Universal privacy compliance detection method and detection system

Abstract

The invention provides a universal privacy compliance detection method and a universal privacy compliance detection system. The detection method comprises the following operation steps: step 1, collecting sensitive information; step 2, permission acquisition; 3, automatic detection: selecting a universal detection scheme or a specific detection scheme according to the type of a target to be detected, and detecting whether the privacy is compliant or not according to the detection scheme; and step 4, report generation. The method is suitable for all App application programs in China, non-intrusive privacy compliance detection is achieved through AOSP and jailbreak modes, meanwhile, the automation technology is used, manual intervention is not needed in the detection process, a report of the detection result is automatically generated, a user only needs to pay attention to the marked part in the detection report, and the detection efficiency is improved. And meanwhile, only the detection platform follows up the compliance security regulations of the Ministry of Industry and Information, and the owner of the application program does not need to pay attention, so that quick, efficient and universal privacy compliance detection is realized.

Description

Technical Field

[0001] The present invention relates to the field of privacy compliance detection, and in particular to a universal privacy compliance detection method and detection system. Background Art

[0002] During the development of an application, there are strict requirements for privacy compliance. Without the user's consent, the application may not collect the user's personal information, such as mailing address, address book, album content, camera, recorder, clipboard, and other related information.

[0003] The commonly used privacy compliance inspection method in the development process is usually to manually check the code to see whether there are functions that collect user privacy information in the code, and further determine whether these functions have user confirmation logic when they are executed. In the actual development process, multiple third-party plug-ins or SDKs are also integrated. For third-party plug-ins or SDKs, it is difficult to determine whether there is any illegal acquisition of user privacy information by manually checking the code.

[0004] When there are new privacy compliance detection items, it is necessary to manually re-implant data to detect the callers of sensitive functions corresponding to the new privacy compliance detection items and analyze privacy compliance issues. The detection efficiency is very low and the detection method is cumbersome. At the same time, the use of implanted data is highly invasive to the code and easily affects existing business.

[0005] The existing manual code inspection method is to check whether there are functions that collect user privacy information in the code, and further determine whether these functions have user confirmation logic when they are executed. In the actual development process, multiple third-party plug-ins or SDKs are also integrated. For third-party plug-ins or SDKs, it is difficult to determine whether there is illegal acquisition of user privacy information by manually checking the code. This is especially true when encountering obfuscated program code.

[0006] For applications, common static code checks or dynamic code checks usually require intrusion into the business and modification of existing business programs. The use of implanted data is highly invasive to the code, affecting existing business and easily creating vulnerabilities. If there are multiple applications that need to be checked within an enterprise or business unit, this inefficient and unsafe operation will need to be performed multiple times.

[0007] The rules for privacy compliance are not fixed but are dynamically optimized and updated. When there are new privacy compliance detection items, we need to manually re-implant the callers of data detection sensitive functions corresponding to the new privacy compliance detection items each time to analyze the privacy compliance issues. Summary of the invention

[0008] The technical problem to be solved by the present invention is to overcome the defects of inaccurate privacy compliance monitoring and low monitoring efficiency in the prior art, and to provide a universal privacy compliance detection method and detection system.

[0009] The present invention solves the above technical problems through the following technical solutions:

[0010] The present invention provides a universal privacy compliance detection method and detection system, the detection method comprising the following steps:

[0011] Step 1: Collect sensitive information and obtain the information of the target to be detected;

[0012] Step 2: Obtain permissions to obtain the permissions of the target to be detected;

[0013] Step 3: Automated detection: Select a general detection solution or a specific detection solution based on the type of target to be detected, and detect whether the privacy is compliant according to the detection solution;

[0014] Step 4: Report generation: Generate a visual report based on the test results in step 3.

[0015] In this technical solution, which is applicable to all App applications in China, non-invasive privacy compliance testing is achieved through AOSP and jailbreak. At the same time, automation technology is used, and the testing process does not require human intervention. A report on the test results is automatically generated. Users only need to pay attention to the marked parts in the test report. At the same time, only the testing platform follows up on the compliance and security regulations of the Ministry of Industry and Information Technology, and the application owners do not need to pay attention to it, thus achieving fast, efficient and universal privacy compliance testing.

[0016] Preferably, the universal detection solution in step three is a full-type Android detection application detection.

[0017] Preferably, the specific detection scheme in step three is a specific platform application detection.

[0018] Preferably, the specific operation steps for detecting whether privacy is compliant in step 3 are:

[0019] S1. Automatic interpretation and verification of privacy policy;

[0020] S2. Perform comparative analysis to determine whether privacy is compliant. If privacy is compliant, proceed directly to step 4. If privacy is not compliant, report the non-compliant behavior and then proceed to step 4.

[0021] In this technical solution, privacy compliance is tested.

[0022] Preferably, the visualization report in step 4 includes historical data comparison and trend analysis.

[0023] Preferably, the detection system comprises a monitoring and processing unit, a sensitive information collection unit, a permission acquisition unit, a sensitive information reporting unit and a self-starting and associated startup unit, and the monitoring and processing unit is respectively connected to the sensitive information collection unit, the permission acquisition unit, the sensitive information reporting unit and the self-starting and associated startup unit;

[0024] The sensitive information collection unit is connected to the authority acquisition unit, the authority acquisition unit is connected to the sensitive information reporting unit, and the sensitive information reporting unit is connected to the self-starting and associated starting unit.

[0025] In this technical solution, the sensitive information collected by the device is uniformly reported to the data platform, the privacy permissions obtained by the device are uniformly reported to the data platform, the sensitive information obtained by the device is uniformly reported to the data platform, the scene automation test, set specific scenarios, automatically run the application, and the running results are uniformly reported to the data platform.

[0026] Preferably, the monitoring processing unit includes a data analysis processing module, a report generation module, a labeling module, a data sending module and a manual confirmation module.

[0027] In this technical solution, the monitoring and processing unit is used to parse the log of the detection process according to the set format. According to the privacy compliance requirements of the Ministry of Industry and Information Technology, a privacy security report is dynamically generated, and the locations that may involve security and privacy are marked and sent to the detection personnel. The detection personnel only need to pay attention to the marked parts and perform manual secondary confirmation. If it is confirmed that it does not meet privacy compliance, it needs to be modified.

[0028] Preferably, the sensitive information collection unit includes an API slicing module, a call stack information printing module and a custom log library module.

[0029] In this technical solution, the sensitive information collected by the sensitive information collection unit is subject to collection rules based on the requirements of the industrial and information technology department, including IP address acquisition, clipboard reading and writing, Wi-Fi information acquisition, network status information acquisition, device unique identification acquisition (IDFA, Android ID), use of recorder, use of camera, use of Bluetooth, use of calendar, use of sports and fitness information, use of schedule information, use of address book, use of text messages, etc.

[0030] Preferably, the permission acquisition unit includes an acquisition module and a calling information module.

[0031] In this technical solution, the permissions used in the permission acquisition unit include camera usage permissions, microphone usage permissions, Bluetooth usage permissions, album usage permissions, address book usage permissions, device unique identification acquisition permissions, calendar usage permissions, etc.

[0032] Preferably, the sensitive information reporting unit includes an interception rule prefabrication module, an information interception module and a network request log reporting module.

[0033] In this technical solution, the sensitive information reported in the sensitive information reporting unit includes device information and user personal information.

[0034] On the basis of being in accordance with the common sense in the art, the above-mentioned preferred conditions can be arbitrarily combined to obtain the preferred embodiments of the present invention.

[0035] The positive and progressive effects of the present invention are:

[0036] The present invention is applicable to all App applications in China. Through AOSP and jailbreak, non-intrusive privacy compliance detection is achieved. At the same time, automation technology is used. The detection process does not require manual intervention and a report on the detection results is automatically generated. Users only need to pay attention to the marked parts in the detection report. At the same time, only the detection platform follows up on the compliance and security regulations of the Ministry of Industry and Information Technology. The application owner does not need to pay attention to it, thus achieving fast, efficient and universal privacy compliance detection.

[0037] The present invention can effectively improve the accuracy and efficiency of detection, reduce the risk of omissions due to human factors, and save enterprises a lot of human resources and time costs. More importantly, through automated compliance testing, enterprises can respond to policy changes more quickly, ensure that the APP continues to meet the latest compliance requirements, and enhance the competitiveness of related industries. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 The figure is a schematic diagram of the overall process of a universal privacy compliance detection method according to an embodiment of the present invention.

[0039] Figure 2 for Figure 1 The diagram shows the operation flow of the universal privacy compliance detection method for detecting whether privacy is compliant.

[0040] Figure 3 for Figure 1 The overall structural diagram of the general privacy compliance detection system is shown.

[0041] Figure 4 for Figure 1 The diagram shows the specific steps of environment construction, demand analysis and project planning for a general privacy compliance detection system.

[0042] Description of Reference Numerals

[0043] 1. Monitoring and processing unit; 11. Data analysis and processing module; 12. Report generation module; 13. Labeling module; 14. Data sending module; 15. Manual confirmation module;

[0044] 2. Sensitive information collection unit; 21. API slicing module; 22. Call stack information printing module; 23. Custom log library module;

[0045] 3. Permission acquisition unit; 31. Acquisition module; 32. Calling information module;

[0046] 4. Sensitive information reporting unit; 41. Interception rule prefabrication module; 42. Information interception module; 43. Network request log reporting module;

[0047] 5. Self-starting and associated startup units; 51. Self-starting module of the application; 52. Associated startup module of the started application. DETAILED DESCRIPTION

[0048] The present invention is further described below by way of examples, but the present invention is not limited to the scope of the examples.

[0049] Figures 1 to 4 The following is a schematic diagram of the structure of an embodiment of a universal privacy compliance detection method and detection system of the present invention. The universal privacy compliance detection method and detection system The detection method includes the following steps:

[0050] Step 1: Collect sensitive information and obtain the information of the target to be detected;

[0051] Step 2: Obtain permissions to obtain the permissions of the target to be detected;

[0052] Step 3: Automated detection: Select a general detection solution or a specific detection solution based on the type of target to be detected, and detect whether the privacy is compliant according to the detection solution;

[0053] Step 4: Report generation: Generate a visual report based on the test results in step 3.

[0054] When the present invention is used, on the Android system, based on its open source characteristics and according to pre-made privacy monitoring rules, the AOSP installation file is customized, the corresponding file is installed on the monitoring machine, and subsequent operations all use this monitoring machine.

[0055] For the iOS system, due to its closed source nature, the operating system files cannot be customized. However, based on the Hook feature, the pre-made monitoring rules can be made into a dynamic library. Based on the Jailbreak vulnerability, the pre-made dynamic library can be mounted on the monitored application through dynamic loading.

[0056] In this technical solution, which is applicable to all App applications in China, non-invasive privacy compliance testing is achieved through AOSP and jailbreak. At the same time, automation technology is used, and the testing process does not require human intervention. A report on the test results is automatically generated. Users only need to pay attention to the marked parts in the test report. At the same time, only the testing platform follows up on the compliance and security regulations of the Ministry of Industry and Information Technology, and the application owners do not need to pay attention to it, thus achieving fast, efficient and universal privacy compliance testing.

[0057] The general detection solution in step 3 is a full-type Android detection application detection.

[0058] The specific detection scheme in step three is a specific platform application detection.

[0059] The specific steps for checking whether privacy is compliant in step 3 are as follows:

[0060] S1. Automatic interpretation and verification of privacy policy;

[0061] S2. Perform comparative analysis to determine whether privacy is compliant. If privacy is compliant, proceed directly to step 4. If privacy is not compliant, report the non-compliant behavior and then proceed to step 4.

[0062] In this technical solution, privacy compliance is tested.

[0063] The visualization report in step 4 includes historical data comparison and trend analysis.

[0064] The detection system comprises a monitoring and processing unit 1, a sensitive information collection unit 2, a permission acquisition unit 3, a sensitive information reporting unit 4 and a self-starting and associated startup unit 5, wherein the monitoring and processing unit 1 is connected to the sensitive information collection unit 2, the permission acquisition unit 3, the sensitive information reporting unit 4 and the self-starting and associated startup unit 5 respectively;

[0065] The sensitive information collection unit 2 is connected to the authority acquisition unit 3 , the authority acquisition unit 3 is connected to the sensitive information reporting unit 4 , and the sensitive information reporting unit 4 is connected to the self-starting and associated starting unit 5 .

[0066] In this technical solution, the sensitive information collected by the device is uniformly reported to the data platform, the privacy permissions obtained by the device are uniformly reported to the data platform, the sensitive information obtained by the device is uniformly reported to the data platform, the scene automation test, set specific scenarios, automatically run the application, and the running results are uniformly reported to the data platform.

[0067] The monitoring processing unit 1 includes a data analysis processing module 11 , a report generation module 12 , a labeling module 13 , a data sending module 14 and a manual confirmation module 15 .

[0068] In this technical solution, the monitoring and processing unit 1 is used to parse the log of the detection process according to the set format, and a privacy security report is dynamically generated according to the privacy compliance requirements of the Ministry of Industry and Information Technology. The locations that may involve security and privacy are marked and sent to the detection personnel. The detection personnel only need to pay attention to the marked parts and perform manual secondary confirmation. If it is confirmed that it does not meet privacy compliance, it needs to be modified.

[0069] The sensitive information collection unit 2 includes an API slicing module 21, a call stack information printing module 22 and a custom log library module 23.

[0070] In the present technical solution, the sensitive information collected by the sensitive information collection unit 2 is subject to collection rules formulated according to the requirements of the industrial and information technology department, including IP address acquisition, clipboard reading and writing, Wi-Fi information acquisition, network status information acquisition, device unique identification acquisition (IDFA, Android ID), use of recorder, use of camera, use of Bluetooth, use of calendar, use of sports and fitness information, use of schedule information, use of address book, use of text messages, etc.

[0071] All APIs that obtain the above-mentioned sensitive information are sliced. When the monitored application obtains this information, it will automatically go to the slicing program to output the caller information corresponding to the call request that triggers the slice and the call location information in the target software package. In an optional manner, when the output function is executed, the call stack information corresponding to the call request is printed; the call stack information includes the caller information and call location information corresponding to the call request, and is recorded in a custom log library. After the automated process is executed, the logs in the local library are uploaded to the monitoring service platform for analysis and generation of relevant reports.

[0072] The permission acquisition unit 3 includes an acquisition module 31 and a calling information module 32 .

[0073] In this technical solution, the permissions used in the permission acquisition unit 3 include camera usage permissions, microphone usage permissions, Bluetooth usage permissions, album usage permissions, address book usage permissions, device unique identification acquisition permissions, calendar usage permissions, etc.

[0074] The acquisition module 31 is used to acquire the target software package;

[0075] The call information module 32 includes caller information corresponding to the call request and call location information in the target software package, wherein the target software package is obtained by inserting a stub code into a compiled file corresponding to the application source code, and the stub code is used to output the caller information corresponding to the call request and the call location information in the target software package when a call request for a target method is detected during the operation of the target software package;

[0076] Wherein, the target method is a method that has privacy compliance risks.

[0077] The sensitive information reporting unit 4 includes an interception rule prefabrication module 41 , an information interception module 42 and a network request log reporting module 43 .

[0078] In this technical solution, the sensitive information reported in the sensitive information reporting unit 4 includes device information and user personal information.

[0079] In the sensitive information reporting unit 4, sensitive information including device information and user personal information is uploaded in original fields;

[0080] Based on the prefabricated system, when prefabricating the system, network information interception is added to intercept all uplink data of the monitored application of the target device, and the uplink data is stored in the database, including the request header and request body information. After the monitoring is completed, the network request log in the database is reported to the monitoring service platform.

[0081] In this unit, the APP is compiled, and the interception and recording code is inserted into the privacy compliance sensitive function. When the APP is running, the time point and call chain information of each privacy behavior are recorded. The recorded time point and call chain information will be uploaded to the detection platform for storage. In this way, by recording the time point and call chain information of each privacy behavior, the time node and caller of the function can be clearly known, so as to facilitate the detection platform to sort out accurate solutions. The time point and call chain information are function call information;

[0082] Among them, the instrumentation interception recording code to the privacy compliance sensitive function is all the system functions related to hardware information, such as album function, Bluetooth function, etc. Furthermore, the new privacy clause is only added to the system functions related to hardware information. This application will instrument all the system functions related to hardware information in advance;

[0083] For example, in the privacy terms, when running a certain APP, the functions of restricting the reading of the camera and address book need to be updated. However, it is necessary to add restrictions on reading the Bluetooth function. The Bluetooth function is a system function related to the terminal hardware information. Therefore, when adding new privacy terms, there is no need to re-insert the sensitive functions, thereby improving the detection efficiency.

[0084] The self-starting and associated starting unit 5 comprises a self-starting module 51 of an application and an associated starting module 52 of an application to be started.

[0085] In the self-starting and associated starting unit 5, a plug-in code is inserted into the file, and the plug-in code is used to output the caller information corresponding to the call request and the call location information in the target software package when a call request to the target method is detected during the operation of the target software package;

[0086] Wherein, the target method is a method that has privacy compliance risks;

[0087] The stub code may be implemented based on aspect-based programming technology to run the target software package;

[0088] When the instrumentation code outputs the caller information and the calling location information, performing privacy compliance processing on the target software package according to the caller information and the calling location information;

[0089] This is different from the existing software release, which is unable to implement self-testing of calls to target methods that have privacy compliance risks, thereby affecting the normal release of the software when there are privacy compliance risks in the software. The present method embodiment implements the location of the caller and the call location at the code line level in the target software package by inserting the compiled file corresponding to the application source code, thereby facilitating self-checking of privacy compliance risks and pre-release privacy compliance risk processing of the target software package based on the caller information and the call location information before release and listing, thereby ensuring the privacy compliance rate of the software and improving the success rate and efficiency of software release.

[0090] In the present invention, dynamic code analysis and behavior monitoring technology are adopted to capture the behavior and data request operations of the application program at runtime by implanting monitoring code, that is, AOP aspect-oriented programming technology is used to insert key paths and methods to realize the recording of runtime behavior.

[0091] The present invention uses system API hook technology to intercept sensitive permission requests of applications and record request events and context information, that is, using Xposed Framework or similar frameworks to modify the execution path of applications at runtime and capture calls to sensitive operations.

[0092] In the present invention, data encryption and secure transmission use public key encryption to encrypt data to ensure that data is not stolen or tampered with during transmission from the client to the server, that is, HTTPS protocol and TLS encryption are used to provide end-to-end security protection for data transmission.

[0093] In the present invention, the back-end service and data analysis utilize machine learning and data mining techniques to analyze the collected data and identify potential privacy risks and compliance issues, that is, use a big data analysis platform, such as Apache Spark or Hadoop, for efficient data processing and analysis.

[0094] In the present invention, natural language processing technology is used for automatic interpretation and comparison of privacy policies to perform semantic analysis on the privacy policy document, automatically identify and interpret its content, that is, text mining and sentiment analysis technology are used to extract key information and compare it with the actual behavior of the application.

[0095] In the present invention, the template-based report generation technology is combined with the data visualization library to present the analysis results in an intuitive manner, that is, using BI tools such as Tableau or Power BI to visualize the data and generate customized reports.

[0096] When using the present invention, the environment must first be built, that is, the development environment must be set up, including the selection and configuration of programming languages, frameworks, IDEs and other tools; then demand analysis and project planning must be performed, that is, the corresponding modules must be developed, and unit testing and integration testing must be performed to ensure code quality and correct implementation of functions. For each technical challenge, such as encryption security, data analysis efficiency, etc., the above principles and technical means are used to solve the problem and test and verify the problem. The specific steps are as follows: Figure 4 shown.

[0097] From the above, it can be seen that the present invention utilizes the latest natural language processing, data encryption and dynamic monitoring technologies. This platform can effectively identify, analyze and handle privacy compliance related issues to ensure the security and legal use of user data.

[0098] Although the specific embodiments of the present invention are described above, it should be understood by those skilled in the art that this is only for illustration and the protection scope of the present invention is defined by the appended claims. Those skilled in the art may make various changes or modifications to these embodiments without departing from the principles and essence of the present invention, but these changes and modifications all fall within the protection scope of the present invention.

Claims

1. A general privacy compliance detection method, characterized by: The detection method comprises the following steps: Step 1: Collect sensitive information and obtain the information of the target to be detected; Step 2: Obtain permissions to obtain the permissions of the target to be detected; Step 3: Automated detection: Select a general detection solution or a specific detection solution based on the type of target to be detected, and detect whether the privacy is compliant according to the detection solution; Step 4: Report generation: Generate a visual report based on the test results in step 3.

2. The universal privacy compliance detection method according to claim 1, characterized in that: The general detection solution in step 3 is a full-type Android detection application detection.

3. The universal privacy compliance detection method according to claim 1, characterized in that: The specific detection scheme in step three is a specific platform application detection.

4. The universal privacy compliance detection method according to claim 1, characterized in that: The specific steps for checking whether privacy is compliant in step 3 are as follows: S1. Automatic interpretation and verification of privacy policy; S2. Perform comparative analysis to determine whether privacy is compliant. If privacy is compliant, proceed directly to step 4. If privacy is not compliant, report the non-compliant behavior and then proceed to step 4.

5. The universal privacy compliance detection method according to claim 1, characterized in that: The visualization report in step 4 includes historical data comparison and trend analysis.

6. A universal privacy compliance detection system is obtained according to the universal privacy compliance detection method according to any one of claims 1 to 5, characterized in that: The detection system comprises a monitoring and processing unit (1), a sensitive information collection unit (2), an authority acquisition unit (3), a sensitive information reporting unit (4) and a self-starting and associated startup unit (5), wherein the monitoring and processing unit (1) is connected to the sensitive information collection unit (2), the authority acquisition unit (3), the sensitive information reporting unit (4) and the self-starting and associated startup unit (5) respectively; The sensitive information collection unit (2) is connected to the authority acquisition unit (3), the authority acquisition unit (3) is connected to the sensitive information reporting unit (4), and the sensitive information reporting unit (4) is connected to the self-starting and associated starting unit (5).

7. The universal privacy compliance detection system according to claim 6, characterized in that: The monitoring processing unit (1) comprises a data analysis processing module (11), a report generation module (12), a marking module (13), a data sending module (14) and a manual confirmation module (15).

8. The universal privacy compliance detection system according to claim 6, characterized in that: The sensitive information collection unit (2) comprises an API slicing module (21), a call stack information printing module (22) and a custom log library module (23).

9. The universal privacy compliance detection system according to claim 6, characterized in that: The authority acquisition unit (3) comprises an acquisition module (31) and a call information module (32).

10. The universal privacy compliance detection system according to claim 6, characterized in that: The sensitive information reporting unit (4) comprises an interception rule prefabrication module (41), an information interception module (42) and a network request log reporting module (43).

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