A data security management method and device, electronic equipment and storage medium

Abstract

The application discloses a kind of data security management method, device, electronic equipment and storage medium, method includes: obtaining the information data to be managed, including sensitive data and conventional data;Sensitive data and conventional data are encrypted and stored to different servers, and regular backup is carried out;Sensitive information in information data is desensitized, and desensitized data is obtained;Based on desensitized data, execute target data analysis through pre-constructed sandbox environment, and obtain data analysis result;According to the authority range and control strategy of preestablished, data sharing platform is established based on server;In response to the data sharing request of authorized object, target data is shared to authorized object through the API interface of data sharing platform.The embodiment of the application provides significant beneficial effects in data security, privacy protection, data sharing and utilization efficiency, is suitable for various kinds of efficient, safe management and sharing data scene, can be widely applied in data processing technical field.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, and in particular to a data security management method and device, electronic equipment and storage medium. BACKGROUND

[0002] With the rapid development of information technology, data has become an important asset for enterprises and organizations. However, the management and sharing of data face many challenges, especially in terms of data security and privacy protection. Information data often contains sensitive data and regular data, such as personal identity information, financial information, etc. Once leaked, it may cause serious privacy invasion and economic loss. Although regular data does not involve sensitive information, its integrity and availability are also important.

[0003] Traditional data management methods often mix sensitive data and regular data, lack effective security measures, and are easy targets for attacks. In addition, during the data sharing process, there is a lack of fine-grained permission control, which may lead to unintentional leakage of sensitive information. SUMMARY

[0004] The main purpose of the embodiments of the present application is to propose a data security management method, device, electronic equipment and storage medium, in order to solve at least one problem of the prior art, and the present application can realize data security management.

[0005] To achieve the above-mentioned purpose, one aspect of an embodiment of the present application proposes a data security management method, the method comprising:

[0006] Obtaining information data to be managed; the information data includes sensitive data and regular data;

[0007] Encrypting and storing the sensitive data and regular data to different servers, and periodically backing up the data stored in the servers;

[0008] Based on the preset desensitization rule, desensitizing the sensitive information in the information data to obtain desensitized data;

[0009] Based on the desensitized data, executing target data analysis through a pre-constructed sandbox environment to obtain data analysis results;

[0010] Among them, the desensitized data and the data analysis results are stored in the server;

[0011] According to the preset permission range and control policy, a data sharing platform is established based on the server;

[0012] In response to a data sharing request of an authorized object, the target data is shared to the authorized object through the API interface of the data sharing platform.

[0013] In some embodiments, the sensitive data and the regular data are stored to different servers, including the following steps:

[0014] The sensitive data is stored to a local server; the data on the local server is encrypted using a preset encryption algorithm;

[0015] The regular data is stored to a cloud server; the data of the cloud server is encrypted and controlled using the security function of the cloud service provider.

[0016] In some embodiments, the server includes a local server and a cloud server; the data stored in the server is regularly backed up, including the following steps:

[0017] The data on the local server is regularly backed up based on a preset period, including full backup and incremental backup; the execution period of the incremental backup is longer than that of the full backup, and the backup data is stored in different physical locations of the local server compared to the data to be backed up;

[0018] The data on the cloud server is regularly backed up using the backup function of the cloud service provider, and the data recovery process of the cloud server is regularly tested; each backup copy obtained by different backup processing is stored in different physical locations of the cloud server.

[0019] In some embodiments, the sensitive information in the information data is desensitized based on a preset desensitization rule, including the following steps:

[0020] In response to a preset data element review rule, the sensitive information is marked in the information data;

[0021] The data type of the sensitive information includes a first type, a second type and a third type;

[0022] The first type of sensitive data is desensitized;

[0023] The second type of sensitive data is generalized;

[0024] The third type of sensitive data is strongly encrypted;

[0025] A desensitization mapping table is constructed according to the correspondence between the sensitive information and the desensitized data corresponding thereto.

[0026] In some embodiments, based on the desensitized data, the target data analysis is performed through a pre-constructed sandbox environment to obtain a data analysis result, including the following steps:

[0027] In response to a preset configuration requirement, a sandbox environment is created by configuring a target computing resource through network isolation;

[0028] The sandbox environment is integrated with an analysis algorithm to be executed.

[0029] The desensitized data is input into the sandbox environment, target data analysis is performed based on the analysis algorithm, and a data analysis result is output through the sandbox environment.

[0030] In some embodiments, a data sharing platform is established based on the server according to a preset permission range and control policy, including the following steps:

[0031] In response to the customization needs of the management object for the permission and range of data access, the sharing data range of the data sharing platform is determined;

[0032] The security and privacy settings of the data sharing platform are configured through the control policy;

[0033] The control policy includes an access control policy, a data encryption policy, and an audit log recording policy.

[0034] In some embodiments, in response to a data sharing request of an authorized object, the target data is shared to the authorized object through the API interface of the data sharing platform, including the following steps:

[0035] In response to the data sharing request of the authorized object, the data to be shared is determined;

[0036] The data to be shared is subjected to data cleaning processing to obtain data to be transmitted;

[0037] Based on a preset transmission layer security protocol, the data to be transmitted is encrypted and transmitted to the authorized object through the API interface of the data sharing platform to complete the data sharing.

[0038] To achieve the above-mentioned purpose, another aspect of the embodiment of the present application proposes a data security management device, the device comprises:

[0039] The first module is used for acquiring information data to be managed; the information data includes sensitive data and regular data;

[0040] The second module is used for encrypting and storing the sensitive data and the regular data to different servers, and periodically backing up the data stored by the servers;

[0041] The third module is used for performing desensitization operation on the sensitive information in the information data based on a preset desensitization rule to obtain desensitized data;

[0042] The fourth module is used for performing target data analysis based on the desensitized data through a pre-constructed sandbox environment to obtain a data analysis result;

[0043] The desensitized data and the data analysis result are stored in the server;

[0044] A fifth module is configured to establish a data sharing platform based on the server according to the preset authority range and control policy;

[0045] A sixth module is configured to share target data to an authorized object through an API interface of the data sharing platform in response to a data sharing request of the authorized object.

[0046] To achieve the above-mentioned purposes, another aspect of the embodiment of the present application provides an electronic device, which comprises a memory and a processor, the memory stores a computer program, and the processor implements the above-mentioned method when executing the computer program.

[0047] To achieve the above-mentioned purposes, another aspect of the embodiment of the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the above-mentioned method.

[0048] The present application provides a kind of data security management method, device, electronic equipment and storage medium, which obtains information data to be managed;Information data includes sensitive data and conventional data;Sensitive data and conventional data are encrypted and stored in different servers, and the data stored in server is backed up regularly;Based on the preset desensitization rule, sensitive information in information data is desensitized, and desensitized data is obtained;Based on desensitized data, target data analysis is executed through pre-constructed sandbox environment, and data analysis result is obtained;Desensitized data and data analysis result are stored in server;According to the preset authority range and control policy, data sharing platform is established based on server;In response to the data sharing request of authorized object, target data is shared to authorized object through the API interface of data sharing platform.The present application includes the following beneficial effects:

[0049] 1. Data security is improved: by encrypting sensitive data and conventional data and storing them in different servers, the risk of data leakage is effectively reduced, thereby improving the overall data security.

[0050] 2. Data backup: regularly backup the data stored in server to ensure quick recovery in case of data loss or damage, and protect the integrity and availability of data.

[0051] 3. Sensitive information desensitization: based on the preset desensitization rule, sensitive information is desensitized to generate desensitized data. Desensitized data retains data value while eliminating the risk of sensitive information leakage, suitable for data analysis, testing and other scenarios.

[0052] 4. Safe data analysis environment: target data analysis is executed through pre-constructed sandbox environment to ensure the safety and isolation of data analysis process, and prevent misoperation or leakage of original data during data analysis process.

[0053] 5. Data sharing controllability: based on the preset permission range and control strategy, a data sharing platform is established to ensure that only authorized objects can access specific data. Through the API interface, a flexible and controllable data sharing mechanism is provided to meet the access needs of different authorized objects.

[0054] 6. Improve data utilization efficiency: under the premise of ensuring data security, through the data sharing platform and desensitization data analysis, the utilization efficiency of data is improved, supporting enterprise decision-making, business innovation and other needs.

[0055] In summary, the embodiments of the present application provide significant benefits in terms of data security, privacy protection, data sharing and utilization efficiency, and are suitable for various scenarios that require efficient, secure management and sharing of data. BRIEF DESCRIPTION OF DRAWINGS

[0056] Figure 1 is a flowchart of the data security management method provided by the embodiments of the present application;

[0057] Figure 2 is a structural schematic diagram of the data security management device provided by the embodiments of the present application;

[0058] Figure 3 is a hardware structure schematic diagram of the electronic device provided by the embodiments of the present application. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical scheme and advantages of the present application clearer, the following will further describe the present application in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementation described in the following exemplary embodiments does not represent all the implementations consistent with the embodiments of the present application, but is only an example of devices and methods consistent with some aspects of the embodiments of the present application as described in the appended claims.

[0060] It can be understood that the terms "first", "second" and the like used in the present application can be used in the present application to describe various concepts, but unless specifically stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of the present application, the first information can also be referred to as the second information, and similarly, the second information can also be referred to as the first information. Depending on the context, the word "if" as used herein can be interpreted as "when" or "when" or "in response to determining".

[0061] The terms "at least one", "multiple", "each", "any", and the like, at least one includes one, two or more than two, multiple includes two or more than two, each refers to each of the corresponding plurality, and any refers to any one of the plurality.

[0062] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in the description of the application herein is for describing the embodiments of the application only and is not intended to be limiting of the application.

[0063] The data security management method provided by the embodiments of the application relates to the technical field of data processing. The data security management method provided by the embodiments of the application can be applied to a terminal, can be applied to a server, and can also be software running in the terminal or the server. In some embodiments, the terminal can be a smart phone, a tablet computer, a notebook computer, a desktop computer, a smart speaker, a smart watch, a vehicle-mounted terminal, and the like, but is not limited thereto. The server end can be configured as a stand-alone physical server, can be configured as a server cluster or a distributed system composed of multiple physical servers, can be configured as a cloud server providing basic cloud computing services such as cloud service, cloud database, cloud computing, cloud function, cloud storage, network service, cloud communication, middleware service, domain name service, security service, CDN, and big data and artificial intelligence platform, and the server can also be a node server in a blockchain network. The software can be an application that implements the data security management method, and the like, but is not limited to the above forms.

[0064] The application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld devices or portable devices, tablet devices, multi-processor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and the like. The application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, and the like that perform specific tasks or implement specific abstract data types. The application can also be practiced in a distributed computing environment, in which tasks are performed by remote processing devices connected by a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media, including storage devices.

[0065] Figure 1 The method in the optional flowchart of the data security management method provided by the embodiments of the application, Figure 1 may include but is not limited to steps S100 to S600.

[0066] S100, obtaining information data to be managed;

[0067] Among them, the information data includes sensitive data and regular data;

[0068] Exemplarily, in some embodiments, taking a vehicle as an example of the collection end of information data, data collection can be implemented as follows:

[0069] S11, extracting personal information:

[0070] Operation: The system extracts the basic information of the vehicle owner and driving habit data from the vehicle management system.

[0071] According to the preset data collection requirements, access the information system and sensors of the vehicle, and extract the corresponding data.

[0072] The extracted data includes:

[0073] Owner Information: including name, contact information, driving license information, etc., for identifying and contacting the owner.

[0074] Driving Habits Data: including driving speed, acceleration, brake frequency, etc., for analyzing driving behavior.

[0075] Vehicle Usage Data: including driving mileage, maintenance record, fuel consumption, etc., for evaluating vehicle performance and maintenance needs.

[0076] S12, extracting environmental detection information:

[0077] Operation: The system extracts data such as temperature, humidity, and air quality of the driving environment from the vehicle's environmental monitoring system.

[0078] The extracted data includes:

[0079] Environmental Parameters: including temperature, humidity, air quality index, etc., for evaluating the vehicle driving environment.

[0080] S200, encrypting sensitive data and regular data and storing them in different servers, and regularly backing up the data stored in the servers;

[0081] It should be noted that in some embodiments, storing sensitive data and regular data in different servers can include the following steps: storing sensitive data in a local server; using a preset encryption algorithm to encrypt the data on the local server; storing regular data in a cloud server; using the security features of the cloud service provider to encrypt the data on the cloud server.

[0082] For example, in some specific embodiments, taking the application scenario of the vehicle information data mentioned above as an example, data storage can be implemented as follows:

[0083] The system first classifies the collected data and identifies which data contains sensitive information, such as the personal information and driving habits of the vehicle owner, and which data is regular environmental monitoring information.

[0084] For data containing sensitive information, the system will choose to store it on a local server to better control physical access and encryption measures. For example, the personal information and driving habit data of the vehicle owner will be stored on the company's internal secure servers, which are located in a controlled data center and have 24 / 7 monitoring and access log recording.

[0085] For regular environmental monitoring information, the system may choose to store it on a cloud server, as this data usually does not require frequent physical access, and cloud service providers usually provide high availability and scalability storage solutions. For example, temperature, humidity, and air quality data of the vehicle driving environment will be uploaded to the storage buckets of the cloud service provider, which are located in different geographical locations to ensure data redundancy and fast access.

[0086] Specifically, corresponding security measures can be implemented for different servers, which can be implemented as follows:

[0087] For sensitive data stored in a local server, the system will use the SM4 encryption algorithm to encrypt the data, ensuring that even if the data is accessed illegally, it cannot be interpreted. At the same time, the system will set strict access control, only authorized employees can access these data, and all access attempts will be recorded and monitored.

[0088] For data stored in a cloud server, the system will use the security features of the cloud service provider, such as storage bucket encryption and access policies, to ensure that only authorized applications and services can access the data. In addition, the system will regularly conduct security audits on the cloud storage buckets to check for unauthorized access attempts or configuration errors.

[0089] It should be noted that the server includes a local server and a cloud server; in some embodiments, the data stored in the server is periodically backed up, which can include the following steps: periodically performing full backup and incremental backup on the data on the local server based on a preset period; wherein the execution period of the incremental backup is longer than that of the full backup, and the backup data is stored in a different physical location of the local server than the data being backed up; using the backup function of the cloud service provider to periodically backup the data on the cloud server, and periodically testing the data recovery process of the cloud server; wherein each backup copy obtained by different backup processing is stored in a different physical location of the cloud server.

[0090] Exemplarily, in some specific embodiments, the data backup of the server can be implemented as follows:

[0091] For the data on the local server, the system will perform a full backup once a day and incremental backups every week and every month. The backup data will be stored in different physical locations to prevent catastrophic events from the original storage location. For example, daily backups will be replicated to another data center, while monthly backups are stored in an offline secure location.

[0092] For the data stored in the cloud, the system will use the backup function of the cloud service provider to ensure that multiple copies of the data are stored in different geographic locations. The system will also periodically test the recovery process to ensure that data can be quickly recovered in the event of data loss or damage.

[0093] S300, based on the preset desensitization rule, desensitizing the sensitive information in the information data to obtain desensitized data;

[0094] It should be noted that in some embodiments, based on the preset desensitization rule for desensitizing sensitive information in the information data, the following steps can be included: in response to the preset data element review rule, mark the sensitive information in the information data; wherein the data type of the sensitive information includes a first type, a second type and a third type; desensitizing the first type of sensitive data; generalizing the second type of sensitive data; strongly encrypting the third type of sensitive data; and constructing a desensitization mapping table according to the correspondence between the sensitive information and the desensitized data obtained therefrom.

[0095] Exemplarily, in some specific embodiments, taking the application scenario of the information data of the vehicle as an example, the definition of the desensitization rule can be implemented as follows:

[0096] Operation: The system first conducts a review of information data related to security and privacy regulations to determine which data elements are considered sensitive information. For example, according to the General Data Protection Regulation, personal identifiable information (PII) needs to be de-identified. In the scenario of GPS data, the system will develop a set of rules that specify which information must be replaced (generalization, such as latitude and longitude information such as route) or encrypted (i.e. strong encryption processing). Among them, when performing de-identification operation, the system will keep a mapping table to track the correspondence between the original data and the de-identified data, but this mapping table will be strictly protected and only authorized data management personnel can access it.

[0097] S400, based on the de-identified data, performing target data analysis through a pre-built sandbox environment to obtain a data analysis result;

[0098] Among them, the de-identified data and the data analysis result are stored in the server.

[0099] It should be noted that in some embodiments, based on the de-identified data, the target data analysis is performed through a pre-built sandbox environment to obtain a data analysis result, which can include the following steps: in response to a pre-set configuration requirement, a sandbox environment is created by configuring a target computing resource through network isolation; wherein the sandbox environment integrates the analysis algorithm to be executed; the de-identified data is input into the sandbox environment, the target data analysis is performed based on the analysis algorithm, and the data analysis result is output through the sandbox environment.

[0100] Illustratively, in some specific embodiments, taking the aforementioned application scenario of vehicle information data as an example, first, a virtual sandbox environment is created, the required computing resources are configured and network isolation is implemented to ensure that it is completely isolated from the external network. Next, the analysis algorithm to be executed (such as the route optimization algorithm) is integrated into the sandbox, and these algorithms are strictly reviewed to ensure that they meet the security standards and privacy protection requirements. Subsequently, the system inputs the de-identified data (such as GPS trajectory) into the sandbox environment, which has been de-identified before entering the sandbox to reduce privacy risks. In the sandbox, the system performs data analysis using technologies such as multi-party secure computation (MPC) and federated learning (FL), and the calculation process is performed within the sandbox, all operations are monitored and recorded to ensure that there is no data leakage. After the calculation is completed, the sandbox environment will output the analysis result, such as the optimized driving route, and at this time all original data and intermediate calculation results are completely cleared to prevent data leakage.

[0101] S500, according to the pre-set permission range and control policy, establishing a data sharing platform based on the server;

[0102] It should be noted that in some embodiments, based on the server to establish a data sharing platform, according to the preset permission range and control strategy, can include the following steps: in response to the customization needs of the management object for the permission and range of data access, determine the shared data range of the data sharing platform; configure the security and privacy settings of the data sharing platform through the control strategy; wherein the control strategy includes access control strategy, data encryption strategy and audit log recording strategy.

[0103] Exemplarily, in some specific embodiments, taking the application scenario of the vehicle information data as an example, the data sharing platform can realize the following:

[0104] S51, establish a data sharing platform:

[0105] The system establishes a data sharing platform, providing API interfaces for external modules to access data services. The design of this platform aims to realize the modularization of data services, allowing users to customize data access permissions and ranges according to their needs. For example, through this platform, desensitized GPS data and other related data (such as driving habit data and environmental monitoring information) can be safely provided to authorized partners and research institutions.

[0106] S52, ensure data security:

[0107] The system ensures the security and privacy of data on the sharing platform through measures such as access control, data encryption and audit log recording. In order to prevent data leakage, the system will conduct strict security checks on shared data to ensure that all shared data comply with privacy regulations and privacy protection requirements. At the same time, all transmitted data will be encrypted before transmission to ensure security during the sharing process.

[0108] S600, in response to the data sharing request of the authorized object, the target data is shared to the authorized object through the API interface of the data sharing platform.

[0109] It should be noted that in some embodiments, in response to the data sharing request of the authorized object, the target data is shared to the authorized object through the API interface of the data sharing platform, which can include the following steps: in response to the data sharing request of the authorized object, determine the data to be shared; perform data cleaning processing on the data to be shared to obtain the data to be transmitted; based on the preset transmission layer security protocol, the data to be transmitted is encrypted and transmitted to the authorized object through the API interface of the data sharing platform to complete the data sharing.

[0110] Exemplarily, in some specific embodiments, taking the application scenario of the vehicle information data as an example, the data sharing can be realized as follows:

[0111] S61, realize the data sharing mechanism:

[0112] The system enables data sharing through an API interface, ensuring security during the sharing process. Specifically, the system will implement data access control measures to ensure that only authorized users can access specific data. At the same time, all shared data transmission will use encryption technology to prevent data from being stolen or tampered with during transmission. In addition, the system will also record audit logs to track data access and usage, ensuring transparency and compliance.

[0113] S62, sharing data with partners:

[0114] The system will share the desensitized data with partners, research institutions or government departments for analysis and decision support. These data will include desensitized, sandboxed GPS route data and related driving behavior data, ensuring that these data meet privacy regulations and privacy protection requirements when shared. In this way, partners and research institutions can use data for in-depth analysis and research without revealing personal privacy, thereby supporting policy-making and business decision-making.

[0115] To explain the principle of the technical solution of the present application in detail, the overall process of the present application will be described below in conjunction with some specific embodiments. It should be easily understood that the following is an explanation of the technical principle of the present application and cannot be regarded as a limitation of the present application.

[0116] First of all, it needs to be pointed out that the existing data management system mainly focuses on data storage, processing and sharing, but there are deficiencies in data security and privacy protection. Especially in the field of automobiles, with the development of Internet of Vehicles technology, a large amount of personal information and environmental detection information is collected and used, and the security and privacy of these data have become a problem to be solved.

[0117] Although the current technology can desensitize and sandbox data, it is still not enough in terms of data security and authentication during transmission, storage and processing, and there is a risk of data leakage and unauthorized access. Although there is data desensitization technology, it is still a difficult problem to ensure privacy protection in complex data processing scenarios, especially when data is shared and applied across platforms. The existing data management system is usually not flexible and extensible enough, and it is difficult to keep up with the changing business needs and technological progress. While the existing data sharing platform can achieve "data available but invisible", sometimes it sacrifices the efficiency of sharing and utilization, resulting in the value of data not being fully utilized. The current technology is mostly isolated, lacking a comprehensive solution to solve the problems of secure storage, privacy protection, sharing and utilization of data.

[0118] In view of this, the present application proposes a data management scheme with invisible data availability. By integrating and optimizing existing technologies, the present application aims to provide a more secure and efficient data management scheme, particularly in the safe storage and sharing of personal information and environmental detection information in the automotive field. In this way, the present application not only inherits the advantages of existing technologies, but also improves and innovates on the shortcomings of existing technologies to better adapt to the needs of data security and privacy protection.

[0119] In some specific application scenarios, the embodiments of the present application can be implemented through the following flow steps:

[0120] S1, data collection:

[0121] S11, extracting personal information:

[0122] Operation: The system extracts the basic information and driving habit data of the vehicle owner from the vehicle management system.

[0123] According to the preset data collection requirements, access the information system and sensors of the vehicle to extract the corresponding data.

[0124] The extracted data includes:

[0125] Owner Information: including name, contact information, driving license information, etc., used to identify and contact the owner.

[0126] Driving Habits Data: including driving speed, acceleration, brake frequency, etc., used to analyze driving behavior.

[0127] Vehicle Usage Data: including driving mileage, maintenance records, fuel consumption, etc., used to evaluate vehicle performance and maintenance needs.

[0128] S12, extracting environmental detection information:

[0129] Operation: The system extracts data such as temperature, humidity, and air quality of the driving environment from the vehicle's environmental monitoring system.

[0130] The extracted data includes:

[0131] Environmental Parameters: including temperature, humidity, air quality index, etc., used to evaluate the vehicle driving environment.

[0132] S2, data storage:

[0133] S21, determining the storage location:

[0134] The system first classifies the collected data, identifying which data contains sensitive information, such as the owner's personal information and driving habits, and which data is regular environmental monitoring information.

[0135] For data containing sensitive information, the system will choose to store it on local servers to better control physical access and encryption measures. For example, the owner's personal information and driving habits data will be stored on secure servers within the company, which are located in controlled data centers and have 24 / 7 monitoring and access log records.

[0136] For regular environmental monitoring information, the system may choose to store it on cloud servers, as these data usually do not require frequent physical access, and cloud service providers usually provide high availability and scalability storage solutions. For example, temperature, humidity and air quality data of the vehicle driving environment will be uploaded to the storage buckets of cloud service providers, which are located in different geographical locations to ensure data redundancy and fast access.

[0137] S22, implement security measures:

[0138] For sensitive data stored on local servers, the system will use the SM4 encryption algorithm to encrypt the data, ensuring that even if the data is accessed illegally, it cannot be read. At the same time, the system will set strict access control, only authorized employees can access these data, and all access attempts will be recorded and monitored.

[0139] For data stored in cloud servers, the system will use the security features of cloud service providers, such as bucket encryption and access policies, to ensure that only authorized applications and services can access the data. In addition, the system will regularly conduct security audits on cloud storage buckets to check for unauthorized access attempts or configuration errors.

[0140] S23, regular backup:

[0141] For data on local servers, the system will perform a full backup every day and incremental backups every week and month. Backup data will be stored in different physical locations to prevent catastrophic events from the original storage location. For example, daily backups will be copied to another data center, while monthly backups will be stored in an offline secure location.

[0142] For cloud-stored data, the system will use the backup features of cloud service providers to ensure that multiple copies of data are stored in different geographical locations. The system will also regularly test the recovery process to ensure that data can be quickly recovered in the event of data loss or damage.

[0143] S3, data desensitization:

[0144] S31, define desensitization rules:

[0145] Operation: The system first conducts a review of information data-related security privacy regulations to determine which data elements are considered sensitive information. For example, according to the General Data Protection Regulation, personal identity information (PII) needs to be desensitized. In the scenario of GPS data, the system will develop a set of rules that specify which information must be replaced or encrypted.

[0146] For GPS route data, the system may decide to generalize specific latitude and longitude coordinates, replacing specific values with a range. For example, the latitude and longitude of a certain location "39.9042°N, 116.4074°E" can be represented as "near the center of Beijing" or "from one area to another" to describe the route from point A to point B.

[0147] It should be noted that generalization refers to replacing specific data with broader categories or ranges to reduce the accuracy of the data while still retaining its analytical value. The purpose of generalization is to reduce the identification ability of the data so that it cannot be traced back to an individual.

[0148] Desensitization refers to processing sensitive data so that it cannot identify the original information without changing the data format or structure. The purpose of desensitization is to protect the privacy and security of data and prevent personal identity from being identified when data is leaked.

[0149] Adjusting the desensitization strategy in the question is generally aimed at encrypting user personal identity, such as replacing the real name with a random ID 12345, making it difficult to develop a desensitization strategy.

[0150] The generalization strategy can be changed according to different needs. The specific degree of generalization can be defined according to the sensitivity of the data, the use scenario, the analysis requirement, and the requirement of the relevant regulations.

[0151] For example: How many people in the center of Beijing may need to buy a certain insurance? For this example question, for the customer population, the target customer can be generalized to "35-50 year-old middle and high income population in Beijing".

[0152] For areas near the city center, a central point (such as Tiananmen Square, Wangfujing, etc.) can be chosen as the city center, and a radius (such as 3 km, 5 km, or 10 km) can be set to define the scope of "nearby". Several districts around the city center can also be chosen as the scope, such as Dongcheng District, Xicheng District, Chaoyang District, Haidian District, etc. These districts are generally considered to be "near the center". Areas with high population density near the city center can be chosen, which are usually mixed commercial and residential areas, and can use census data or geographic information system (GIS) data to define.

[0153] The degree of generalization is determined by the needs, taking into account factors such as analysis cost, existing data sources, target customer groups, market environment, etc.

[0154] Maintain flexibility during analysis, dynamically adjust the scope based on preliminary analysis results and market feedback, and provide the degree of generalization after generalization to the demand side for selection, such as choosing a radius of how many kilometers or choosing Dongcheng District, Xicheng District, or choosing which part of the high-density population area.

[0155] Develop different generalization strategies according to different scenarios and needs: such as a user tends to buy a certain brand of notebook computer, different generalization strategies can be developed according to different needs. There may be the following needs:

[0156] ① Find the potential customer group of keyboard and mouse:

[0157] Generalization strategy:

[0158] Purchase preference description: Replace the specific purchase record "user bought a certain brand of mechanical keyboard and wireless mouse in 2023" with "a user has purchased multiple peripheral products in the past year".

[0159] Behavioral data: Aggregate behavior data, such as "user viewed 10 keyboard and mouse products in the past three months" to "a user viewed multiple peripheral products in the past three months".

[0160] ② Find the potential customer group of a certain brand:

[0161] Generalization strategy:

[0162] Purchase preference description: Replace the specific preference description "user has strong interest in a certain brand of notebook computer" with "potential customer group shows interest in a certain brand of notebook computer".

[0163] ③ Find users interested in notebook computers with a specific price range (such as 5000-8000 yuan):

[0164] Generalization strategy:

[0165] Price Range Description: Generalize specific price descriptions, e.g., "User B viewed a laptop priced at 6000 yuan" is replaced with "Customer B showed interest in laptops priced between 5000-8000 yuan."

[0166] For data that needs to be encrypted, the system will use strong encryption standards, such as AES-256, to encrypt the data. For example, if the system stores detailed information about a specific driving route, this information will be encrypted into an unreadable string before being stored. Only authorized personnel with the correct key can decrypt and view it.

[0167] Specific example: If the system records the driving trajectory of a vehicle: the trajectory shows that the owner drives from "a street in Chaoyang District, Beijing" to "a street in Haidian District, Beijing". According to the desensitization rules, the system can replace "a street in Chaoyang District" with "Chaoyang District" or "a commercial area", and "a street in Haidian District" with "Haidian District" or "near a school". After processing, the data can still be used for analysis, but the specific geographic location cannot be identified.

[0168] S32, execute desensitization operation:

[0169] When performing desensitization operations, the system will maintain a mapping table to track the correspondence between original data and desensitized data, but this mapping table will be strictly protected and only authorized data management personnel can access it. In this way, desensitized data can still be used for analysis and research, while ensuring the protection of personal privacy. For example, researchers can use processed GPS data to analyze traffic flow without specifically pointing to any individual or specific location.

[0170] Formulation basis:

[0171] The formulation of desensitization rules needs to consider data types, use purposes and industry standards to ensure that data can be effectively used and strictly protect personal privacy. For example, when processing market research data, it is required to strictly protect personal data according to relevant privacy regulations. The data used at this time includes consumer survey data such as age, gender, income level and purchase preferences, and the purpose of use is to analyze market trends to develop relevant marketing strategies.

[0172] Specific standards:

[0173] Different types of data have different sensitivities. They should be classified according to their nature (such as personal identity information, financial information, health records, etc.), and corresponding desensitization rules should be formulated. For example, personal identity information needs more stringent desensitization processing, while general market survey data can be moderately generalized. Considering the storage and presentation form of data, such as text, numerical value, image, etc., formulate data processing specifications for different formats. For example, replace characters for text data, and range generalization for numerical value data.

[0174] S4, Sandbox Computing:

[0175] First, the system creates a virtual sandbox environment, configures the required computing resources and implements network isolation to ensure that it is completely isolated from the external network. Next, the analysis algorithms to be executed (such as route optimization algorithms) are integrated into the sandbox, and these algorithms are strictly reviewed to ensure that they meet security standards and privacy protection requirements. Subsequently, the system inputs the desensitized data (such as GPS trajectories) into the sandbox environment, which has been desensitized before entering the sandbox to reduce privacy risks. In the sandbox, the system uses technologies such as multi-party secure computing (MPC) and federated learning (FL) to perform data analysis, and the calculation process is carried out within the sandbox, all operations are monitored and recorded to ensure that there is no data leakage. After the calculation is completed, the sandbox environment will output the analysis results, such as the optimized driving route, and at this time all original data and intermediate calculation results are completely cleared to prevent data leakage.

[0176] Algorithm Review:

[0177] 1.1 Security Review:

[0178] Code Review: Perform static analysis on the implementation code of the algorithm to check for security vulnerabilities (such as buffer overflow, SQL injection, etc.).

[0179] Dependency Library Review: Check the third-party libraries and modules that the algorithm depends on to confirm that they have no known security vulnerabilities and ensure that the version used is the latest.

[0180] 1.2 Privacy Protection Performance:

[0181] Data Desensitization Verification: Confirm that the input desensitized data meets the privacy protection requirements, ensuring that the original information cannot be recovered during processing.

[0182] Privacy Protection Mechanism: Review whether the algorithm embeds privacy protection technologies (such as differential privacy, encryption technology, etc.), and evaluate its ability to protect personal privacy in the output results.

[0183] 1.3 Performance Evaluation:

[0184] Efficiency Testing: Evaluate the algorithm's running efficiency in a sandbox environment, ensuring it completes computational tasks within a reasonable time.

[0185] Resource Consumption Analysis: Analyze the algorithm's use of computational resources, confirming it does not excessively consume resources during computation.

[0186] 1.4 Compliance Review:

[0187] Compliance Check: Ensure the algorithm adheres to relevant regulations (such as GDPR, PIPL, etc.) and industry standards, particularly in data handling and privacy protection.

[0188] 2. Review Criteria:

[0189] Security Standards: Comply with industry standards (such as OWASP, NIST, etc.) and the organization's internal security policies.

[0190] Privacy Protection Standards: Ensure that privacy protection measures adopted meet industry best practices, effectively preventing data breaches and personal identification.

[0191] Performance Standards: The algorithm's running time and resource consumption should be within acceptable ranges, typically evaluated according to the organization's defined benchmarks.

[0192] Compliance Standards: Ensure the algorithm and processing flow comply with applicable regulations and standards, and that appropriate regulations are followed when handling personal data.

[0193] 3. Review Process

[0194] Application Submission: The development team submits an algorithm review application, accompanied by algorithm documentation and relevant code.

[0195] Initial Assessment: The review team conducts an initial assessment to confirm the completeness of the application materials and performs a preliminary code review.

[0196] Detailed Review:

[0197] Conduct a detailed analysis of the code, security, privacy protection performance, and compliance.

[0198] Implement a combination of automated tools and manual checks.

[0199] Review Report: The review team writes a review report summarizing the review results, pointing out existing problems and improvement suggestions.

[0200] Feedback and Correction: Feedback the review report to the development team, requiring them to make corrections based on the suggestions and then resubmit the review.

[0201] Final Review: After the modified algorithm passes the final review, confirming it meets all standards, it can be released for execution in a sandbox environment.

[0202] 4. Handling Measures for Non-compliance:

[0203] Problem Record: The review team records the reasons for non-compliance and existing problems and forms a problem list.

[0204] Feedback Mechanism: Provide detailed review results to the development team, offer improvement suggestions and repair guidance.

[0205] Re-review Requirement: Require the development team to resubmit the review application after fixing all problems and re-enter the review process.

[0206] Temporary Disable: Temporarily disable algorithms that do not meet safety and privacy protection standards and cannot run in a sandbox environment.

[0207] Risk Assessment: If the algorithm is non-compliant and poses potential risks, conduct a risk assessment and take necessary remedial measures, such as data cleaning, additional security controls, etc.

[0208] Data Optimization Algorithm:

[0209] 1.1 Data Privacy Protection:

[0210] Input Data Review:

[0211] Ensure that the input GPS data has been desensitized, deleting or encrypting users' personal identity information (PII) such as name, address, mobile phone number, etc.

[0212] Verify that desensitized data can prevent user identity recovery, i.e., ensure that data cannot be traced back to a specific user.

[0213] Output Data Review:

[0214] Review the output of the algorithm to ensure that it does not contain any personal information or sensitive data. If geographic information needs to be included in the output, it should be generalized to a wider area description (e.g., "from Area A to Area B") instead of a specific address.

[0215] 1.2 Algorithm Privacy Protection Mechanism:

[0216] Privacy Protection Technology:

[0217] Review whether the algorithm integrates privacy protection technologies such as differential privacy (Differential Privacy) and homomorphic encryption (Homomorphic Encryption) to prevent the disclosure of user location information during data processing.

[0218] Then, according to the examination standards and examination procedures, the user's privacy can be effectively protected, and sensitive information will not be leaked during data analysis and processing.

[0219] During the examination process, the user's privacy needs to be protected:

[0220] Data minimization principle: Only collect and use necessary data during processing, avoid excessive exposure of user information.

[0221] Data de-identification: Ensure that data is de-identified during storage and processing, eliminating the ability to identify users.

[0222] User consent: Ensure that the user's explicit consent is obtained before collecting and processing user data, and provide transparent information about the purpose and scope of data use.

[0223] Audit and monitoring: Implement monitoring during algorithm execution, record all operations for subsequent audit and problem tracking.

[0224] S5, data sharing platform:

[0225] S51, establish a data sharing platform:

[0226] The system establishes a data sharing platform, providing API interfaces for external modules to access data services. The design of this platform aims to achieve modularized services of data, allowing users to customize data access permissions and scope according to their needs. For example, through this platform, desensitized GPS data and other related data (such as driving habit data and environmental monitoring information) can be safely provided to authorized partners and research institutions.

[0227] S52, ensure data security:

[0228] The system ensures the security and privacy of data on the sharing platform through measures such as access control, data encryption and audit log recording. In order to prevent data leakage, the system will conduct strict security checks on shared data to ensure that all shared data meet relevant privacy regulations and privacy protection requirements. At the same time, all transmitted data will be encrypted before transmission to ensure security during sharing.

[0229] The system ensures data security and privacy by implementing access control, data encryption, and audit logging. In terms of encryption, according to FIPS140-2 / 3 (Federal Information Processing Standard) and ISO / IEC 27001 (Information Security Management Standard published by the International Organization for Standardization), encryption algorithms such as AES, RC4, ECC, etc. can be used to encrypt transmitted data. At the same time, during the transmission of data, TLS (Transport Layer Security) and VPN (Virtual Private Network) are used for data transmission to ensure that data is encrypted during network transmission and prevent man-in-the-middle attacks.

[0230] In terms of access control policy, the following two strategies can be adopted:

[0231] Role-Based Access Control (RBAC): Assign permissions based on user roles to ensure that only authorized users can access sensitive data. For example, administrators can access all data, while ordinary users can only access data required for their work.

[0232] Attribute-Based Access Control (ABAC): Use user attributes, resource attributes, and environmental conditions (such as time, location) to dynamically decide permissions, providing more granular control. Throughout the process, the principle of least privilege is followed: users and systems only obtain the minimum permissions required to complete tasks to reduce potential security risks.

[0233] In terms of access control mechanisms, identity verification and permission review are used to ensure the security of data access:

[0234] Identity verification: Use multi-factor authentication (MFA) such as password, SMS verification code or biometric technology to ensure the authenticity of user identity.

[0235] Permission review: Regularly review user permissions to ensure that data no longer needed for access is promptly withdrawn.

[0236] In terms of audit logging, the recorded content includes:

[0237] User activity log: Records user login / logout time, accessed data, performed operations, modified records, etc.

[0238] System event log: Records system security events such as permission changes, abnormal access attempts, data sharing, etc.

[0239] Data access log: Details who accessed which data at what time, including access request source IP address, etc.

[0240] Query methods include:

[0241] Centralized Log Management: Use centralized log management systems (such as ELK Stack, Splunk, etc.) to facilitate the storage, search, and analysis of logs.

[0242] Real-time Monitoring and Alerting: The system should have real-time monitoring capabilities and automatically trigger alerts for abnormal access behavior, prompting security administrators to investigate.

[0243] Regular Auditing: Regularly generate audit reports to analyze access patterns and potential security threats, ensuring the integrity and accuracy of logs.

[0244] S6、Data Sharing Process:

[0245] During the data sharing process, ensuring the security and compliance of data is crucial. The following is a detailed process for data sharing, including data preparation, transmission methods, allocation and management of access rights, and the regulations and restrictions that partners should follow when receiving and using data.

[0246] S61、Data Sharing Mechanism Implementation:

[0247] Data Preparation:

[0248] De-sensitization: Ensure that all data to be shared has been de-sensitized. For GPS route data and driving behavior data, remove or encrypt personal identifiable information (PII) such as names, contact information, and specific addresses, and replace them with more general descriptions.

[0249] Data Cleaning: Before sharing, clean the data to ensure its accuracy and integrity, and delete invalid or redundant data records.

[0250] Data Formatting: Convert data into a standard format (such as CSV, JSON, etc.) for easy transmission and analysis.

[0251] Transmission Methods:

[0252] API Interface: Use a secure API interface for data transmission to ensure the security of data requests and responses.

[0253] Encryption Technology: Use TLS (Transport Layer Security) to encrypt all data during transmission to prevent theft or tampering during transmission.

[0254] Allocation and Management of Access Rights:

[0255] Permission Management: Implement role-based access control (RBAC) or attribute-based access control (ABAC) based on user roles and needs to ensure that only authorized users can access specific data.

[0256] Examples of Role-Based Access Control:

[0257] ① For Research Institutions:

[0258] Roles: Researcher, Project Manager, Data Analyst.

[0259] Access Rights:

[0260] Researcher: Can access de-identified datasets for research and analysis, prohibited from accessing any Personally Identifiable Information (PII).

[0261] Project Manager: Can access project-related data and analysis results, view overall data usage.

[0262] Data Analyst: Can access detailed analysis tools and data reports, but cannot modify raw data or access unprocessed sensitive data.

[0263] ② For Business Partners:

[0264] Roles: Market Manager, Sales Representative.

[0265] Access Rights:

[0266] Market Manager: Can access market research and consumer behavior data to help develop market strategies.

[0267] Sales Representative: Can access aggregated data related to sales, but cannot view detailed purchase records of users.

[0268] Examples of Attribute-Based Access Control:

[0269] ① Partner Attribute Definitions:

[0270] User Attributes:

[0271] Identity: Identity information of the partner (e.g., "Researcher of a certain research institution").

[0272] Role: Specific role of the user (e.g., "Project Manager" or "Data Analyst").

[0273] Authentication Status: Whether the user has been authenticated (e.g., MFA authentication).

[0274] Resource Attributes:

[0275] Data Type: Shared data types (e.g., "De-identified GPS Data", "Driving Behavior Data").

[0276] Data Sensitivity: Sensitivity level of the data (e.g., "Low Sensitivity", "High Sensitivity").

[0277] Environmental Conditions:

[0278] Time: The time at which the user accesses the data (e.g., work hours or non-work hours).

[0279] Location: The physical location of the user (e.g., a specific network environment or VPN access).

[0280] ② Permission decision process:

[0281] Dynamic decision: Based on the user's attributes, the requested resource attributes, and the current environmental conditions, dynamically decide whether the user has the right to access specific data. For example:

[0282] If the user is a "researcher" and the requested data is "desensitized GPS data", and the request occurs during work hours, access is allowed.

[0283] If the user attempts to access data outside of work hours, the request is denied.

[0284] User authentication: Implement multi-factor authentication (MFA) to ensure the authenticity of the identity of the user requesting access to the data.

[0285] Regular review: Regularly review and update access permissions to ensure that data no longer needed for access is timely withdrawn.

[0286] S62, share data with partners:

[0287] ① Partner selection:

[0288] Screening partners: Ensure that partners sharing data (such as research institutions, government departments, etc.) have legal and compliance, and can comply with relevant requirements for data privacy protection.

[0289] ② Regulations and restrictions on receiving and using data:

[0290] Compliance commitment: Partners receiving data must sign a confidentiality agreement and data use agreement, clearly stating the privacy regulations and privacy protection requirements they must follow when using data.

[0291] Purpose of use: Partners can only use shared data for specific analysis and decision support, and are strictly prohibited from using data for other unauthorized purposes.

[0292] Restrictions on data re-sharing: Partners may not share the received data with third parties unless authorized by the data provider.

[0293] Data storage and destruction: After using the data, the partner should store the data securely according to the agreement and completely destroy it according to the regulations when it is no longer needed.

[0294] Audit and Monitoring: The provider has the right to audit the partner's data usage to ensure compliance with the data sharing agreement and privacy protection provisions.

[0295] ③ Data Feedback Mechanism:

[0296] Regular Feedback: Partners should regularly feedback to the data provider on the effectiveness of data usage and analysis results to continuously improve the data sharing mechanism.

[0297] Problem Reporting: In the process of data usage, if any privacy leakage or data security problems are found, they should be reported to the data provider in a timely manner to take appropriate measures.

[0298] In summary, in view of the shortcomings of the prior art, the purpose of the present application is to provide an improved data management system with the following characteristics:

[0299] The present application aims to make data more secure in the process of transmission, storage and processing through some advanced security technologies and authentication mechanisms, prevent data leakage and unauthorized access. At the same time, some more comprehensive data privacy protection measures are also provided to ensure that personal privacy can be effectively protected in various data processing situations. In addition, by optimizing the data sharing mechanism, the efficiency of data sharing and utilization can also be improved, maximizing the value of data.

[0300] This solution not only solves the problems of data security storage, privacy protection, sharing and utilization, but also meets the data management needs of the automotive industry and other industries. By achieving these goals, the technical progress of the data management system is promoted, especially in the automotive field, ensuring the secure storage and sharing of personal information and environmental monitoring information, providing a more reliable and efficient solution.

[0301] Compared with the prior art, the technical feature effects of the embodiment of the present application include but are not limited to:

[0302] 1. Enhanced data security and authentication mechanism:

[0303] The present application integrates advanced security technologies and authentication mechanisms to ensure the security of data in the process of transmission, storage and processing, solves the problem of insufficient security in the prior art, prevents data leakage and unauthorized access. Especially for the privacy protection problem of data sharing and cross-platform application, a more comprehensive solution is provided.

[0304] 2. Dynamic de-sensitization processing mechanism:

[0305] For complex data processing scenarios, the invention designs a set of dynamic de-sensitization rules that can flexibly process data types such as GPS route data and driving habits data. De-sensitization measures not only include simple replacement and encryption, but also data generalization processing to ensure effective protection of personal privacy in diversified applications.

[0306] 3. Efficient data sharing platform:

[0307] The invention provides a modular data sharing platform that allows users to customize data access permissions and scope according to their needs. This platform not only realizes data "availability invisibility", but also optimizes data sharing mechanisms to ensure that data utilization efficiency is not sacrificed during sharing, thereby maximizing the commercial value of data.

[0308] 4. Secure application of sandbox computing environment:

[0309] The invention applies sandbox computing technology such as trusted execution environment, MPC and federated learning to build a secure computing environment to ensure data privacy during analysis and processing. This innovation solves the problem of insufficient privacy protection in existing data processing technologies, ensuring that sensitive data is not leaked during use.

[0310] 5. Flexibility and scalability design:

[0311] The data management system has high flexibility and scalability, which can quickly adapt to changing business needs and technological progress, overcoming the lack of flexibility and scalability of existing systems, ensuring that it can continuously meet the data management needs of different fields such as the automotive industry.

[0312] 6. Overall data management solution:

[0313] The invention provides an overall data management framework that can simultaneously solve the problems of secure data storage, privacy protection, sharing and utilization, avoiding the shortcomings of isolated solutions in existing technologies. This solution is particularly suitable for data management needs in the automotive industry and other industries, promoting technological progress in data management systems.

[0314] As shown in Figure 2 the embodiment of the invention also provides a data security management device 900, which can include:

[0315] The first module 901 is used to obtain information data to be managed; the information data includes sensitive data and regular data;

[0316] The second module 902 is used to encrypt and store the sensitive data and the regular data to different servers, and to perform regular backup on the data stored by the servers;

[0317] The third module 903 is configured to perform a desensitization operation on the sensitive information in the information data based on a preset desensitization rule, to obtain desensitized data.

[0318] The fourth module 904 is configured to perform target data analysis based on the desensitized data through a pre-constructed sandbox environment, to obtain a data analysis result.

[0319] The desensitized data and the data analysis result are stored in a server.

[0320] The fifth module 905 is configured to establish a data sharing platform based on the server according to a preset permission range and a control policy.

[0321] The sixth module 906 is configured to share the target data to an authorized object through an API interface of the data sharing platform in response to a data sharing request of the authorized object.

[0322] The content of the method embodiments of the present application is applicable to the device embodiments, the device embodiments specifically implement the same functions as the method embodiments, and achieve the same beneficial effects as the method embodiments.

[0323] The present application also provides an electronic device, which includes a memory and a processor, the memory stores a computer program, and the processor implements the above data security management method when executing the computer program. The electronic device can be any smart terminal, such as a tablet computer or a vehicle-mounted computer.

[0324] It can be understood that the content of the above method embodiments is applicable to the device embodiments, the device embodiments specifically implement the same functions as the method embodiments, and achieve the same beneficial effects as the method embodiments.

[0325] Please refer to Figure 3 , Figure 3 The hardware structure of the electronic device 1000 of another embodiment is illustrated, which includes:

[0326] The processor 1001 can be implemented in a general-purpose CPU (Central Processing Unit), a microprocessor, an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits, and is used to execute related programs to implement the technical solutions provided by the embodiments of the present application.

[0327] The memory 1002 can be implemented in the form of a Read Only Memory (ROM), a static storage device, a dynamic storage device, or a Random Access Memory (RAM), etc. The memory 1002 can store an operating system and other application programs, and when the technical solutions provided by the embodiments of the present specification are implemented by software or firmware, the related program codes are stored in the memory 1002 and are called and executed by the processor 1001 to perform the data security management method of the embodiments of the present application;

[0328] The input / output interface 1003 is used to realize information input and output;

[0329] The communication interface 1004 is used to realize the communication interaction between the device and other devices, which can realize communication through wired mode (such as USB, network cable, etc.) or wireless mode (such as mobile network, WIFI, Bluetooth, etc.);

[0330] The bus 1005 transmits information between various components (such as the processor 1001, the memory 1002, the input / output interface 1003, and the communication interface 1004) of the device;

[0331] The processor 1001, the memory 1002, the input / output interface 1003, and the communication interface 1004 are connected to each other through the bus 1005 for communication connection within the device.

[0332] The embodiments of the present application also provide a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the above-mentioned data security management method.

[0333] It can be understood that the contents in the above method embodiments are applicable to the present storage medium embodiments, the functions specifically realized by the present storage medium embodiments are the same as those of the above method embodiments, and the beneficial effects achieved by the present storage medium embodiments are also the same as those of the above method embodiments.

[0334] The memory, as a non-transitory computer readable storage medium, can be used to store non-transitory software programs and non-transitory computer executable programs. In addition, the memory can include a high-speed random access memory, and can also include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state memory device. In some embodiments, the memory can optionally include a memory remotely arranged relative to the processor, and these remote memories can be connected to the processor through a network. Examples of the above network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0335] The data security management method, data security management device, electronic equipment and storage medium provided by the embodiment of the application include the following beneficial effects:

[0336] 1. Data security is improved: by encrypting the sensitive data and the regular data and storing them in different servers, the risk of data leakage is effectively reduced, thereby improving the overall data security.

[0337] 2. Data backup: regularly backing up the data stored in the server ensures that the data can be quickly recovered in the case of data loss or damage, thereby guaranteeing the integrity and availability of the data.

[0338] 3. Sensitivity information desensitization: based on the preset desensitization rule, the sensitive information is desensitized to generate desensitized data. The desensitized data retains the value of the data while eliminating the risk of sensitive information leakage, and is suitable for data analysis, testing and other scenarios.

[0339] 4. Safe data analysis environment: the target data analysis is performed through the pre-constructed sandbox environment, thereby ensuring the safety and isolation of the data analysis process and preventing misoperation or leakage of the original data during the data analysis process.

[0340] 5. Controllable data sharing: based on the preset permission range and control strategy, the data sharing platform is established, and only authorized objects can access specific data. The data sharing is realized through the API interface, thereby providing a flexible and controllable data sharing mechanism to meet the access requirements of different authorized objects.

[0341] 6. Improve data utilization efficiency: under the premise of ensuring data security, the data utilization efficiency is improved through the data sharing platform and the desensitized data analysis, thereby supporting enterprise decision-making, business innovation and other requirements.

[0342] In summary, the embodiment of the application provides significant beneficial effects in terms of data security, privacy protection, data sharing and utilization efficiency, and is suitable for various scenarios that require efficient, secure management and sharing of data.

[0343] The embodiments described in the present application are used to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application. Those skilled in the art can know that, with the evolution of technology and the appearance of new application scenarios, the technical solutions provided by the embodiments of the present application are also applicable to similar technical problems.

[0344] Those skilled in the art can understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and can include more or fewer steps than shown in the figures, or combine certain steps, or different steps.

[0345] The system embodiments described above are only schematic, and the units described as separate components can or can not be physically separate, that is, can be located in one place, or can be distributed on multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiments of the present application.

[0346] Those skilled in the art can understand that all or some of the steps in the above disclosed method, the functional modules / units in the system, and the device can be implemented as software, firmware, hardware, and appropriate combinations thereof.

[0347] The terms "first", "second", "third", "fourth" and the like (if any) in the specification of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device that includes a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0348] It should be understood that, in the present application, "at least one" means one or more, and "multiple" means two or more. "And / or" is used to describe the relationship between associated objects, which means that there can be three relationships, for example, "A and / or B" can mean: only A, only B, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally represents an "or" relationship between the associated objects. "At least one of the following" or similar expressions means any combination of these items, including any combination of single or multiple items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0349] In several embodiments provided by the present application, it should be understood that the disclosed system and method can be implemented in other ways. For example, the above-described system embodiments are only illustrative, for example, the division of the above units is only a logical functional division, and actual implementation can have another division manner, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed units can be indirect coupling or communication connection through some interfaces, systems or units, which can be electrical, mechanical or other forms.

[0350] The units described above as separate components can or can not be physically separated, and the components displayed as units can or can not be physical units, that is, they can be located in one place, or they can be distributed on multiple network units. According to actual needs, some or all of the units can be selected to achieve the purpose of the embodiment of the present application.

[0351] In addition, the functional units in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0352] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application, essentially or in other words, the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes multiple instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various program storage media.

[0353] The preferred embodiments of the embodiments of the present application are described above with reference to the accompanying drawings, and are not limited to the scope of the embodiments of the present application. Any modifications, equivalent replacements and improvements made by those skilled in the art without departing from the scope and essence of the embodiments of the present application shall be within the scope of the embodiments of the present application.

Claims

1. A data security management method characterized by comprising: The method comprises the following steps: obtaining information data to be managed; the information data comprises sensitive data and regular data; storing the sensitive data and the regular data in different servers in an encrypted manner, and performing periodic backup on the data stored in the servers; performing desensitization operation on sensitive information in the information data based on preset desensitization rules to obtain desensitized data; performing target data analysis based on the desensitized data through a pre-constructed sandbox environment to obtain data analysis results; wherein the desensitized data and the data analysis results are stored in the servers; establishing a data sharing platform based on the servers according to a preset permission range and control policy; in response to a data sharing request of an authorized object, sharing target data to the authorized object through an API interface of the data sharing platform; wherein the step of storing the sensitive data and the regular data in different servers in an encrypted manner comprises the following steps: storing the sensitive data in a local server; and performing encryption processing on the data in the local server using an SM4 encryption algorithm; storing the regular data in a cloud server; and performing encryption control on the data in the cloud server using a security function of a cloud service provider; wherein the servers comprise a local server and a cloud server; and the step of performing periodic backup on the data stored in the servers comprises the following steps: performing full backup and incremental backup on the data in the local server periodically based on a preset period; wherein the execution period of the incremental backup is longer than that of the full backup, and the backup data is stored in different physical locations of the local server compared with the data to be backed up; performing backup processing on the data in the cloud server periodically using a backup function of a cloud service provider, and testing the data recovery process of the cloud server periodically; wherein each backup copy obtained through different backup processing is stored in different physical locations of the cloud server.

2. The data security management method of claim 1, wherein, The step of performing desensitization operation on sensitive information in the information data based on preset desensitization rules comprises the following steps: in response to a preset data element review rule, marking the sensitive information in the information data; wherein the data type of the sensitive information comprises a first type, a second type and a third type; performing desensitization processing on the sensitive data of the first type; performing generalization processing on the sensitive data of the second type; performing strong encryption processing on the sensitive data of the third type; constructing a desensitization mapping table according to the correspondence between the sensitive information and the desensitized data corresponding thereto.

3. The data security management method of claim 1, wherein, The step of performing target data analysis based on the desensitized data through a pre-constructed sandbox environment to obtain data analysis results comprises the following steps: in response to a preset configuration requirement, creating the sandbox environment by network isolation configuration of target computing resources; wherein the sandbox environment integrates an analysis algorithm to be executed; inputting the desensitized data into the sandbox environment, performing the target data analysis based on the analysis algorithm, and outputting the data analysis results through the sandbox environment.

4. The data security management method of claim 1, wherein, The data sharing platform is established based on the server according to the preset authority range and control policy, and comprises the following steps: In response to the customization requirement of the management object for the authority and range of data access, the shared data range of the data sharing platform is determined; The security and privacy settings of the data sharing platform are configured through the control policy; The control policy comprises an access control policy, a data encryption policy and an audit log recording policy.

5. The data security management method of claim 1, wherein, In response to the data sharing request of the authorized object, the target data is shared to the authorized object through the API interface of the data sharing platform, and comprises the following steps: In response to the data sharing request of the authorized object, the data to be shared is determined; The data to be shared is subjected to data cleaning processing to obtain data to be transmitted; Based on the preset transmission layer security protocol, the data to be transmitted is encrypted and transmitted to the authorized object through the API interface of the data sharing platform to complete data sharing.

6. A data security management apparatus characterized by comprising: The device is applied to the data security management method of claim 1, and the device comprises: A first module is configured to obtain information data to be managed; the information data comprises sensitive data and regular data; A second module is configured to encrypt and store the sensitive data and the regular data to different servers, and perform periodic backup on the data stored in the servers; A third module is configured to perform desensitization operation on sensitive information in the information data based on a preset desensitization rule to obtain desensitized data; A fourth module is configured to perform target data analysis based on the desensitized data through a pre-constructed sandbox environment to obtain data analysis results; The desensitized data and the data analysis results are stored in the servers; A fifth module is configured to establish a data sharing platform based on the servers according to a preset authority range and control policy; A sixth module is configured to share target data to an authorized object through an API interface of the data sharing platform in response to a data sharing request of the authorized object.

7. An electronic device, comprising: The electronic device comprises a memory and a processor, the memory stores a computer program, and the processor implements the method of any one of claims 1 to 5 when executing the computer program.

8. A computer-readable storage medium storing a computer program, the computer-readable storage medium comprising: The computer program is executed by the processor to implement the method of any one of claims 1 to 5.

Images