Computer data security protection system based on Internet of Things

Abstract

The invention relates to the technical field of computer security, in particular to a computer data security protection system based on Internet of Things, which comprises a monitoring module used for monitoring the working state and data transmission condition of Internet of Things terminal equipment in real time. And the encryption module is used for encrypting data transmission by using an encryption technology. And the authentication module is used for performing identity authentication on the user and the terminal equipment by using a cryptographic technology. And the recording module is used for dynamically adjusting the verification hierarchy according to the use habit of the user. The authorization module is used for jointly undertaking authentication and authorization tasks through multiple nodes; identity authentication and authorization tasks are divided into basic authentication, intermediate authentication and advanced authentication. The login time, the use place and the operation habit of the user are analyzed in real time through the big data and machine learning technology, the system can dynamically adjust the authentication strength according to the risk level, the safety of the system is improved, and therefore measures are taken to protect property and privacy safety.

Description

Technical Field

[0001] The present invention relates to the field of computer security technology, and in particular to a computer data security protection system based on the Internet of Things. Background Art

[0002] With the development of the times, all walks of life have actively introduced relevant technical means such as the Internet and big data. The widespread application of various high-tech technologies has brought about tremendous changes in people's learning, entertainment, life and consumption. However, it should also be noted that while the Internet and big data technologies are widely used, computer network security issues are increasing. Network information security issues will not only affect individuals, but also enterprises and society. Therefore, technology companies are also paying more and more attention to investment in network security, and developers have begun to conduct extensive research on computer network information security in the big data era.

[0003] In the prior art, a single authentication technology is usually used for security protection. Such authentication methods are usually relatively simple, which makes information easily leaked or cracked by attackers. For example, attackers disguise themselves as legitimate websites or other applications to trick users into entering their account passwords, thereby obtaining user credential information. Many users tend to use simple and easy-to-remember passwords and use the same password on multiple platforms. Once the password of a platform is leaked, other platforms will also be affected.

[0004] To sum up, how to solve the problem that the existing technology uses a single authentication technology for security protection, which makes information easily leaked or cracked by attackers has become a difficult problem that needs to be solved urgently in this field. Therefore, it is necessary to propose a computer data security protection system based on the Internet of Things. Summary of the invention

[0005] To solve the above problems, the present invention provides a computer data security protection system based on the Internet of Things, which uses big data and machine learning technology to perform real-time analysis on users' login time, usage location and operating habits. The system can dynamically adjust the authentication strength according to the risk level, improve the security of the system, and take measures to protect property and privacy security.

[0006] In order to achieve the above-mentioned purpose, the technical solution of the present invention is as follows: A computer data security protection system based on the Internet of Things is composed of a monitoring module, an encryption module, an authentication module, a recording module and an authorization module.

[0007] The monitoring module is used to monitor the working status and data transmission of IoT terminal devices in real time.

[0008] The encryption module is used to encrypt data transmission using encryption technology and also provides decryption function.

[0009] The authentication module is used to authenticate the identity of users and terminal devices using cryptographic technology.

[0010] The recording module is used to dynamically adjust the verification level according to user usage habits; and set different access rights according to the user's role and attributes.

[0011] The authorization module is used to jointly undertake authentication and authorization tasks through multiple nodes; the identity authentication and authorization tasks are divided into basic authentication, intermediate authentication and advanced authentication.

[0012] Furthermore, IoT terminal devices include but are not limited to computers, mobile phones, tablets, smart watches and smart homes.

[0013] Furthermore, the monitoring module includes the following units:

[0014] The acquisition unit is used to collect physical world data and convert it into digital signals.

[0015] The network unit is used to transmit the collected data using network security technology.

[0016] The data processing unit is used to analyze and process the transmitted data and extract useful information.

[0017] The application unit is used to establish the management platform and operation platform of actual applications according to user needs.

[0018] Furthermore, network security technologies include network firewalls, intrusion detection systems IDS and intrusion prevention systems IPS.

[0019] Furthermore, the encryption technology uses symmetric encryption AES and asymmetric encryption RSA algorithms.

[0020] Furthermore, cryptographic techniques include digital signatures, public key and private key authentication techniques.

[0021] Further, authentication levels include single-factor authentication, multi-factor authentication, and biometric authentication.

[0022] Further, dynamically adjusting the verification level includes the following steps:

[0023] S1. Behavior analysis: Use big data and machine learning technology to collect and analyze users' login time, usage location and operation habits to build user behavior models.

[0024] S2. User grouping: Divide users into different groups based on their behavior patterns, and set different access permissions for each group.

[0025] S3. Permission setting: Use real-time behavioral analysis and biometric recognition to set access permissions.

[0026] Furthermore, in S1, the operating habits include but are not limited to typing speed, mouse movement trajectory, keyboard tapping pattern and screen sliding speed.

[0027] Furthermore, in the authorization module, single-factor authentication is used for basic authentication in low-risk scenarios; multi-factor authentication is used for intermediate authentication in medium-risk scenarios; and biometrics are used for advanced authentication in high-risk scenarios.

[0028] The above scheme has the following principles and beneficial effects:

[0029] 1. The present invention adjusts the verification method according to the user's behavior patterns and habits. By dynamically adjusting the verification level, the system provides corresponding security measures according to the user's actual risk level. By using big data and machine learning technology to conduct real-time analysis of the user's login time, usage location and operation habits, the system can promptly detect abnormal behaviors, such as abnormal login attempts or data leakage risks, and take measures to protect property and privacy security.

[0030] By combining single-factor, multi-factor and biometric authentication, the system can dynamically adjust the authentication strength according to the risk level, improving the security of the system, especially in high-risk scenarios, where biometric authentication is almost impossible to forge, effectively preventing illegal access. In low-risk scenarios, using a simple single-factor authentication method can reduce the cumbersome verification steps encountered by users in daily use and improve operational convenience.

[0031] 2. The present invention can monitor the working status and data transmission of IoT terminal devices in real time through the monitoring module, and detect abnormal behavior in time. Once abnormal behavior or potential threats are detected, a multi-level response mechanism is immediately triggered to ensure computer protection security. The data processing unit conducts in-depth analysis of the collected data, extracts key information, and provides data support for the formulation of security strategies. This helps to identify potential security vulnerabilities and take preventive measures in advance.

[0032] 3. The present invention uses symmetric encryption AES and asymmetric encryption RSA technology to ensure the confidentiality and integrity of data during transmission. It provides encryption and decryption functions to ensure that data can be properly protected at both the sending and receiving ends, prevent data from being intercepted, tampered with or leaked, effectively prevent access by illegal users or devices, and further ensure the security of the system.

[0033] 4. The present invention builds a multi-level defense system through network firewall, intrusion detection system IDS and intrusion prevention system IPS technology, which can effectively identify and intercept potential network attacks and ensure the security of network data. According to the real-time monitored network traffic and attack behavior, the network security strategy can be dynamically adjusted to further increase defense measures.

[0034] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is a structural block diagram of a computer data security protection system based on the Internet of Things in an embodiment of the present invention.

[0036] Figure 2 4 is a structural block diagram of a monitoring module in an embodiment of the present invention.

[0037] Figure 3 Schematic diagram of dynamically adjusting the verification level in an embodiment of the present invention. DETAILED DESCRIPTION

[0038] The following is further described in detail through specific implementation methods:

[0039] Embodiment 1:

[0040] As attached Figure 1-Figure 3 As shown: A computer data security protection system based on the Internet of Things, which consists of a monitoring module, an encryption module, an authentication module, a recording module and an authorization module. Among them, the monitoring module is mainly used to monitor the working status and data transmission of the Internet of Things terminal equipment in real time. The encryption module is used to encrypt data transmission and provide decryption function. The authentication module is used to authenticate the user and the terminal device. The recording module is used to dynamically adjust the verification level according to the user's usage habits. The authorization module jointly undertakes the authentication and authorization tasks through multiple nodes; the authentication and authorization tasks are divided into basic authentication, intermediate authentication and advanced authentication.

[0041] The following is a detailed explanation of the functions of each module:

[0042] The monitoring module is used to monitor the working status and data transmission of the IoT terminal devices in real time. The IoT terminal devices include but are not limited to computers, mobile phones, tablets, smart watches and smart homes; in this embodiment, computers and mobile phones are selected.

[0043] The encryption module is used to encrypt data transmission using symmetric encryption AES and asymmetric encryption RSA algorithms; it also provides decryption functions.

[0044] The authentication module is used to authenticate the identity of users and terminal devices using digital signatures, public keys, and private key authentication technologies.

[0045] Specifically, the monitoring module monitors the working status and data transmission of IoT terminal devices in real time. If the terminal device communicates with a virus website, the monitoring module can detect abnormal data traffic or behavior patterns. If the monitoring module is improperly configured or has vulnerabilities, attackers may bypass monitoring or use false data to cover up their malicious activities. The encryption module uses symmetric encryption AES and asymmetric encryption RSA algorithms to encrypt data transmission to ensure the confidentiality and integrity of data during transmission. Before transmitting sensitive information, the authentication module can use the public key to encrypt data, and only users holding the corresponding private key can decrypt the data.

[0046] For example, suppose a user is using a computer and a mobile phone to surf the Internet. The user attempts to access an unknown website link, which may be obtained through email, social media, or other channels. The monitoring module detects that the user is accessing an unknown website and that the website may contain malicious content. The monitoring module triggers an alarm and reminds the user that the website may be unsafe.

[0047] Even if the user continues to visit the website, all transmitted data will be encrypted by the encryption module. If the website attempts to send malicious code to the user's device, the code will be encrypted, making it difficult to execute. If the website requires the user to provide personal information or download certain files, the authentication module will ask the user to authenticate his identity.

[0048] The recording module is used to dynamically adjust the verification level according to the user's usage habits. The verification level includes single-factor authentication, multi-factor authentication and biometric authentication; and set different access rights according to the user's role and attributes.

[0049] The dynamic adjustment of the verification level includes the following steps:

[0050] S1. Behavior analysis: Use big data and machine learning technology to collect and analyze users' login time, usage location and operation habits to build user behavior models.

[0051] S2. User grouping: Divide users into different groups based on their behavior patterns, and set different access permissions for each group.

[0052] S3. Permission setting: Use real-time behavioral analysis and biometric recognition to set access permissions.

[0053] Specifically, the recording module uses big data and machine learning technology to collect information such as user login time, usage location, operating habits (such as typing speed, mouse movement trajectory, keyboard tapping pattern and screen sliding speed). The system builds a user behavior model based on the collected data and identifies the user's normal operating mode.

[0054] The system divides users into different groups based on their behavior patterns. For example, the operating habits of the elderly are significantly different from those of ordinary children. The typing speed and reading sliding speed of the elderly are significantly slower than those of ordinary children.

[0055] The record module divides users into different groups. Adults are considered regular users with higher trust and access rights, while children are considered occasional users with lower trust.

[0056] For example, a child picks up an adult's phone, opens a game and starts playing. The recording module monitors the user's behavior pattern in real time and detects that the current operating habits do not match the adult's behavior model. The system dynamically adjusts the verification level based on the detection results and requires multi-factor authentication or biometric authentication.

[0057] Even if the child is able to pass the verification, the system will still set the corresponding access rights according to the user role and attributes. The child is prohibited from making in-game purchases or top-ups. If the child fails to pass the verification or the permission setting does not allow top-ups, the top-up operation cannot be completed. At the same time, the system records the attempt and notifies the adult about the unusual activity.

[0058] The authorization module is used to jointly undertake authentication and authorization tasks through multiple nodes; the identity authentication and authorization tasks are divided into basic authentication, intermediate authentication and advanced authentication.

[0059] In low-risk scenarios, single-factor authentication is used for basic authentication; in medium-risk scenarios, multi-factor authentication is used for intermediate authentication; in high-risk scenarios, biometrics are used for advanced authentication.

[0060] Specifically, the authorization module is a complex and flexible system that manages access rights based on user identity and environmental factors. By having multiple nodes jointly undertake authentication and authorization tasks, the security and reliability of the system can be enhanced. In terms of dividing identity authentication and authorization levels, basic authentication, intermediate authentication, and advanced authentication are used as different levels, and are dynamically adjusted according to actual conditions and security requirements.

[0061] For example, Mr. Zhang received a fake bank notification SMS, asking him to log in to the bank app immediately for verification. Mr. Zhang followed the SMS instructions to log in to the bank app and tried to make a large transfer. The recording module monitors the user's behavior pattern in real time and detects that the current operation habits do not match Mr. Zhang's daily behavior model. The system marks Mr. Zhang's account as high-risk. At the same time, according to the preset rules, Mr. Zhang is temporarily classified as a user group that requires a higher level of authentication.

[0062] Because the transfer amount is large and the login location is unusual, the system further requires biometric authentication (such as fingerprint, iris or facial recognition) for further verification. If Mr. Zhang fails to pass the biometric authentication, the transfer operation will be rejected.

[0063] Embodiment 2:

[0064] As attached Figure 2 As shown, the difference from the above embodiment is that the monitoring module includes a collection unit, a network unit, a data processing unit and an application unit.

[0065] Specifically, the acquisition unit is mainly used to collect data from the physical world and convert it into digital signals. The network unit is used to transmit the collected data using network security technology; network security technology includes network firewalls, intrusion detection systems IDS and intrusion prevention systems IPS. The data processing unit is used to analyze and process the transmitted data and extract useful information. The application unit is used to establish a management platform and operation platform for actual applications according to user needs.

[0066] For example, users view the screen of a home network camera in a smart home through a smartphone application. The network unit ensures the security of data transmission and prevents access by unauthorized devices through technologies such as firewalls, IDS and IPS.

[0067] The acquisition unit captures the video stream and converts it into a digital signal. The intrusion detection system IDS detects abnormal traffic or behavior and sends an alert to the user. When the system detects abnormal activity, the intrusion prevention system IPS actively blocks data transmission and takes measures to prevent data from being stolen.

[0068] Through the coordinated work of the various components of the monitoring module, the system can effectively prevent unauthorized data access and protect the privacy of users. In this example, even if someone tries to steal family privacy through the Internet, the system can prevent potential risk operations through real-time behavior analysis, intrusion detection and defense mechanisms, thereby protecting the privacy of users' families.

[0069] Obviously, the above embodiments are merely examples for the purpose of clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the invention.

Claims

1. A computer data security protection system based on the Internet of Things, characterized by: It consists of monitoring module, encryption module, authentication module, recording module and authorization module; Monitoring module, used to monitor the working status and data transmission of IoT terminal devices in real time; An encryption module, used for encrypting data transmission using encryption technology; It also provides decryption function; Authentication module, used to authenticate users and terminal devices using cryptographic technology; The recording module is used to dynamically adjust the verification level according to user usage habits; And set different access permissions based on the user's role and attributes; Authorization module, used to undertake authentication and authorization tasks through multiple nodes; The identity authentication and authorization tasks are divided into basic authentication, intermediate authentication and advanced authentication.

2. The computer data security protection system based on the Internet of Things according to claim 1 is characterized in that: IoT terminal devices include but are not limited to computers, mobile phones, tablets, smart watches and smart homes.

3. The computer data security protection system based on the Internet of Things according to claim 2 is characterized in that: The monitoring module includes the following units: An acquisition unit, used to collect data from the physical world and convert it into digital signals; A network unit, used to transmit the collected data using network security technology; A data processing unit is used to analyze and process the transmitted data and extract useful information; The application unit is used to establish the management platform and operation platform of actual applications according to user needs.

4. The computer data security protection system based on the Internet of Things according to claim 3 is characterized in that: Network security technologies include network firewalls, intrusion detection systems (IDS) and intrusion prevention systems (IPS).

5. The computer data security protection system based on the Internet of Things according to claim 4 is characterized in that: The encryption technology uses symmetric encryption AES and asymmetric encryption RSA algorithms.

6. The computer data security protection system based on the Internet of Things according to claim 5 is characterized in that: Cryptography technology includes digital signature, public key and private key authentication technology.

7. The computer data security protection system based on the Internet of Things according to claim 6 is characterized in that: Authentication levels include single-factor authentication, multi-factor authentication, and biometric authentication.

8. The computer data security protection system based on the Internet of Things according to claim 7 is characterized in that: Dynamically adjusting the validation level includes the following steps: S1. Behavior analysis: Use big data and machine learning technology to collect and analyze users' login time, usage location and operation habits to build user behavior models; S2. User grouping: users are divided into different groups according to their behavior patterns, and different access rights are set for each group; S3. Permission setting: Use real-time behavioral analysis and biometric recognition to set access permissions.

9. The computer data security protection system based on the Internet of Things according to claim 8 is characterized in that: In S1, the operation habits include but are not limited to typing speed, mouse movement trajectory, keyboard tapping pattern and screen sliding speed.

10. The computer data security protection system based on the Internet of Things according to claim 9 is characterized in that: In the authorization module, single-factor authentication is used for basic authentication in low-risk scenarios; multi-factor authentication is used for intermediate authentication in medium-risk scenarios; and biometrics is used for advanced authentication in high-risk scenarios.

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