephone fraud prevention system 100 has an automatic call-hanging function; when the call is determined to be high-risk, it will immediately terminate the call.

[0032] exist Figure 5 In this system, the telephone fraud prevention system 100 uses a red light to indicate calls classified as dangerous. These calls may come from phishing and fraudulent websites, fake news websites, fake information websites, illegal content websites, websites spreading hacking techniques, copyright infringement websites, intellectual property infringement websites, fraudulent websites, online gambling websites, spam and advertising websites, websites promoting drug use, websites that have been reported extensively, and websites that the AI ​​module 120 determines the caller comes from containing high-risk content. These websites can be recorded in the blacklist 144 of the data storage component 140, so that the telephone fraud prevention system 100 can quickly identify which websites are dangerous.

[0033] After the call ends, the AI ​​module 120 analyzes the conversation and organizes the content into a text summary (as shown in step S550) to inform the user that the call has been flagged as dangerous. If the user does not listen to the call immediately, the message will be stored in the data storage component 140 and marked as unread. The background information in the text summary may include "This is not a Fubon Bank call," "Multiple reports indicate this is a scam call," and "High-risk investment scam." Furthermore, if the AI ​​module 120 detects obvious fraudulent activity, it can also cause the phone fraud prevention system 100 to automatically hang up the call or block future interactions with the number, thereby protecting the user from potential harm.

[0034] The following section will provide a more in-depth introduction to AI Module 120. Please continue reading. Figure 1In this embodiment, the AI ​​module 120 utilizes technologies such as natural language processing, semantic analysis, image recognition, and optical character recognition to interpret and understand the dialogue content. The AI ​​module 120 can engage in meaningful conversations with the caller 10, verifying the caller's identity and intent by asking relevant questions. Through natural language processing and semantic analysis, the AI ​​module 120 can discern the context and nuances of the dialogue, thereby detecting irregular or suspicious patterns that may indicate fraudulent intent. Furthermore, by analyzing fraud-related keywords and interaction methods, such as mentions of "money," "bank account," or requests for urgently needed personal information, the AI ​​module 120 can identify potential threats. The telephone fraud prevention system 100 continuously updates the fraud detection algorithm of the AI ​​module 120 based on new data and emerging fraud methods, ensuring its adaptability and ability to respond to evolving deception techniques.

[0035] During the conversation, if caller 10 mentions any URLs or websites, AI module 120 checks these references and compares them against a known blacklist 144. It can also perform real-time phishing assessments to evaluate the legitimacy of the mentioned online resources. This proactive verification prevents users from unintentionally accessing malicious websites that could compromise their security. Unlike traditional caller ID or call blocking services that rely solely on existing databases and static data, the phone fraud prevention system 100 actively participates in the conversation to verify the legitimacy of caller 10. This real-time, interactive approach provides a more robust and dynamic fraud detection mechanism, capable of identifying sophisticated and novel fraud attempts that may bypass traditional filtering methods.

[0036] The Telephone Fraud Prevention System 100 enhances user convenience and organizational efficiency through its text summaries and integration with external services 20, such as calendars and messaging platforms. After a call ends, the system generates a concise text summary, eliminating the need for users to listen to lengthy recordings. These summaries include key details discussed during the call, allowing users to quickly review and reference important information. Furthermore, the AI ​​module 120 intelligently extracts relevant data from the conversation, such as appointment times, dates, and other actionable items. Once the relevant information is extracted, the system automatically creates corresponding events in the user's calendar or sends notifications via messaging services. This automation reduces the need for manual data entry, improves organizational efficiency, and lowers the risk of oversight. Users can configure the integration module 150 to prioritize specific types of data or specify preferred external services, ensuring the system can be tailored to individual or organizational needs. In this way, the system ensures that important events are recorded promptly and accurately, reducing the risk of omissions and improving overall productivity.

[0037] The integration module 150 is designed for versatility, supporting APIs for various calendar and messaging services, including but not limited to Google Calendar and Microsoft Outlook. Alternatively, the integration module 150 can also set a built-in alarm on a user's smartphone as a reminder. This broad compatibility ensures that the phone fraud prevention system 100 can be seamlessly integrated into different user environments, whether for individuals or organizations.

[0038] Security and privacy protection are fundamental elements in the design of the telephone fraud prevention system 100. This system employs multi-layered protection mechanisms to safeguard sensitive information and ensure user privacy. The AI ​​module 120 continuously improves its fraud detection capabilities by learning from past interactions and user feedback. This adaptive learning process enables the system to identify and combat new fraud tactics, maintaining a high level of threat detection and mitigation effectiveness.

[0039] During call analysis and storage, all processed sensitive information is protected by strong encryption protocols. Data storage component 140 ensures that conversation summaries, categorized data, and records of suspicious or dangerous calls are securely stored, preventing unauthorized access and data leakage. The telephone fraud prevention system 100 complies with relevant data protection regulations, ensuring that user data receives the highest level of care and confidentiality. By preventing unauthorized access to sensitive information and systematically reporting suspicious numbers to the backend, the telephone fraud prevention system 100 maintains strict privacy standards.

[0040] Furthermore, users can control their interaction with the telephone fraud prevention system 100 through the user intervention interface 160. This user intervention interface 160 allows users to oversee the AI's actions or directly participate in the conversation, providing transparency and fostering trust in the operation of the telephone fraud prevention system 100. The user intervention interface 160 allows users to monitor ongoing conversations in real time via a hands-free device, enabling them to intervene or directly control the call when necessary. This feature ensures that users are not entirely dependent on the AI ​​module 120, providing additional security and adaptability.

[0041] For example, if a user detects that the caller 10 is not suspicious in a call categorized as "suspicious" or "dangerous," they can choose to override the AI ​​module 120's decision to terminate the call, further interact with the caller 10, or take alternative actions based on their own judgment. This interactive capability enhances user trust and allows for personalized handling of complex or ambiguous call scenarios.

[0042] The fraud detection effectiveness of the telephone fraud prevention system 100 is maintained through a robust learning and updating mechanism. The AI ​​module 120 integrates machine learning algorithms, analyzing data from past interactions and user feedback to continuously improve its performance. This mechanism involves several key processes. First, the system systematically collects and analyzes user interactions and feedback to identify areas for improvement. For example, if a user marks a call as fraudulent, even if the AI ​​module 120 did not previously classify it that way, it will learn from the feedback and adjust its detection parameters accordingly. Second, the telephone fraud prevention system 100 is designed to integrate with external threat intelligence sources 40, allowing it to access the latest fraud tactics information and integrate this data into its detection algorithms, enhancing the AI ​​module 120's ability to identify and effectively respond to new threats. Furthermore, the AI ​​module 120 continuously trains its machine learning model, improving based on the latest data and detection patterns. This continuous optimization ensures the system can effectively cope with evolving fraud strategies, maintaining high accuracy in call classification and fraud detection. The Telephone Fraud Prevention System 100 analyzes patterns and adjusts its operating parameters to adapt to new environments and user behaviors, ensuring its effectiveness in diverse user environments and changing threat scenarios.

[0043] In addition, please refer to Figure 2 , Figure 2 The diagram illustrates a block diagram of one embodiment of the telephone fraud prevention system of the present invention. To enhance the capabilities of the AI ​​module 120, in one embodiment, the telephone fraud prevention system 100 also integrates a large language model 60 provided by a third-party AI company, such as OpenAI's GPT. This integration enables the telephone fraud prevention system 100 to utilize state-of-the-art natural language processing and understanding capabilities within the large language model. By incorporating the large language model 60 provided by a third-party AI company, the telephone fraud prevention system 100 can benefit from the continuous advancements and updates offered by AI service providers, ensuring access to the latest developments in the field of language understanding and generation.

[0044] Furthermore, to better adapt the large language model 60 provided by the third-party AI company to the specific needs of telephone fraud prevention, the telephone fraud prevention system 100 employs customized techniques including Retrieval-Augmented Generation (RAG) and fine-tuning. RAG enhances the AI ​​module 120's ability to retrieve relevant information from a vast knowledge base during conversations, thereby improving its context awareness and response accuracy. This technology ensures that the AI ​​can reference the latest and most relevant information when interacting with callers, contributing to more effective fraud detection and prevention. Fine-tuning involves adjusting the parameters of the large language model 60 using domain data related to fraudulent activities, phishing patterns, and other deceptive tactics. By training the large language model 60 on a specialized dataset, the telephone fraud prevention system 100 can improve the model's understanding and identification of subtle fraud indicators, thereby enhancing its ability to accurately classify and respond to various types of fraudulent calls. This customization process ensures that the AI ​​module 120 remains highly effective in identifying and responding to emerging and complex fraud strategies.

[0045] Implementing the Telephone Fraud Prevention System 100 involves numerous technical considerations to ensure optimal performance and integration. The system's architecture is designed to handle diverse call volumes, from individual users to large enterprises, achieving scalability through modular design and efficient resource management. The system is designed to be compatible with various telecommunications systems and devices, ensuring consistent functionality across different hardware and software environments, whether integrated into personal smartphones or enterprise communication platforms. Real-time call processing and fraud detection require extremely low latency for a smooth user experience. The system employs optimized algorithms and efficient processing technology to ensure real-time response and action in live conversations. The user intervention interface 160 is designed to be intuitive and easy to use, allowing users to easily monitor and control call interactions. Clear visual indicators and simple controls ensure users can interact with the system without technical complexity. Strong security protocols are implemented throughout the system to protect data integrity and prevent unauthorized access. Encryption, reliable authentication methods, and regular security audits are essential components of maintaining system security.

[0046] To illustrate the functions and applications of the telephone fraud prevention system 100, consider the following embodiment. First, please refer to... Figure 6 , Figure 6The flowchart illustrates the operation of the telephone fraud prevention system in a personal use scenario. First, as shown in step S110, the user receives a call from an unknown number while driving. Next, as shown in step S120, the telephone fraud prevention system 100 automatically answers the call and engages in conversation with the caller 10 to verify their identity. Furthermore, as shown in step S130, the user listens to and observes the interaction of the AI ​​module 120 in real time through the audio output interface 130. During the call, as shown in step S140, the AI ​​module 120 detects suspicious language indicating a phishing attempt and classifies the call as "dangerous." Next, as shown in step S150, the telephone fraud prevention system 100 immediately terminates the call, blocks the number, and alerts the user to the fraudulent attempt. Furthermore, as shown in step S160, the incident is reported to the relevant regulatory agency 30 for further action.

[0047] In a business setting, the company integrates the 100 Telephone Fraud Prevention System into its customer service hotline to manage incoming inquiries and prevent fraudulent calls. Please refer to... Figure 7 , Figure 7 The diagram illustrates the operational flow of the telephone fraud prevention system in a personal use scenario. First, as shown in step S210, when a customer calls, the AI ​​module 120 answers and verifies the caller's identity through a series of security questions and interaction methods. Next, as shown in step S220, the AI ​​module 120 determines whether the call is safe. If the call is deemed "safe," as shown in step S230, the AI ​​module 120 transfers the call to the appropriate department and schedules a follow-up appointment in the company's calendar system. Alternatively, as shown in step S240, for "suspicious" calls, the interaction is recorded by the AI ​​module 120 for manual review by the security team. Furthermore, as shown in step S250, for "dangerous" calls, the AI ​​module 120 automatically terminates the call, blocks the caller 10, and reports the incident to the company's cybersecurity unit and / or relevant management agencies.

[0048] Furthermore, in a multi-platform integrated scenario, users utilize the telephone fraud prevention system 100 through multiple electronic devices, including smartphones, tablets, and desktop computers. The integration module 150 synchronizes conversation summaries and calendar events across all devices, ensuring consistent access to call information and scheduled events regardless of the electronic device used. This tight integration enhances user convenience and ensures that important information is readily available across different platforms.

[0049] Compared to existing fraud prevention solutions, the Telephone Fraud Prevention System 100 boasts several innovative features and advantages. Its proactive approach allows the AI ​​module 120 to interact with callers 10 in real time to verify the legitimacy of the call, unlike traditional systems that passively screen calls based on static data. This proactive approach significantly enhances the system's ability to detect and prevent fraudulent activities. The AI ​​module 120's continuous learning and adaptive capabilities enable the Telephone Fraud Prevention System 100 to proactively address evolving fraud tactics. By refining its algorithms based on continuous interaction and user feedback, the Telephone Fraud Prevention System 100 maintains high accuracy and efficient threat detection capabilities. Its user-centric design, including real-time monitoring and user intervention capabilities, gives users greater control and flexibility in call interactions, enhancing trust and ease of use, and ensuring the system meets user preferences and needs.

[0050] Furthermore, the tight integration of the telephone fraud prevention system 100 with external services 20 such as calendars and messaging platforms provides a unified and efficient user experience. Through automated data synchronization and event management, the telephone fraud prevention system 100 reduces the burden of manual data entry and improves organizational efficiency. Robust security measures, including adaptive fraud detection, data encryption, and secure storage protocols, ensure the security of sensitive information during call processing and storage. Adherence to stringent privacy standards enhances user trust and ensures compliance with data protection regulations. In addition, the scalability and compatibility with various telecommunications systems and devices ensure broad applicability and easy integration into diverse user environments.

[0051] While the embodiments described herein provide a comprehensive overview of the functionality of the telephone fraud prevention system 100, various modifications and variations can be implemented without departing from the scope of the invention. These modifications include, but are not limited to, alternative classification schemes, where the risk classification method can be adjusted to incorporate additional classification categories or different judgment criteria based on specific user needs or emerging fraud patterns. Enhanced verification methods, such as integrating biometrics or multi-factor authentication, can further strengthen the system's ability to verify caller 10. The telephone fraud prevention system 100 can also be extended to integrate a wider range of external services, such as customer relationship management (CRM) systems, enterprise resource planning (ERP) platforms, and other organizational tools, further expanding its applicability.

[0052] The system offers user-adjustable settings to modify the sensitivity, response actions, and integration preferences of the Telephone Fraud Prevention System 100, enhancing its adaptability to individual or organizational needs. Furthermore, multilingual support expands the system's applicability across different regions and user groups, ensuring effective fraud prevention in multilingual environments. These modifications and changes reflect the versatility and scalability of the Telephone Fraud Prevention System 100, allowing it to be customized to specific applications and evolving user needs.

[0053] Although the present invention has been disclosed above with reference to embodiments, it is not intended to limit the present invention. Those skilled in the art can make appropriate modifications without departing from the spirit and scope of the present invention. Therefore, the scope of protection of the present invention shall be determined by the claims.

Claims

1. A telephone fraud prevention system, characterized in that, include: A communication interface configured to receive and transmit telephone calls; An artificial intelligence module is configured to: When a user is unable to answer a call or a caller is not identified, it means that the user will automatically answer the call. Natural language processing and semantic analysis are used to conduct a real-time dialogue with the caller to verify the caller's identity and assess the legitimacy of the phone call. The content of the conversation is analyzed in real time to detect potential fraudulent activities by identifying suspicious keywords or patterns related to scams; Based on the analysis results, the telephone call was classified into one of several risk categories, which at least include safe, suspicious, and dangerous. For telephone calls classified as dangerous, the call will be automatically terminated, the caller's number will be blocked, and the incident will be reported to the management agency. Real-time phishing assessment is performed on any web links or URLs provided by callers during the conversation, and the web links are compared with a pre-stored blacklist of malicious URLs to identify phishing attempts. Use image recognition and optical character recognition technologies to analyze any visual content provided by the caller during the conversation; and Based on previous call records and data from external threat intelligence sources, it continuously updates its fraud detection algorithm parameters; An audio output interface is configured to allow the user to monitor the ongoing conversation in real time. A user intervention interface is configured to allow the user to intervene in and control the phone call, and can override the actions taken by the artificial intelligence module; A data storage component is configured to store conversation summaries, classification data, and records of suspicious or dangerous telephone calls in encrypted form; and An integration module is configured to extract relevant information from the conversation and integrate it into external services, including calendars and messaging platforms, automatically schedule events in the user's calendar, and send corresponding notifications through the messaging platform.

2. The telephone fraud prevention system as described in claim 1, characterized in that, This AI module is configured to support dialogue and analysis in multiple languages.

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