Network platform data leakage risk assessment system and method and electronic equipment

Abstract

The invention relates to the technical field of data security, and discloses a network platform data leakage risk assessment system and method and electronic equipment, and the system comprises a data collection and recombination module, a leakage assessment positioning module and a data preservation and encryption module. The method and the electronic equipment correspond to the system. According to the application, the data acquisition and recombination module is used for recombination, and an accurate data basis is provided for subsequent evaluation; performing risk assessment and positioning by using a leakage assessment and positioning module, and generating a security encryption strategy; the data security is ensured by using a data preservation encryption module; comprehensive assessment and protection of the network platform data leakage risk are realized, the processing efficiency of the multi-source heterogeneous data of the network platform is effectively improved, the accuracy and the real-time performance of network platform data leakage risk assessment are improved, and the serious centralized data leakage risk is avoided.

Description

Technical Field

[0001] The present application relates to the field of data security technology, and specifically to a network platform data leakage risk assessment system, method and electronic equipment. Background Art

[0002] With the rapid development of Internet technology, the construction of network platforms has become increasingly mature, and as a result, massive amounts of data have been concentrated on network platforms, which has led to a significant increase in the risk of concentrated data leakage. In the face of this situation, it is necessary to improve the accuracy and real-time performance of network platform data leakage risk assessment.

[0003] Furthermore, the network platform integrates multi-source heterogeneous data from various data sources, which brings challenges in data processing, further affecting the risk assessment of data leakage on the network platform. Therefore, it is necessary to improve the efficiency of processing multi-source heterogeneous data on the network platform.

[0004] In summary, there is an urgent need for a new technical solution for network platform data leakage risk assessment to improve the efficiency of processing multi-source heterogeneous data on network platforms, improve the accuracy and real-time performance of network platform data leakage risk assessment, and avoid serious data leakage risks. Summary of the invention

[0005] The purpose of this application is to provide a network platform data leakage risk assessment system, method and electronic device to solve the technical problems raised in the above background technology.

[0006] To achieve the above objectives, this application discloses the following technical solutions:

[0007] In a first aspect, the present application discloses a network platform data leakage risk assessment system, which includes a data acquisition and reorganization module, a leakage assessment and positioning module, and a data preservation and encryption module; the data acquisition and reorganization module is communicatively connected to the leakage assessment and positioning module, and the leakage assessment and positioning module is communicatively connected to the data preservation and encryption module;

[0008] The data acquisition and reorganization module is used to collect multi-source heterogeneous data of the network platform using distributed acquisition technology, and reorganize the collected multi-source heterogeneous data based on preset reorganization rules to obtain evaluation data; wherein, the multi-source heterogeneous data at least includes user information, transmission records and system logs; the reorganization rules at least include time chain rules, logic chain rules and data source rules, the time chain rules are specifically based on the order of the time when the multi-source heterogeneous data is generated, the logic chain rules are specifically based on the logic of the multi-source heterogeneous data in the leakage risk assessment, and the data source rules are specifically based on the data source generated by the multi-source heterogeneous data.

[0009] The leakage assessment and positioning module is used to run a preset leakage assessment and positioning model and combine the assessment data to assess and locate the leakage risk and generate a security encryption strategy; wherein the leakage assessment and positioning model is used to assess and locate the leakage risk and generate a corresponding security encryption strategy, and the security encryption strategy is used to preserve and / or encrypt multi-source heterogeneous data;

[0010] The data security encryption module is used to execute the security encryption strategy; wherein, the data security encryption module is communicatively connected with each data source of the network platform.

[0011] Preferably, the reorganization is performed based on the order of time when the multi-source heterogeneous data is generated, specifically:

[0012] Get the data names and corresponding timestamps when all multi-source heterogeneous data are generated;

[0013] Reorganize the data names of all corresponding multi-source heterogeneous data when they are generated based on the order of corresponding timestamps, and establish a calling relationship between the corresponding data names and data contents; wherein the calling relationship is used to call the corresponding data contents based on the data names;

[0014] The data names and the corresponding calling relationships when all corresponding multi-source heterogeneous data are generated in sequence based on the corresponding timestamps after the reorganization are stored.

[0015] Preferably, the logic of leakage risk assessment based on multi-source heterogeneous data is reorganized, specifically:

[0016] Obtaining the logical order of use of data when historically using multi-source heterogeneous data for leakage risk assessment, and extracting features of the corresponding historical multi-source heterogeneous data, reorganizing and fixing the extracted features based on the obtained logical order of use of data when performing leakage risk assessment, to obtain the logic chain rule;

[0017] Acquire real-time multi-source heterogeneous data and perform feature extraction, and reorganize the extracted features based on the logic chain rules, specifically:

[0018] Matching the features corresponding to the extracted real-time multi-source heterogeneous data with the features corresponding to the historical multi-source heterogeneous data in the logic chain rule;

[0019] Based on the matching result, the logical use order of the data in the leakage risk assessment in the logic chain rule is used for reorganization.

[0020] Preferably, the data sources generated based on multi-source heterogeneous data are reorganized, specifically:

[0021] Obtain the data names and corresponding data sources of all multi-source heterogeneous data when they are generated;

[0022] Reorganize the data names when all corresponding multi-source heterogeneous data are generated based on the corresponding data sources, and establish a calling relationship between the corresponding data names and data contents; wherein the calling relationship is used to call the corresponding data contents based on the data names;

[0023] The reorganized data names and the corresponding calling relationships when all corresponding multi-source heterogeneous data are generated based on the corresponding data sources are stored.

[0024] Preferably, the preset process of the leakage assessment positioning model includes:

[0025] Obtaining historical assessment and location of leakage risks using multi-source heterogeneous data and generating corresponding records of the security encryption strategy;

[0026] Using a deep learning model, the leakage assessment and positioning model is constructed and trained to perform the following steps:

[0027] A1: Obtain multi-source heterogeneous data and the corresponding time chain rules, logic chain rules and data source rules for reorganization;

[0028] A2: Use multi-source heterogeneous data to assess leakage risk and obtain risk levels; wherein the risk levels include high risk, medium risk and low risk;

[0029] A3: Locate the leakage risk based on the leakage risk assessment in step A2;

[0030] A4: Based on the location of the leakage risk in step A3, the corresponding security encryption strategy is generated in combination with the time chain rule, the logic chain rule and the data source rule.

[0031] Preferably, step A2 specifically includes:

[0032] A21: Extract features from the acquired multi-source heterogeneous data;

[0033] A22: Calculate the probability value of data leakage risk based on the features obtained in step A21;

[0034] A23: Determine the risk level of data leakage based on the probability value of step A22.

[0035] Preferably, step A3 specifically includes:

[0036] A31: Based on the risk level obtained in step A2, executing step A32 for the high-risk data;

[0037] A32: Analyze the data flow and access path to determine the first leakage point;

[0038] A33: Filter the first leakage point based on the storage location and access rights of the data to obtain a second leakage point;

[0039] A34: Verify and troubleshoot the second leakage points, determine the third leakage points and output them; wherein the number of the first leakage points is greater than the number of the second leakage points, and the number of the second leakage points is greater than the third leakage points.

[0040] Preferably, step A4 specifically includes outputting the corresponding data security encryption strategy based on the third leakage point obtained in step A34;

[0041] The data preservation strategy at least includes:

[0042] When the leakage risk comes from external attacks, the security encryption strategy at least includes: combining the time chain rule, the logic chain rule and the data source rule, cutting off the data transmission between the data source and the outside, strengthening the network firewall setting and increasing the sensitivity of the intrusion detection system;

[0043] When the risk of leakage comes from internal personnel, the security encryption strategy at least includes: combining the time chain rule, the logic chain rule and the data source rule to limit employees' data access rights and implement data encryption.

[0044] In a second aspect, the present application discloses a network platform data leakage risk assessment method, which is applicable to the network platform data leakage risk assessment system as described above, and the method includes:

[0045] S1: Collect multi-source heterogeneous data from the network platform and reorganize them to generate assessment data; wherein, during collection, distributed collection technology is used to collect multi-source heterogeneous data including at least user information, transmission records and system logs, and during reorganization, the data is reorganized based on at least preset time chain rules, logic chain rules and data source rules. The time chain rule is reorganized based on the order of the time when the multi-source heterogeneous data is generated, the logic chain rule is reorganized based on the logic of the multi-source heterogeneous data in the leakage risk assessment, the data source rule is used to reorganize based on the data source generated by the multi-source heterogeneous data, and the assessment data is the reorganized multi-source heterogeneous data and is used for leakage assessment and positioning;

[0046] S2: Run a preset leakage assessment and location model and evaluate and locate leakage risks in combination with the assessment data to generate a security encryption strategy; wherein the leakage assessment and location model is used to evaluate and locate leakage risks and generate the corresponding security encryption strategy, and the security encryption strategy is used to guide the preservation and / or encryption of multi-source heterogeneous data;

[0047] S3: Execute the security encryption strategy.

[0048] In a third aspect, the present application discloses an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the network platform data leakage risk assessment method as described above when executing the computer program.

[0049] Beneficial effects: The network platform data leakage risk assessment system, method and electronic device of the present application utilize a data acquisition and reorganization module, a leakage assessment and positioning module and a data preservation and encryption module to achieve a comprehensive assessment and protection of network platform data leakage risks; wherein, the data acquisition and reorganization module acquires multi-source heterogeneous data through distributed acquisition technology, and reorganizes it according to time chain rules, logic chain rules and data source rules, providing an accurate data basis for subsequent assessments; the leakage assessment and positioning module runs a preset model and combines the reorganized data to perform risk assessment and positioning, and generates a preservation and encryption strategy; the data preservation and encryption module performs corresponding operations according to the strategy, communicates and connects with various data sources of the network platform, ensures data security, and effectively improves the efficiency of processing multi-source heterogeneous data of the network platform, improves the accuracy and real-time performance of network platform data leakage risk assessment, and avoids serious data concentration leakage risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without paying any creative work.

[0051] Figure 1 A structural block diagram of a network platform data leakage risk assessment system provided in an embodiment of the present application;

[0052] Figure 2 A flowchart of a method for assessing the risk of data leakage on a network platform provided in an embodiment of the present application. DETAILED DESCRIPTION

[0053] The technical solutions in the embodiments of the present application are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application.

[0054] In this article, the term "comprising" is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of more restrictions, the elements defined by the sentence "comprising..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0055] The first aspect of this embodiment discloses Figure 1 A network platform data leakage risk assessment system is shown, the system includes a data acquisition and reorganization module, a leakage assessment and positioning module and a data preservation and encryption module; the data acquisition and reorganization module is communicatively connected with the leakage assessment and positioning module, and the leakage assessment and positioning module is communicatively connected with the data preservation and encryption module;

[0056] The data acquisition and reorganization module is used to acquire and reorganize multi-source heterogeneous data of the network platform to generate evaluation data; wherein, during acquisition, distributed acquisition technology is used to acquire multi-source heterogeneous data including at least user information, transmission records and system logs, and during reorganization, the data is reorganized based on at least preset time chain rules, logic chain rules and data source rules. The time chain rule is to reorganize based on the sequence of the moments when the multi-source heterogeneous data is generated, the logic chain rule is to reorganize based on the logic of the multi-source heterogeneous data in the leakage risk assessment, the data source rule is to reorganize based on the data source generated by the multi-source heterogeneous data, and the evaluation data is the reorganized multi-source heterogeneous data and is used for leakage assessment and positioning;

[0057] The leakage assessment and positioning module is used to run the preset leakage assessment and positioning model and combine the assessment data to assess and locate the leakage risk and generate a preservation and encryption strategy; wherein the leakage assessment and positioning model is used to assess and locate the leakage risk and generate a corresponding preservation and encryption strategy, and the preservation and encryption strategy is used to preserve and / or encrypt multi-source heterogeneous data;

[0058] The data security encryption module is used to execute the security encryption strategy; wherein the data security encryption module is connected to the communication of each data source of the network platform.

[0059] In a specific application, in a certain network platform, the data collection and reorganization module uses the existing distributed collection technology to collect multi-source heterogeneous data such as user registration information, transaction records, and system operation logs; according to the time chain rule, for example, user transaction records are reorganized in order of transaction time; according to the logic chain rule, data related to transaction security is reorganized first according to the risk assessment logic; according to the data source rule, data from different business departments are reorganized separately. The reorganized assessment data is transmitted to the leakage assessment and positioning module, which assesses and locates the risk through the leakage assessment and positioning model. If a high-risk situation is found, a security encryption strategy is generated, such as limiting the access rights of certain suspicious users. Finally, the data security encryption module executes these strategies to protect the platform data security.

[0060] Based on the above, this embodiment utilizes the data acquisition and reorganization module, the leakage assessment and positioning module and the data preservation and encryption module to realize the comprehensive assessment and protection of the data leakage risk of the network platform; wherein, the data acquisition and reorganization module collects multi-source heterogeneous data through distributed acquisition technology, and reorganizes it according to the time chain rules, logical chain rules and data source rules, so as to provide an accurate data basis for subsequent evaluation; the leakage assessment and positioning module runs the preset model and combines the reorganized data to perform risk assessment and positioning, and generates a preservation and encryption strategy; the data preservation and encryption module performs corresponding operations according to the strategy, communicates and connects with various data sources of the network platform to ensure data security, effectively improves the efficiency of processing multi-source heterogeneous data of the network platform, improves the accuracy and real-time performance of the data leakage risk assessment of the network platform, and avoids the serious risk of concentrated data leakage.

[0061] Specifically, the reorganization is performed based on the order in which the multi-source heterogeneous data are generated, as follows:

[0062] Get the data names and corresponding timestamps when all multi-source heterogeneous data are generated;

[0063] Reorganize the data names of all corresponding multi-source heterogeneous data when they are generated based on the order of corresponding timestamps, and establish a calling relationship between the corresponding data names and data contents; wherein the calling relationship is used to call the corresponding data contents based on the data names;

[0064] The data names and corresponding calling relationships when all corresponding multi-source heterogeneous data are generated are stored in a reorganized order based on the corresponding timestamps.

[0065] In one example, in a network platform, for multi-source heterogeneous data such as dynamics, comments, and system logs posted by users, the name of each data generated and the corresponding timestamp are first obtained. For example, the timestamp of a dynamic is 10:00 on November 10, 2024, and the timestamp of a comment is 10:05 on November 10, 2024. These data names are reorganized in chronological order. When you need to view the content of a certain data, you can quickly find the corresponding data content through the call relationship.

[0066] Through the above, this embodiment realizes the reorganization of multi-source heterogeneous data in chronological order, and provides time dimension support for more convenient data search and analysis based on time clues and accurate assessment of data leakage risks in subsequent data processing and risk assessment, which helps to quickly locate data that may have problems at a specific time point and improve the efficiency and accuracy of risk assessment.

[0067] Specifically, the logic of leakage risk assessment based on multi-source heterogeneous data is reorganized as follows:

[0068] Obtain the logical order of use of data when using multi-source heterogeneous data for leakage risk assessment in history, and extract features of the corresponding multi-source heterogeneous data in history, reorganize and fix the extracted features based on the obtained logical order of use of data when performing leakage risk assessment, and obtain a logic chain rule;

[0069] Acquire real-time multi-source heterogeneous data and extract features, and reorganize the extracted features based on logical chain rules, specifically:

[0070] Match the features corresponding to the extracted real-time multi-source heterogeneous data with the features corresponding to the historical multi-source heterogeneous data in the logic chain rules;

[0071] Based on the matching results, the logical order of use of the data in the leakage risk assessment in the logic chain rules is used for reorganization.

[0072] It should be noted that the logical chain rules obtained by the present embodiment for obtaining the logical order of use of data when conducting historical leakage risk assessment and extracting historical multi-source heterogeneous data features for reorganization are based on the logical experience known to those skilled in the art. In a specific application, when a certain network platform conducts data reorganization based on logical rules, in analyzing historical leakage risk assessment, it first analyzes the logical order of transaction data and then analyzes user account information, extracts corresponding historical data features, and when new transaction data, user information and other multi-source heterogeneous data are generated, extracts new data features and matches them with historical features. If the new transaction data features match a historical high-risk transaction feature, then according to the logical chain rules, the transaction data and related user account information are preferentially reorganized for more accurate risk assessment.

[0073] Through the above, this embodiment realizes the reorganization of multi-source heterogeneous data based on risk assessment logic, so that the new data can better follow the logic of risk assessment during the reorganization process, improve the pertinence and effectiveness of data processing, and provide a more reasonable data organization method for accurately assessing and locating data leakage risks.

[0074] Specifically, the data sources generated by multi-source heterogeneous data are reorganized as follows:

[0075] Obtain the data names and corresponding data sources of all multi-source heterogeneous data when they are generated;

[0076] Reorganize the data names of all corresponding multi-source heterogeneous data when they are generated based on the corresponding data sources, and establish a calling relationship between the corresponding data names and data contents; wherein the calling relationship is used to call the corresponding data contents based on the data names;

[0077] The data names and corresponding calling relationships when all corresponding multi-source heterogeneous data are generated based on the corresponding data sources after storage and reorganization.

[0078] In a specific application, a certain network platform, data may come from business systems of different departments, such as the human resources department, finance department, sales department, etc. For these multi-source heterogeneous data, first obtain the name of each data and the corresponding data source. For example, a piece of employee attendance data is named "November Attendance Record" and the data source is the human resources system. Then, these data names are reorganized according to the data source. When you need to view the data content of a certain data source, you can quickly find the corresponding data through the call relationship.

[0079] Through the above, this embodiment realizes the reorganization of multi-source heterogeneous data according to the data source, which helps to better manage and analyze data from different data sources. In the data leakage risk assessment, it is possible to more quickly identify data sources that may be at risk, adopt targeted preservation and encryption strategies, and improve the efficiency of data security protection.

[0080] Specifically, the preset process of the leakage assessment and positioning model includes:

[0081] Obtain historical records of the risk assessment and location of leakage using multi-source heterogeneous data and generate corresponding security encryption strategies;

[0082] Using the deep learning model, build and train the leak assessment and positioning model to perform the following steps:

[0083] A1: Obtain multi-source heterogeneous data and the corresponding time chain rules, logic chain rules and data source rules for reorganization;

[0084] A2: Use multi-source heterogeneous data to assess the risk of leakage and obtain risk levels, which include high risk, medium risk, and low risk.

[0085] A3: Locate the leakage risk based on the leakage risk assessment in step A2;

[0086] A4: Based on the location of the leakage risk in step A3, the corresponding security encryption strategy is generated in combination with the time chain rules, logic chain rules and data source rules.

[0087] Through the above, this embodiment realizes the accurate assessment and positioning of data leakage risks on the network platform and generates preservation and encryption strategies. By learning from historical experience, the model can better cope with the complexity of multi-source heterogeneous data, improve the accuracy and real-time performance of risk assessment, and provide strong support for the timely implementation of effective data preservation and encryption measures.

[0088] Specifically, step A2 includes:

[0089] A21: Extract features from the acquired multi-source heterogeneous data;

[0090] A22: Calculate the probability value of data leakage risk based on the features obtained in step A21;

[0091] A23: Determine the risk level of data leakage based on the probability value of step A22.

[0092] In a specific application, this embodiment extracts features from the acquired multi-source heterogeneous data, and the features may include data type, data volume, data source, data access frequency, etc.; the extracted features are input into a pre-trained risk assessment model, which may be based on a machine learning algorithm, such as a random forest, a support vector machine, etc.; the risk assessment model calculates the probability value based on the input features to reflect the possibility of data leakage.

[0093] Through the above, this embodiment realizes the quantitative assessment of data leakage risk. Through clear data feature analysis and probability calculation, it can more objectively judge the degree of risk faced by the data, provide an accurate basis for subsequent risk positioning and strategy formulation, and improve the scientificity and reliability of data leakage risk assessment.

[0094] Specifically, step A3 includes:

[0095] A31: Based on the risk level obtained in step A2, execute step A32 for high-risk data;

[0096] A32: Analyze the data flow and access path to determine the first leakage point;

[0097] A33: Combine the storage location and access rights of the data to filter the first leakage point and obtain the second leakage point;

[0098] A34: Verify and troubleshoot the second leakage point, determine the third leakage point and output it; wherein the number of the first leakage points is greater than the number of the second leakage points, and the number of the second leakage points is greater than the third leakage points.

[0099] In a specific application, the flow direction and access path of the data analyzed in this embodiment are determined to determine the first leakage point, which can be to find abnormal data transmission behavior by analyzing network traffic, system logs and other information; combine the storage location and access rights of the data to obtain the second leakage point. For example, if some data is stored in a less secure location or too many users have too high access rights, then these places may be the location of leakage risk; verify and troubleshoot the second leakage point, determine the third leakage point and output it, which can be verified by simulating attacks, vulnerability scanning and other methods to verify the authenticity of the leakage point. It can be understood that the flow direction and access path of the data analyzed in this embodiment, combined with the storage location and access rights of the data, are all analyses that can be performed by those skilled in the art based on common sense, and from step A32 to step A34, it is a progressive screening, so the number of the first leakage points obtained is greater than the number of the second leakage points, and the number of the second leakage points is greater than the third leakage points.

[0100] Through the above, this embodiment achieves accurate positioning of data leakage risks. Through gradual and in-depth analysis and investigation, the source of data leakage can be found more accurately, providing specific goals for taking targeted security encryption strategies, and effectively improving the effect of data security protection.

[0101] Specifically, step A4 specifically includes outputting a corresponding data security encryption strategy based on the third leakage point obtained in step A34;

[0102] The data preservation strategy shall at least include:

[0103] When the risk of leakage comes from external attacks, the security encryption strategy at least includes: combining time chain rules, logic chain rules and data source rules, cutting off data transmission between the data source and the outside, strengthening network firewall settings and increasing the sensitivity of the intrusion detection system;

[0104] When the risk of leakage comes from insiders, the security encryption strategy shall at least include: combining time chain rules, logic chain rules and data source rules to limit employees' data access rights and implement data encryption.

[0105] In a specific application, after a network platform determines the third leakage point of data leakage, if it is judged that the leakage risk comes from external attacks, such as hackers trying to invade, then in combination with the time chain rule, priority is given to protecting important data generated recently; according to the logic chain rule, data related to core business is strengthened; according to the data source rule, the connection of certain external data sources is cut off; at the same time, the network firewall setting is strengthened to improve the sensitivity of the intrusion detection system; if the leakage risk comes from internal personnel, such as an employee is found to abnormally access sensitive data, the employee's data access rights are restricted in combination with the reorganization rule, and a higher level of encryption is implemented for sensitive data. It should be noted that the preservation and encryption in the preservation and encryption strategy of this embodiment both use existing data preservation technology and data encryption technology, such as access control technology and asymmetric encryption technology.

[0106] Through the above, this embodiment achieves effective response to data leakage risks, executes different data preservation and encryption strategies based on different risk types, and ensures data security.

[0107] The second aspect of this embodiment discloses Figure 2 A network platform data leakage risk assessment method is shown, which is applicable to the network platform data leakage risk assessment system as described above, and the method includes:

[0108] S1: Collect multi-source heterogeneous data from the network platform and reorganize them to generate assessment data; wherein, during collection, distributed collection technology is used to collect multi-source heterogeneous data including at least user information, transmission records and system logs, and during reorganization, the data is reorganized based on at least preset time chain rules, logic chain rules and data source rules. The time chain rule is to reorganize based on the sequence of the moments when the multi-source heterogeneous data is generated, the logic chain rule is to reorganize based on the logic of the multi-source heterogeneous data in the leakage risk assessment, and the data source rule is to reorganize based on the data source generated by the multi-source heterogeneous data. The assessment data is the reorganized multi-source heterogeneous data and is used for leakage assessment and positioning;

[0109] S2: Run the preset leakage assessment and location model and combine the assessment data to assess and locate the leakage risk, and generate a preservation and encryption strategy; wherein the leakage assessment and location model is used to assess and locate the leakage risk and generate a corresponding preservation and encryption strategy, and the preservation and encryption strategy is used to guide the preservation and / or encryption of multi-source heterogeneous data;

[0110] S3: Execute the security encryption policy.

[0111] It should be noted that the network platform data leakage risk assessment method of this embodiment corresponds to the aforementioned network platform data leakage risk assessment system. Therefore, the content not specifically described in the network platform data leakage risk assessment method of this embodiment can refer to the aforementioned network platform data leakage risk assessment system for but not limited to the function definition, working principle and technical effects, and this text will not elaborate on it.

[0112] The third aspect of this embodiment discloses an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the network platform data leakage risk assessment method as described above when executing the computer program.

[0113] Similarly, it should be noted that the electronic device of this embodiment corresponds to the aforementioned network platform data leakage risk assessment system. Therefore, the contents not specifically described in the electronic device of this embodiment may, but are not limited to, refer to the aforementioned network platform data leakage risk assessment system for function definition, working principle and technical effects, and this text will not elaborate on them here.

[0114] In summary, the network platform data leakage risk assessment system, method and electronic device of the present embodiment utilizes a data acquisition and reorganization module, a leakage assessment and positioning module and a data preservation and encryption module to achieve a comprehensive assessment and protection of network platform data leakage risks; wherein, the data acquisition and reorganization module collects multi-source heterogeneous data through distributed acquisition technology, and reorganizes it according to time chain rules, logical chain rules and data source rules, so as to provide an accurate data basis for subsequent evaluation; the leakage assessment and positioning module runs a preset model and combines the reorganized data to perform risk assessment and positioning, and generates a preservation and encryption strategy; the data preservation and encryption module performs corresponding operations according to the strategy, communicates and connects with various data sources of the network platform, ensures data security, and effectively improves the efficiency of processing multi-source heterogeneous data of the network platform, improves the accuracy and real-time performance of the network platform data leakage risk assessment, and avoids the serious risk of concentrated data leakage.

[0115] In the embodiments provided in the present application, it should be understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code or any appropriate combination thereof. For hardware implementation, the processor can be implemented in one or more of the following units: application specific integrated circuit (ASIC), digital signal processor (DSP), digital signal processing device (DSPD), programmable logic device (PLD), field programmable gate array (FPGA), processor, controller, microcontroller, microprocessor, other electronic units designed to implement the functions described herein or their combination. For software implementation, part or all of the flow of the embodiment can be completed by instructing the relevant hardware through a computer program. When implemented, the above program can be stored in a computer-readable storage medium or transmitted as one or more instructions or codes on a computer-readable storage medium. Computer-readable storage media include computer storage media and communication media, wherein the communication medium includes any medium that is convenient for transmitting a computer program from one place to another. The storage medium can be any available medium that a computer can access. The computer-readable storage medium can include but is not limited to RAM, ROM, EEPROM, CD-ROM or other optical disk storage, disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of an instruction or data structure and can be accessed by a computer.

[0116] Finally, it should be noted that the above is only a preferred embodiment of the present application and is not intended to limit the present application. Although the present application has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A network platform data leakage risk assessment system, characterized in that: The system includes a data acquisition and reorganization module, a leakage assessment and positioning module, and a data preservation and encryption module; the data acquisition and reorganization module is in communication connection with the leakage assessment and positioning module, and the leakage assessment and positioning module is in communication connection with the data preservation and encryption module; The data acquisition and reorganization module is used to collect multi-source heterogeneous data of the network platform using distributed acquisition technology, and reorganize the collected multi-source heterogeneous data based on preset reorganization rules to obtain evaluation data; wherein, the multi-source heterogeneous data at least includes user information, transmission records and system logs; the reorganization rules at least include time chain rules, logic chain rules and data source rules, the time chain rules are specifically based on the order of the time when the multi-source heterogeneous data is generated, the logic chain rules are specifically based on the logic of the multi-source heterogeneous data in the leakage risk assessment, and the data source rules are specifically based on the data source generated by the multi-source heterogeneous data. The leakage assessment and positioning module is used to run a preset leakage assessment and positioning model and combine the assessment data to assess and locate the leakage risk and generate a security encryption strategy; wherein the leakage assessment and positioning model is used to assess and locate the leakage risk and generate a corresponding security encryption strategy, and the security encryption strategy is used to preserve and / or encrypt multi-source heterogeneous data; The data security encryption module is used to execute the security encryption strategy; wherein, the data security encryption module is communicatively connected with each data source of the network platform.

2. The network platform data leakage risk assessment system according to claim 1 is characterized in that: The reorganization based on the order of time when the multi-source heterogeneous data is generated is specifically as follows: Get the data names and corresponding timestamps when all multi-source heterogeneous data are generated; Reorganize the data names of all corresponding multi-source heterogeneous data when they are generated based on the order of corresponding timestamps, and establish a calling relationship between the corresponding data names and data contents; wherein the calling relationship is used to call the corresponding data contents based on the data names; The data names and the corresponding calling relationships when all corresponding multi-source heterogeneous data are generated in sequence based on the corresponding timestamps after the reorganization are stored.

3. The network platform data leakage risk assessment system according to claim 1, characterized in that: The logic of leakage risk assessment based on multi-source heterogeneous data is reorganized as follows: Obtaining the logical order of use of data when historically using multi-source heterogeneous data for leakage risk assessment, and extracting features of the corresponding historical multi-source heterogeneous data, reorganizing and fixing the extracted features based on the obtained logical order of use of data when performing leakage risk assessment, to obtain the logic chain rule; Acquire real-time multi-source heterogeneous data and perform feature extraction, and reorganize the extracted features based on the logic chain rules, specifically: Matching the features corresponding to the extracted real-time multi-source heterogeneous data with the features corresponding to the historical multi-source heterogeneous data in the logic chain rule; Based on the matching result, the logical use order of the data in the leakage risk assessment in the logic chain rule is used for reorganization.

4. The network platform data leakage risk assessment system according to claim 1, characterized in that: The data sources generated based on multi-source heterogeneous data are reorganized, specifically: Obtain the data names and corresponding data sources of all multi-source heterogeneous data when they are generated; Reorganize the data names when all corresponding multi-source heterogeneous data are generated based on the corresponding data sources, and establish a calling relationship between the corresponding data names and data contents; wherein the calling relationship is used to call the corresponding data contents based on the data names; The reorganized data names and the corresponding calling relationships when all corresponding multi-source heterogeneous data are generated based on the corresponding data sources are stored.

5. The network platform data leakage risk assessment system according to claim 1, characterized in that: The preset process of the leakage assessment positioning model includes: Obtaining historical assessment and location of leakage risks using multi-source heterogeneous data and generating corresponding records of the security encryption strategy; Using a deep learning model, the leakage assessment and positioning model is constructed and trained to perform the following steps: A1: Obtain multi-source heterogeneous data and the corresponding time chain rules, logic chain rules and data source rules for reorganization; A2: Use multi-source heterogeneous data to assess leakage risk and obtain risk levels; wherein the risk levels include high risk, medium risk and low risk; A3: Locate the leakage risk based on the leakage risk assessment in step A2; A4: Based on the location of the leakage risk in step A3, the corresponding security encryption strategy is generated in combination with the time chain rule, the logic chain rule and the data source rule.

6. The network platform data leakage risk assessment system according to claim 5, characterized in that: Step A2 specifically includes: A21: Extract features from the acquired multi-source heterogeneous data; A22: Calculate the probability value of data leakage risk based on the features obtained in step A21; A23: Determine the risk level of data leakage based on the probability value of step A22.

7. The network platform data leakage risk assessment system according to claim 6, characterized in that: Step A3 specifically includes: A31: Based on the risk level obtained in step A2, executing step A32 for the high-risk data; A32: Analyze the data flow and access path to determine the first leakage point; A33: Filter the first leakage point based on the storage location and access rights of the data to obtain a second leakage point; A34: Verify and troubleshoot the second leakage points, determine the third leakage points and output them; wherein the number of the first leakage points is greater than the number of the second leakage points, and the number of the second leakage points is greater than the third leakage points.

8. The network platform data leakage risk assessment system according to claim 7, characterized in that: Step A4, specifically comprising outputting the corresponding data security encryption strategy based on the third leakage point obtained in step A34; The data preservation strategy at least includes: When the leakage risk comes from external attacks, the security encryption strategy at least includes: combining the time chain rule, the logic chain rule and the data source rule, cutting off the data transmission between the data source and the outside, strengthening the network firewall setting and increasing the sensitivity of the intrusion detection system; When the risk of leakage comes from internal personnel, the security encryption strategy at least includes: combining the time chain rule, the logic chain rule and the data source rule to limit employees' data access rights and implement data encryption.

9. A network platform data leakage risk assessment method, the method is applicable to the network platform data leakage risk assessment system according to any one of claims 1 to 8, characterized in that: The method includes: S1: Collect multi-source heterogeneous data from the network platform and reorganize them to generate assessment data; wherein, during collection, distributed collection technology is used to collect multi-source heterogeneous data including at least user information, transmission records and system logs, and during reorganization, the data is reorganized based on at least preset time chain rules, logic chain rules and data source rules. The time chain rule is reorganized based on the order of the time when the multi-source heterogeneous data is generated, the logic chain rule is reorganized based on the logic of the multi-source heterogeneous data in the leakage risk assessment, the data source rule is used to reorganize based on the data source generated by the multi-source heterogeneous data, and the assessment data is the reorganized multi-source heterogeneous data and is used for leakage assessment and positioning; S2: Run a preset leakage assessment and location model and evaluate and locate leakage risks in combination with the assessment data to generate a security encryption strategy; wherein the leakage assessment and location model is used to evaluate and locate leakage risks and generate the corresponding security encryption strategy, and the security encryption strategy is used to guide the preservation and / or encryption of multi-source heterogeneous data; S3: Execute the security encryption strategy.

10. An electronic device, characterized in that: It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, it implements the network platform data leakage risk assessment method as described in claim 9.

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