Frida-based in-vehicle privacy information monitoring device and method

Abstract

The application provides a Frida-based vehicle-mounted privacy information monitoring device and method, and relates to the technical field of information monitoring. The device comprises an API monitoring module, which is arranged in a vehicle-mounted information entertainment system to be tested, is used for monitoring sensitive API calling behaviors of vehicle-mounted application programs of the vehicle-mounted information entertainment system to be tested, and generates monitoring data; a Socket communication module comprises a server and a client, and the server and the client are connected through communication; the server is arranged in the vehicle-mounted information entertainment system to be tested and creates a Socket port, and is used for sending the monitoring data to the client; the client is arranged in a monitoring end and is used for receiving the monitoring data; and an information display module is arranged in the monitoring end and is used for displaying the sensitive API calling behaviors according to the monitoring data.

Description

Technical Field

[0001] This invention relates to the field of information monitoring technology, and more particularly to a vehicle-mounted privacy information monitoring device and method based on Frida. Background Technology

[0002] With the rapid development of intelligent connected vehicles, the privacy data collected by in-vehicle systems, such as camera images, voice data, location trajectories, and account information, faces severe security challenges. Traditional static monitoring methods are insufficient to cope with the complex in-vehicle environment, necessitating dynamic monitoring technology to ensure data compliance. Current mainstream solutions use dynamic instrumentation technology to monitor system API calls in real time and analyze data flow. Frida-based dynamic instrumentation technology provides an efficient and flexible solution for monitoring privacy leaks in Android systems. This technology injects JavaScript scripts to hook Java or native layer functions of the target application in real time, monitoring sensitive API call behavior.

[0003] In existing technologies, current mobile application privacy leakage monitoring systems based on the Frida framework primarily target Android mobile applications (APPs). The system comprises four steps: Step 1 involves establishing a mapping relationship between privacy information and Android system permissions and APIs. Privacy information includes device information, system information, information from other apps, location information, camera information, network information, Bluetooth information, storage operations, microphone information / recording permissions, SMS information, sensor information, biometric information, and the Android system API class names and method names required to acquire and process this information. The relevant APP modules include phone, location, body activity, call, media file, SMS, contacts, calendar, other app modules, storage, Bluetooth, camera, and network modules. Step 2 involves setting Android system API hooking rules and HTTP / HTTPS packet hooking rules. Step 3 involves deploying the Frida framework and setting corresponding personal information usage scopes for different types of mobile applications based on personal information collection requirements. Step 4 involves determining whether the monitored application has privacy leakage issues based on the mapping relationship, hooking rules, and the personal information usage scopes for different types of mobile applications.

[0004] However, existing mobile application privacy breach monitoring systems based on the Frida framework have the following limitations: they can only monitor Android-based mobile applications and cannot monitor in-vehicle mobile application modules based on Android Automotive, including modules for camera, voice, user accounts, and vehicle data. Furthermore, the APIs associated with these modules are completely different from those of mobile applications. Some systems possess anti-debugging mechanisms that can detect Frida characteristics, leading to privacy breach detection failures. In-vehicle systems typically use higher Android versions, often Android 11 or above, requiring the Frida hook points to be deployed within the Android Automotive system.

[0005] In summary, there is an urgent need for a technical solution that can overcome the above-mentioned shortcomings and monitor the privacy information of in-vehicle mobile applications. Summary of the Invention

[0006] To address the problems existing in the prior art, this invention proposes a Frida-based in-vehicle privacy information monitoring device and method. This invention solves the problem that existing mobile application privacy leakage monitoring methods cannot cover in-vehicle applications, and constructs a Frida-based in-vehicle privacy information monitoring device and method to accurately monitor and analyze data streams from the Android Automotive-based in-vehicle voice system, camera module, location services, and account system.

[0007] In a first aspect of the present invention, a Frida-based in-vehicle privacy information monitoring device is provided, the device comprising: The API monitoring module is deployed on the in-vehicle infotainment system under test to monitor the sensitive API call behavior of the in-vehicle applications of the in-vehicle infotainment system under test and generate monitoring data. The in-vehicle infotainment system under test is set to root mode and the firewall is turned off. The API monitoring module is equipped with a Frida hook module and an anti-debugging setting module. The Frida hook module is configured to dynamically instrument JAVA API and Native layer functions, and the anti-debugging setting module is enabled and the Frida thread is hidden. The Socket communication module includes a server and a client, which are connected via a communication link. The server is deployed on the in-vehicle infotainment system under test and creates a Socket port for sending monitoring data to the client. The client is deployed on the monitoring terminal for receiving monitoring data. An information display module, deployed on the monitoring terminal, is used to display sensitive API call behaviors based on the monitoring data.

[0008] In a second aspect of the present invention, a Frida-based in-vehicle privacy information monitoring method is proposed, which is executed based on the aforementioned Frida-based in-vehicle privacy information monitoring device; wherein, the method includes: The API monitoring module monitors the sensitive API call behavior of the in-vehicle applications of the in-vehicle infotainment system under test and generates monitoring data. The in-vehicle infotainment system under test is set to root mode and the firewall is turned off. The API monitoring module is equipped with a Frida hook module and an anti-debugging setting module. The Frida hook module is configured to dynamically instrument JAVA API and Native layer functions, and the anti-debugging setting module is enabled and the Frida thread is hidden. Monitoring data is sent from the server to the client via the Socket communication module deployed in the in-vehicle infotainment system under test. The monitoring data is received through a client of the Socket communication module deployed at the monitoring end; The information display module shows sensitive API call behaviors based on the monitoring data.

[0009] In a third aspect of the present invention, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement a Frida-based in-vehicle privacy information monitoring method.

[0010] In a fourth aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program that, when executed by a processor, implements a Frida-based in-vehicle privacy information monitoring method.

[0011] In a fifth aspect of the present invention, a computer program product is provided, the computer program product comprising a computer program that, when executed by a processor, implements a Frida-based in-vehicle privacy information monitoring method.

[0012] The Frida-based in-vehicle privacy information monitoring device and method proposed in this invention can adapt to the exclusive privacy data API interface characteristics of in-vehicle infotainment systems. It achieves accurate monitoring of sensitive APIs in the JAVA and Native layers of in-vehicle applications through Frida dynamic instrumentation technology, covering multi-dimensional privacy data of the vehicle and corresponding key data operations. Combined with anti-debugging design, it avoids the monitoring behavior being identified by in-vehicle applications. Furthermore, it realizes real-time transmission of monitoring data through a Socket communication module and visualizes it through a browser. It realizes dynamic monitoring of in-vehicle application privacy data streams and real-time recording of call behavior. Compared with existing static detection methods, it is more adaptable to complex in-vehicle environments and provides efficient and flexible technical protection for the compliance of in-vehicle privacy data. Attached Figure Description

[0013] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1 This is a schematic diagram of the architecture of an in-vehicle privacy information monitoring device based on Frida, according to an embodiment of the present invention.

[0015] Figure 2 This is a schematic diagram of the architecture of a Frida-based vehicle privacy information monitoring system according to a specific embodiment of the present invention.

[0016] Figure 3 This is a schematic diagram of a Frida-based vehicle privacy information monitoring method according to an embodiment of the present invention.

[0017] Figure 4 This is a schematic diagram of the data processing flow according to a specific embodiment of the present invention.

[0018] Figure 5 This is a schematic diagram of a computer device structure according to an embodiment of the present invention. Detailed Implementation

[0019] The principles and spirit of the invention will now be described with reference to several exemplary embodiments. It should be understood that these embodiments are given merely to enable those skilled in the art to better understand and implement the invention, and are not intended to limit the scope of the invention in any way. Rather, these embodiments are provided to make this disclosure more thorough and complete, and to fully convey the scope of this disclosure to those skilled in the art.

[0020] Those skilled in the art will recognize that embodiments of the present invention can be implemented as a system, apparatus, device, method, or computer program product. Therefore, this disclosure can be specifically implemented in the following forms: entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.

[0021] According to embodiments of the present invention, a Frida-based in-vehicle privacy information monitoring device and method are proposed, relating to the field of information monitoring technology. This invention constructs a Frida-based in-vehicle privacy information monitoring device and method to accurately monitor and analyze the data flow of the Android Automotive in-vehicle voice system, camera module, location service, and account system. In practical application scenarios, it monitors violations of regulations by different monitored objects; for the camera module, it detects whether images contain sensitive information such as faces and license plates; the voice system identifies unauthorized recording behavior; the location service verifies whether location information collection complies with the minimum necessary principle; and the account system audits for abuse of permissions by third-party applications. Privacy information monitoring is achieved through data flow monitoring and analysis.

[0022] In the embodiments of the present invention, the following terms need to be explained: Frida: A hooking and debugging framework based on Python and JS.

[0023] API: Application Programming Interface.

[0024] The principles and spirit of the present invention will be explained in detail below with reference to several representative embodiments.

[0025] Figure 1 This is a schematic diagram of the architecture of an in-vehicle privacy information monitoring device based on Frida, according to an embodiment of the present invention. Figure 1 As shown, the device includes: API monitoring module 110 is deployed on the in-vehicle infotainment system under test to monitor the sensitive API call behavior of the in-vehicle applications of the in-vehicle infotainment system under test and generate monitoring data. The in-vehicle infotainment system under test is set to root mode and the firewall is turned off. The API monitoring module 110 is equipped with a Frida hook module and an anti-debugging setting module. The Frida hook module is configured to dynamically instrument JAVA API and Native layer functions, and the anti-debugging setting module is enabled and the Frida thread is hidden. The Socket communication module 120 includes a server and a client, which are connected via a communication link. The server is deployed on the in-vehicle infotainment system under test and creates a Socket port for sending monitoring data to the client. The client is deployed on the monitoring terminal for receiving monitoring data. The information display module 130 is deployed on the monitoring terminal and is used to display sensitive API call behaviors based on the monitoring data.

[0026] To provide a clearer explanation of the Frida-based in-vehicle privacy information monitoring device, the following detailed description is provided in conjunction with embodiments.

[0027] In one embodiment, the API monitoring module 110 is also used to predefine a set of sensitive API methods and a set of sensitive data usage, read the package name and version number of all applications in the tested in-vehicle infotainment system, locate the monitoring methods and data transmission points, and collect API call information; A list of applications is generated based on the package name and version number of all applications. This list is used to provide users with a selection of target monitoring objects.

[0028] In one embodiment, the sensitive APIs in the set of sensitive API methods include APIs corresponding to vehicle data, user account data, in-vehicle camera services, in-vehicle microphone input, and vehicle location information. The sensitive data used in the set includes VIN code, vehicle speed, user list, current user, camera list, camera open, audio recording start, and vehicle location.

[0029] In one embodiment, the hook point of the Frida hook module is located on the sensitive API method set and the sensitive data usage set, and is used to collect monitoring data. The monitoring data includes at least the calling subject of the sensitive API, the API class name, the method name, and the sensitive API call information in the sensitive API method set and the sensitive data usage set.

[0030] In one embodiment, the server of the Socket communication module 120 is integrated with Frida Server, and the client is adapted to Frida Client. The server sends monitoring data of sensitive API calls in real time through the created Socket port, and the client receives the monitoring data through the corresponding Socket port and transmits it to the information display module 130.

[0031] In one embodiment, the information display module 130 is deployed in the browser of the monitoring terminal to display the sensitive API call behavior in a visual form. The displayed content includes at least the sensitive API call time, call frequency, and data operation content.

[0032] It should be noted that although several modules of the Frida-based in-vehicle privacy information monitoring device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of the present invention, the features and functions of two or more modules described above can be embodied in a single module. Conversely, the features and functions of a single module described above can be further divided and embodied by multiple modules.

[0033] In practical application scenarios, refer to Figure 2 This is a schematic diagram illustrating the architecture of a Frida-based vehicle privacy information monitoring system according to a specific embodiment of the present invention. Figure 2 As shown, the specific architecture includes: the monitored object, the API monitoring module, the Socket communication module, and the information display module. The monitored object is the normally deployed in-vehicle application on the tested in-vehicle infotainment system. The API monitoring module is responsible for monitoring the API interface behavior of the in-vehicle application, the Socket communication module is responsible for transmitting the monitored behavior, and the information display module is responsible for displaying the API interface behavior of the in-vehicle application.

[0034] The specific workflow is as follows: Set the in-vehicle infotainment system under test to root mode, use adb commands to set SELinux to permissive mode, and temporarily disable the SELinux firewall. Deploy the API monitoring module to the in-vehicle infotainment system under test, enable the anti-debugging settings module, hide the Frida thread, and bypass ptrace detection; In the API monitoring module, set the sensitive APIs of the monitored object and locate the monitoring methods; In the API monitoring module, set the data acquisition point for the monitored object and locate the monitoring data transmission point; Read the list of applications in the monitored object; The API monitoring module is responsible for monitoring Android system API call information, including the caller, API class name, and method name. Users can select any application from the list of monitored applications and use it normally. The Frida hook module within the API monitoring module performs Java API monitoring, and the Frida hook module also performs Native layer monitoring. Deploy the Socket communication module server to the in-vehicle infotainment system under test. The Socket communication module server is responsible for creating a Socket port and starting server communication. Deploy the Socket communication module client to the monitoring end, open the corresponding Socket port to receive data, and display the received data on the information display module of the browser.

[0035] Having described the apparatus according to exemplary embodiments of the present invention, the following references are made to... Figure 3 An exemplary embodiment of the present invention is described, which is a Frida-based in-vehicle privacy information monitoring method that is executed based on the aforementioned Frida-based in-vehicle privacy information monitoring device.

[0036] Based on the same inventive concept, this invention also proposes a method for monitoring in-vehicle privacy information based on Frida, such as... Figure 3 As shown, the method includes: S301, the API monitoring module monitors the sensitive API call behavior of the in-vehicle applications of the in-vehicle infotainment system under test and generates monitoring data; wherein, the in-vehicle infotainment system under test is set to root mode and the firewall is turned off, the API monitoring module is equipped with a Frida hook module and an anti-debugging setting module, the Frida hook module is configured to dynamically instrument JAVA API and Native layer functions, the anti-debugging setting module is turned on and the Frida thread is hidden; S302 sends monitoring data to the client through the server of the Socket communication module deployed in the tested vehicle infotainment system; S303 receives monitoring data through a client of the Socket communication module deployed at the monitoring end; S304, the information display module displays sensitive API call behaviors based on the monitoring data.

[0037] It should be noted that although the operation of the method of the present invention has been described in a specific order in the above embodiments and figures, this does not require or imply that the operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0038] refer to Figure 4 This is a schematic diagram of a data processing flow according to a specific embodiment of the present invention. Figure 4 As shown, the specific process is as follows: 1) Define a set of sensitive API methods X: In the API monitoring module, define a set of sensitive API methods X to be monitored. Sensitive APIs include vehicle data, user account data, in-vehicle camera service, in-vehicle microphone input, and vehicle location information; that is, X{car.hardware.property.CarPropertyManager, car.user.CarUserManager, car.media.CarCameraManager, car.media.CarAudioManager, location.Location}.

[0039] 2) Define the set Y for sensitive APIs: In the API monitoring module, the sensitive data to be monitored is defined using a set Y. The sensitive data includes VIN code, vehicle speed, user list, current user, camera list, camera open, audio recording start, and vehicle location; that is, Y{getVin, getVehicleSpeed, getAllUsers, getCurrentUser, getAvailableCarCameras, openCamera, startRecording, getLastKnownLocation}.

[0040] The API monitoring module reads the package names and version numbers of all applications in the in-vehicle infotainment system, allowing users to select the application to be tested.

[0041] 3) Use Frida for dynamic monitoring: Deploy the Frida framework and inject the Frida Server into the user-selected application process for testing within the in-vehicle infotainment system.

[0042] Frida's hook points are positioned on sets X and Y defined in the API monitoring module to monitor the calls made by the tested application to sensitive Android system APIs in sets X and Y.

[0043] Start the Socket communication module server and Socket communication module client, that is, start Frida Server and Frida Client to communicate.

[0044] 4) Does it call sensitive APIs? If so, record the sensitive API call behavior: When a user uses the application under test normally, the Socket communication module server records the calls of the application under test to sensitive Android system APIs in the X and Y sets, and sends the call information of sensitive Android system APIs to the Socket communication module client, which is then synchronously displayed on the information display module of the monitoring end browser.

[0045] This invention provides a Frida-based in-vehicle privacy information monitoring device and method compatible with the Android Automotive operating system (an operating system related to motor vehicles). Since in-vehicle applications run on the Android Automotive operating system, compared to mobile applications, Android Automotive defines different API interfaces for privacy data such as voice, camera, location, account, and vehicle data. The Frida API dynamic monitoring method used in this invention can monitor sensitive in-vehicle APIs and datasets, enabling dynamic monitoring of in-vehicle applications' use of vehicle data and real-time recording of their call behavior.

[0046] Based on the aforementioned inventive concept, such as Figure 5 As shown, the present invention also proposes a computer device 500, including a memory 510, a processor 520, and a computer program 530 stored in the memory 510 and executable on the processor 520. When the processor 520 executes the computer program 530, it implements the aforementioned Frida-based in-vehicle privacy information monitoring method.

[0047] Based on the aforementioned inventive concept, this invention proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned Frida-based in-vehicle privacy information monitoring method.

[0048] Based on the aforementioned inventive concept, this invention proposes a computer program product, which includes a computer program that, when executed by a processor, implements a Frida-based in-vehicle privacy information monitoring method.

[0049] The Frida-based in-vehicle privacy information monitoring device and method proposed in this invention can adapt to the exclusive privacy data API interface characteristics of in-vehicle infotainment systems. It achieves accurate monitoring of sensitive APIs in the JAVA and Native layers of in-vehicle applications through Frida dynamic instrumentation technology, covering multi-dimensional privacy data of the vehicle and corresponding key data operations. Combined with anti-debugging design, it avoids the monitoring behavior being identified by in-vehicle applications. Furthermore, it realizes real-time transmission of monitoring data through a Socket communication module and visualizes it through a browser. It realizes dynamic monitoring of in-vehicle application privacy data streams and real-time recording of call behavior. Compared with existing static detection methods, it is more adaptable to complex in-vehicle environments and provides efficient and flexible technical protection for the compliance of in-vehicle privacy data.

[0050] The acquisition, storage, use, and processing of data in this application comply with relevant laws and regulations.

[0051] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, apparatus, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0052] This invention is described with reference to flowchart illustrations and / or block diagrams of methods and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0053] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0054] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0055] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A Frida-based in-vehicle privacy information monitoring device, characterized in that, The device includes: The API monitoring module is deployed on the in-vehicle infotainment system under test to monitor the sensitive API call behavior of the in-vehicle applications of the in-vehicle infotainment system under test and generate monitoring data. The in-vehicle infotainment system under test is set to root mode and the firewall is turned off. The API monitoring module is equipped with a Frida hook module and an anti-debugging setting module. The Frida hook module is configured to dynamically instrument JAVA API and Native layer functions, and the anti-debugging setting module is enabled and the Frida thread is hidden. The Socket communication module includes a server and a client, which are connected via a communication link. The server is deployed on the in-vehicle infotainment system under test and creates a Socket port for sending monitoring data to the client. The client is deployed on the monitoring terminal for receiving monitoring data. An information display module, deployed on the monitoring terminal, is used to display sensitive API call behaviors based on the monitoring data.

2. The Frida-based vehicle privacy information monitoring device according to claim 1, characterized in that, The API monitoring module is also used to predefine a set of sensitive API methods and a set of sensitive data usage, read the package name and version number of all applications in the tested in-vehicle infotainment system, locate the monitoring methods and data transmission points, and collect API call information; A list of applications is generated based on the package name and version number of all applications. This list is used to provide users with a selection of target monitoring objects.

3. The Frida-based vehicle privacy information monitoring device according to claim 2, characterized in that, The sensitive APIs in the set of sensitive API methods include APIs corresponding to vehicle data, user account data, in-vehicle camera services, in-vehicle microphone input, and vehicle location information. The sensitive data used in the set includes VIN code, vehicle speed, user list, current user, camera list, camera open, audio recording start, and vehicle location.

4. The Frida-based vehicle privacy information monitoring device according to claim 1, characterized in that, The hook points of the Fridahoo module are located on the sensitive API method set and the sensitive data usage set, and are used to collect monitoring data. The monitoring data includes at least the calling subject of the sensitive API, the API class name, the method name, and the sensitive API call information in the sensitive API method set and the sensitive data usage set.

5. The Frida-based vehicle privacy information monitoring device according to claim 1, characterized in that, The server side of the Socket communication module is integrated with FridaServer, and the client side is adapted to FridaClient. The server side sends monitoring data of sensitive API calls in real time through the created Socket port, and the client side receives the monitoring data through the corresponding Socket port and transmits it to the information display module.

6. The Frida-based vehicle privacy information monitoring device according to claim 1, characterized in that, The information display module is deployed in the browser of the monitoring terminal and displays the sensitive API call behavior in a visual form. The displayed content includes at least the sensitive API call time, call frequency and data operation content.

7. A method for monitoring in-vehicle privacy information based on Frida, characterized in that, This method is performed based on the Frida-based in-vehicle privacy information monitoring device according to any one of claims 1 to 6; wherein the method includes: The API monitoring module monitors the sensitive API call behavior of the in-vehicle applications of the in-vehicle infotainment system under test and generates monitoring data. The in-vehicle infotainment system under test is set to root mode and the firewall is turned off. The API monitoring module is equipped with a Frida hook module and an anti-debugging setting module. The Frida hook module is configured to dynamically instrument JAVA API and Native layer functions, and the anti-debugging setting module is enabled and the Frida thread is hidden. Monitoring data is sent from the server to the client via the Socket communication module deployed in the in-vehicle infotainment system under test. The monitoring data is received through a client of the Socket communication module deployed at the monitoring end; The information display module shows sensitive API call behaviors based on the monitoring data.

8. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of claim 7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of claim 7.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method of claim 7.

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