Interface joint debugging analysis method and system for data privacy security

Abstract

The invention provides an interface joint debugging analysis method and system for data privacy security, and the specific analysis method comprises four aspects: dynamic encryption and intelligent key management, dynamic access control based on behaviors, intelligent log monitoring and real-time threat detection, and data sensitivity automatic identification and intelligent protection. Wherein the dynamic encryption and intelligent key management comprise two directions of dynamic encryption algorithm selection and intelligent key management, and the behavior-based dynamic access control comprises two directions of dynamic role and authority distribution and behavior anomaly detection and limitation. The intelligent log monitoring and real-time threat detection comprise two directions of log intelligent analysis and a real-time response mechanism, and the data sensitivity automatic identification and intelligent protection comprise two directions of data sensitivity automatic identification and intelligent protection and intelligent data protection. And the data security is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data privacy security, and particularly to an interface joint debugging analysis method and system for data privacy security. Background Art

[0002] Data privacy security refers to measures to protect personal data from being accessed or used by unauthorized third parties, ensuring the privacy, integrity, and availability of personal data. Data privacy security is of great significance to individuals and society. The leakage of personal data may lead to economic losses, identity theft, and other serious consequences. Currently, many systems use static key management mechanisms to ensure the access security of interfaces. Static keys are usually generated by administrators during system deployment and are used for authentication and data encryption during interface calls. Such solutions protect interface access through fixed keys, and common solutions include authentication mechanisms such as API keys and OAuth.

[0003] However, the existing methods of protecting data using static key management mechanisms have the following problems in the process of use: Insufficient data security awareness: When developers conduct interface joint debugging, they often focus more on function implementation and ignore data privacy security issues, lacking awareness of identifying and protecting sensitive data; Lack of effective security mechanisms: Traditional interface joint debugging methods lack effective security mechanisms and cannot effectively protect sensitive data, easily leading to data leakage; Security risks: Once a static key is leaked, it may lead to long-term security risks because the key usually does not expire automatically and requires manual intervention to update; Inadaptability to complex environments: For systems that need to handle different user roles, permissions, and environments (such as development, testing, production), static key management is difficult to effectively distinguish the security requirements of different scenarios and easily leads to permission abuse or unauthorized access. Therefore, corresponding technical solutions need to be designed to solve the existing technical problems. Summary of the Invention

[0004] The purpose of the present invention is to provide an interface joint debugging analysis method and system for data privacy security, which solves the problems of insufficient data security awareness: When developers conduct interface joint debugging, they often focus more on function implementation and ignore data privacy security issues, lacking awareness of identifying and protecting sensitive data; Lack of effective security mechanisms: Traditional interface joint debugging methods lack effective security mechanisms and cannot effectively protect sensitive data, easily leading to data leakage; Security risks: Once a static key is leaked, it may lead to long-term security risks because the key usually does not expire automatically and requires manual intervention to update; Inadaptability to complex environments: For systems that need to handle different user roles, permissions, and environments (such as development, testing, production), static key management is difficult to effectively distinguish the security requirements of different scenarios and easily leads to permission abuse or unauthorized access, this technical problem.

[0005] To achieve the above object, the present invention provides the following technical solutions: An interface joint debugging analysis method for data privacy and security. The specific analysis method includes four aspects: dynamic encryption and intelligent key management, behavior-based dynamic access control, intelligent log monitoring and real-time threat detection, and automatic data sensitivity identification and intelligent protection. Among them, the dynamic encryption and intelligent key management include two directions: dynamic encryption algorithm selection and intelligent key management. The behavior-based dynamic access control includes two directions: dynamic role and permission allocation and behavior anomaly detection and restriction. The intelligent log monitoring and real-time threat detection include two directions: log intelligent analysis and real-time response mechanism. The automatic data sensitivity identification and intelligent protection include two directions: automatic data sensitivity identification and intelligent protection and intelligent data protection.

[0006] As a preferred embodiment of the present invention, for the dynamic encryption algorithm selection: According to the sensitivity of the data, the interface call frequency, and the transmission environment, different data encryption levels are set. For the interface transmitting important financial data, the AES-256 encryption algorithm is used. For low-sensitivity data, the AES-128 encryption algorithm is used. In the intelligent key management system: Step 1: Assign a key to each encryption algorithm; Step 2: The key management module will generate an alarm based on the key leakage risk analysis. If the system detects the risk of illegal access or leakage of the key, it will immediately trigger the process of key replacement and system encryption reconstruction.

[0007] As a preferred embodiment of the present invention, for the dynamic role and permission allocation: Step 1: At initialization, the system assigns basic permissions according to the user's identity and role; Step 2: When the user accesses the interface, the system monitors the user's behavior in real time and dynamically adjusts their permissions. If a user suddenly requests access to a large amount of sensitive data, the system will automatically require additional verification or temporarily reduce their permissions; For the behavior anomaly detection and restriction: Step 1: The behavior monitoring module will continuously track the user's historical behavior and establish a behavior feature library for each user; Step 2: When the system detects abnormal behavior, it will immediately trigger an alarm, restrict the user's access to sensitive interfaces, and may require multi-factor authentication to confirm their identity.

[0008] As a preferred embodiment of the present invention, the intelligent log analysis is as follows: Step 1, the system automatically collects access logs of all interfaces, including access time, user information, operation type, and transmitted data; Step 2, the intelligent analysis module analyzes the log data based on machine learning algorithms to identify potential attack patterns, and the system identifies SQL injection attacks, brute-force login attempts, and abnormal requests; Step 3, for each detected threat, the system automatically adjusts the protection strategy according to the risk level, blocks the attack in real time, and records detailed logs for security auditing. The real-time response mechanism is as follows: Step 1, the threat detection module can identify and respond at the initial stage of an attack. When the system detects abnormal traffic, it automatically allocates traffic or analyzes data packets to prevent data leakage; Step 2, the system not only blocks the attack source but also sends real-time notifications to the administrator, providing information on the attack pattern, affected data, and attacker IP address for further analysis and response.

[0009] As a preferred embodiment of the present invention, the automatic identification of data sensitivity is as follows: Step 1, the system automatically identifies sensitive information in the data by scanning fields, such as personal identity information, financial records, and medical data; Step 2, the identified sensitive data is classified and corresponding encryption or de-sensitization processing is applied. The system can use data de-sensitization technology to hide some sensitive information or encrypt the entire data field through encryption algorithms. The intelligent data protection is as follows: Step 1, for sensitive data, the system takes multiple protection measures, including encrypted storage, access control, and data auditing, to ensure that the data can only be accessed by authorized users; Step 2, the data protection method is automatically adjusted according to the sensitivity of the data. For medical data, the system uses the strongest encryption technology, while for non-sensitive log data, no encryption is performed.

[0010] As a preferred embodiment of the present invention, the specific analysis system introduces a dynamic encryption algorithm and an intelligent key management mechanism, adopts a behavior-based dynamic access control model to replace the traditional static permission control, and improves the interface security protection ability through intelligent log analysis and real-time threat detection mechanisms.

[0011] As a preferred embodiment of the present invention, the selection of the dynamic encryption algorithm is as follows: The system dynamically determines the use of different encryption algorithms and encryption intensities according to the sensitivity of the data, the transmission environment, and the interface call frequency. High-strength encryption is used for sensitive data, while lightweight encryption is used for non-sensitive data. The intelligent key management is as follows: The key is rotated regularly or automatically generated according to a preset strategy during use to avoid the risk of leakage of static keys. In addition, the system can evaluate the security of the key through intelligent analysis. Once it is found that the key may be leaked, it is immediately replaced and relevant personnel are notified for operation.

[0012] As a preferred embodiment of the present invention, the role permission allocation: dynamically allocates permissions according to the actual behaviors and needs of users, avoiding users having excessive permissions when they do not need them; the behavior anomaly detection and restriction: the system identifies and restricts potential malicious behaviors through real-time behavior analysis. Once an abnormal behavior is detected, the system automatically performs permission restriction or alerts.

[0013] As a preferred embodiment of the present invention, for the intelligent log analysis, the system uses machine learning and big data analysis technologies to automatically identify potential attack patterns, identify complex attack behaviors, and be able to adapt to new attack means. The system automatically conducts threat analysis through algorithms such as pattern recognition and anomaly detection; real-time response mechanism: the log analysis and threat detection mechanisms can respond in real time at the initial stage of an attack, promptly isolate suspicious activities, and reduce the risk of data leakage or system intrusion. The system completes data processing and threat assessment to ensure an immediate response.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0015] The interface joint debugging analysis method and system for data privacy security provided by the present invention improve data security: by classifying the data transmitted through the interface and configuring privacy security policies, effectively preventing the leakage of sensitive data and improving data security; reducing security risks: through interface joint debugging tests and security risk assessments, timely discovering and fixing security vulnerabilities to reduce security risks; improving development efficiency: providing a unified interface joint debugging analysis platform, simplifying the development process and improving development efficiency. Specific implementation manners

[0016] Embodiment:

[0017] An interface joint debugging analysis method for data privacy security, the specific analysis method includes four aspects: dynamic encryption and intelligent key management, behavior-based dynamic access control, intelligent log monitoring and real-time threat detection, and automatic identification and intelligent protection of data sensitivity. Among them, dynamic encryption and intelligent key management include two directions: dynamic encryption algorithm selection and intelligent key management, behavior-based dynamic access control includes two directions: dynamic role and permission allocation and behavior anomaly detection and restriction, intelligent log monitoring and real-time threat detection includes two directions: log intelligent analysis and real-time response mechanism, and automatic identification and intelligent protection of data sensitivity includes two directions: automatic identification and intelligent protection of data sensitivity and intelligent data protection.

[0018] Dynamic Encryption Algorithm Selection: Based on the sensitivity of data, interface call frequency, and transmission environment, different data encryption levels are set. For interfaces transmitting important financial data, the AES-256 encryption algorithm is adopted. For low-sensitivity data, the AES-128 encryption algorithm is used. In the intelligent key management system: Step 1, assign a key to each encryption algorithm; Step 2, the key management module generates an alarm based on the analysis of key leakage risk. If the system detects the risk of illegal access or leakage of the key, it immediately triggers the process of key replacement and system encryption reconstruction.

[0019] Dynamic Role and Permission Assignment: Step 1, during initialization, the system assigns basic permissions according to the user's identity and role; Step 2, when the user accesses the interface, the system monitors the user's behavior in real time and dynamically adjusts their permissions. If a user suddenly requests access to a large amount of sensitive data, the system will automatically require additional verification or temporarily reduce their permissions; Behavior Anomaly Detection and Restriction: Step 1, the behavior monitoring module continuously tracks the user's historical behavior and establishes a behavior feature library for each user; Step 2, when the system detects abnormal behavior, it immediately triggers an alarm, restricts the user's access to sensitive interfaces, and may require multi-factor authentication to confirm their identity.

[0020] Intelligent Log Analysis: Step 1, the system automatically collects access logs for all interfaces, including access time, user information, operation type, and transmitted data; Step 2, the intelligent analysis module analyzes the log data based on machine learning algorithms to identify potential attack patterns. The system identifies SQL injection attacks, brute-force login attempts, and abnormal requests; Step 3, for each detected threat, the system automatically adjusts the protection strategy according to the risk level, blocks the attack in real time, and records detailed logs for security auditing; Real-time Response Mechanism: Step 1, the threat detection module can identify and respond at the initial stage of an attack. The system automatically distributes traffic or analyzes data packets when detecting abnormal traffic to prevent data leakage; Step 2, the system not only blocks the attack source but also sends real-time notifications to the administrator, providing information about the attack pattern, affected data, and attacker IP for further analysis and response.

[0021] Automatic Recognition of Data Sensitivity: Step 1, the system automatically identifies sensitive information in the data by scanning fields in the data, such as personal identity information, financial records, and medical data; Step 2, the identified sensitive data will be classified and corresponding encryption or de - identification processing will be applied. The system can use data de - identification technology to hide some sensitive information, or encrypt the entire data field through encryption algorithms; Intelligent Data Protection: Step 1, for sensitive data, the system will implement multiple protection measures, including encrypted storage, access control, and data auditing, to ensure that the data can only be accessed by authorized users; Step 2, the data protection method will be automatically adjusted according to the sensitivity of the data. For medical data, the system will use the strongest encryption technology, while for non - sensitive log data, no encryption will be performed.

[0022] The specific analysis system introduces a dynamic encryption algorithm and an intelligent key management mechanism, adopts a behavior - based dynamic access control model to replace the traditional static permission control, and enhances the interface security protection ability through intelligent log analysis and real - time threat detection mechanisms.

[0023] Selection of Dynamic Encryption Algorithm: The system dynamically determines the use of different encryption algorithms and encryption strengths according to the sensitivity of the data, the transmission environment, and the interface call frequency. High - strength encryption is used for sensitive data, while lightweight encryption is used for non - sensitive data. Intelligent Key Management: The key will be rotated regularly or automatically generated according to a preset policy during use to avoid the risk of static key leakage. In addition, the system can evaluate the security of the key through intelligent analysis. Once it is found that the key may be leaked, it will be immediately replaced and relevant personnel will be notified for operation.

[0024] Role Permission Assignment: Permissions are dynamically assigned according to the actual behavior and needs of the user to avoid users having excessive permissions when they do not need them; Detection and Restriction of Abnormal Behavior: The system identifies and restricts potential malicious behaviors through real - time behavior analysis. Once abnormal behavior is detected, the system automatically performs permission restrictions or alerts.

[0025] Intelligent Log Analysis: The system uses machine learning and big data analysis technologies to automatically identify potential attack patterns, identify complex attack behaviors, and be able to adapt to new attack methods. The system automatically conducts threat analysis through algorithms such as pattern recognition and anomaly detection; Real - Time Response Mechanism: The log analysis and threat detection mechanisms can respond in real - time at the initial stage of an attack, promptly isolate suspicious activities, reduce the risk of data leakage or system intrusion, and the system completes data processing and threat assessment to ensure an immediate response.

[0026] In addition, the present invention is designed with interface joint debugging analysis: an automated interface joint debugging tool is adopted to perform real-time analysis during the interface data transmission process to ensure that the privacy protection measures during the data transmission process are correctly applied; the system can verify the data format and protocol during the interface joint debugging stage to ensure that all parties' interfaces comply with the privacy protection standards during the data interaction process;

[0027] Data encryption and desensitization processing: During the data transmission process, strong encryption algorithms such as AES and RSA are used to encrypt sensitive data to prevent data leakage during transmission; for some data that does not require encryption, the system can automatically desensitize it to avoid exposing sensitive information;

[0028] Permission management and authentication mechanism: During the interface joint debugging process, fine-grained permission management control is adopted to ensure that the access permissions and data processing permissions of each interface are strictly configured in accordance with the principle of least privilege; multi-factor identity authentication is integrated to ensure that only authorized users and systems can access sensitive data;

[0029] Data sensitivity identification and classification: During the interface joint debugging, the system automatically identifies the sensitivity of the data and performs corresponding encryption or desensitization processing according to the sensitivity level. Optimize the data sensitivity identification through artificial intelligence or machine learning methods;

[0030] Real-time monitoring and anomaly detection: All data streams generated during the interface joint debugging process are monitored in real time to automatically detect potential abnormal data streams or security threats; intelligent algorithms are used to analyze the data streams to timely identify data leakage, tampering, or unauthorized access behaviors;

[0031] Dynamic security policy adjustment:

[0032] Based on the security events or threats during the interface joint debugging process, the system can dynamically adjust the security policy to enhance the flexibility and adaptability of privacy protection;

[0033] When a vulnerability or non-compliance with the privacy protection standard is found, automatically push security policy updates to ensure that the system is always in a high-security state;

[0034] Log recording and audit tracking: The system makes detailed log records of all operations during the interface joint debugging process and ensures that these logs can be traced to help auditors identify potential risks.

[0035] Data encryption protection in this solution: Ensure that all sensitive data is encrypted during transmission to avoid the risk of data exposure in the public network;

[0036] Encryption key management and protection to avoid security vulnerabilities caused by key leakage;

[0037] Privacy Data Masking: The system can desensitize sensitive data according to different privacy requirements to avoid exposing personal information, especially during data analysis and debugging;

[0038] Access Control and Authentication: Strengthen access control for interfaces to prevent unauthorized access requests. Through multi-factor authentication, ensure that each access is strictly verified;

[0039] Abnormal Behavior Detection and Response: During the interface joint debugging process, monitor abnormal behaviors or malicious attacks in real time and respond promptly to prevent data leakage or tampering;

[0040] Log Protection and Audit Trail: All operation and access logs are encrypted and stored to ensure the integrity and confidentiality of the logs. Through the audit trail function, any improper operation or security event can be traced back;

[0041] Compliance and Legal Risk Prevention: Ensure that the interface joint debugging analysis complies with relevant laws and regulations on data privacy protection to avoid legal risks during the data processing process; When designing the system, consider the data privacy legal requirements in different regions to ensure the compliance of data privacy protection measures.

[0042] Finally, it should be noted that the above are only the preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions recorded in the foregoing embodiments or perform equivalent replacements for some of the technical features. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. An interface joint debugging analysis method for data privacy and security, characterized in that: The specific analysis methods include four aspects: dynamic encryption and intelligent key management, behavior-based dynamic access control, intelligent log monitoring and real-time threat detection, and automatic data sensitivity identification and intelligent protection. Among them, the dynamic encryption and intelligent key management include two directions: dynamic encryption algorithm selection and intelligent key management; the behavior-based dynamic access control includes two directions: dynamic role and permission allocation, and behavior anomaly detection and restriction; the intelligent log monitoring and real-time threat detection include two directions: intelligent log analysis and real-time response mechanism; the automatic data sensitivity identification and intelligent protection include two directions: automatic data sensitivity identification and intelligent protection, and intelligent data protection.

2. The interface joint debugging analysis method for data privacy and security according to claim 1, wherein: The dynamic encryption algorithm selection: According to the sensitivity of the data, the interface call frequency, and the transmission environment, different data encryption levels are set. For the interface transmitting important financial data, the AES-256 encryption algorithm is used; for low-sensitivity data, the AES-128 encryption algorithm is used. In the intelligent key management system: Step 1: Assign a key to each encryption algorithm; Step 2: The key management module will generate an alarm based on the key leakage risk analysis. If the system detects the risk of illegal access or leakage of the key, it will immediately trigger the process of key replacement and system encryption reconstruction.

3. A method for joint debugging and analysis of interfaces for data privacy and security according to claim 1, characterized in that: The dynamic role and permission allocation: Step 1: At initialization, the system assigns basic permissions according to the user's identity and role; Step 2: When the user accesses the interface, the system monitors the user's behavior in real time and dynamically adjusts their permissions. If a user suddenly requests access to a large amount of sensitive data, the system will automatically require additional verification or temporarily reduce their permissions; The behavior anomaly detection and restriction: Step 1: The behavior monitoring module continuously tracks the user's historical behavior and establishes a behavior feature library for each user; Step 2: When the system detects abnormal behavior, it immediately triggers an alarm, restricts the user's access to sensitive interfaces, and may require multi-factor authentication to confirm the identity.

4. A method for interface joint debugging analysis for data privacy and security according to claim 1, characterized in that: The intelligent log analysis: Step 1: The system automatically collects the access logs of all interfaces, including access time, user information, operation type, and transmitted data; Step 2: The intelligent analysis module analyzes the log data based on machine learning algorithms to identify potential attack patterns. The system identifies SQL injection attacks, brute-force login attempts, and abnormal requests; Step 3: For each detected threat, the system automatically adjusts the protection strategy according to the risk level, blocks the attack in real time, and records detailed logs for security auditing. The real-time response mechanism: Step 1: The threat detection module can identify and respond at the initial stage of the attack. When the system detects abnormal traffic, it will automatically allocate traffic or perform packet analysis to prevent data leakage; Step 2: The system will not only block the attack source but also send a real-time notification to the administrator, providing information about the attack pattern, affected data, and attacker IP, facilitating further analysis and response.

5. The interface joint debugging analysis method for data privacy security according to claim 1, characterized in that: The automatic identification of data sensitivity: Step 1, the system automatically identifies sensitive information, such as personal identity information, financial records, and medical data, by scanning the fields in the data. Step 2, the identified sensitive data will be classified and corresponding encryption or desensitization processing will be applied. The system can use data desensitization technology to hide part of the sensitive information, or encrypt the entire data field through an encryption algorithm. The intelligent data protection: Step 1, for sensitive data, the system will implement multiple protection measures, including encrypted storage, access control, and data auditing, to ensure that the data can only be accessed by authorized users. Step 2, the data protection method will be automatically adjusted according to the sensitivity of the data. For medical data, the system will use the strongest encryption technology, while for non-sensitive log data, no encryption will be performed.

6. An interface joint debugging analysis system for data privacy and security, characterized in that: Specifically, the system introduces a dynamic encryption algorithm and an intelligent key management mechanism, adopts a behavior-based dynamic access control model to replace the traditional static permission control, and enhances the interface security protection ability through intelligent log analysis and real-time threat detection mechanisms.

7. An interface joint debugging analysis system for data privacy and security according to claim 6, characterized in that: The selection of the dynamic encryption algorithm: The system dynamically determines the use of different encryption algorithms and encryption intensities according to the sensitivity of the data, the transmission environment, and the interface call frequency. High-strength encryption is used for sensitive data, and lightweight encryption is used for non-sensitive data. The intelligent key management: The key will be rotated regularly or automatically generated according to a preset policy during use to avoid the risk of static key leakage. In addition, the system can evaluate the security of the key through intelligent analysis. Once it is found that the key may be leaked, it will be immediately replaced and relevant personnel will be notified for operation.

8. An interface joint debugging analysis system for data privacy and security according to claim 6, characterized in that: The role permission assignment: Permissions are dynamically assigned according to the actual behavior and needs of the user to avoid the user having excessive permissions when not needed. The behavior anomaly detection and restriction: The system identifies and restricts potential malicious behaviors through real-time behavior analysis. Once an abnormal behavior is detected, the system automatically performs permission restrictions or alerts.

9. An interface joint debugging analysis system for data privacy and security according to claim 6, characterized in that: The intelligent log analysis: The system uses machine learning and big data analysis technologies to automatically identify potential attack patterns, identify complex attack behaviors, and be able to adapt to new attack methods. The system automatically conducts threat analysis through algorithms such as pattern recognition and anomaly detection. The real-time response mechanism: The log analysis and threat detection mechanisms can respond in real time at the initial stage of an attack, promptly isolate suspicious activities, reduce the risk of data leakage or system intrusion, and the system completes data processing and threat assessment to ensure an immediate response.