Data cross-border circulation security risk supervision system and method based on big data technology

Abstract

The present invention discloses a data cross-border circulation security risk supervision system and method based on big data technology, and relates to the technical field of data supervision. The present invention extracts data features of each cross-border data, and classifies all cross-border data according to the data features; performs primary data classification on the supervision platform; extracts the circulation position of each cross-border data in the historical records, and performs secondary position classification on the supervision platform; calculates the sensitivity of each supervision platform to the cross-border data based on the collected data standards; constructs a collaborative supervision flow; establishes a data sharing center in each collaborative supervision flow; selects the best circulation route, and correspondingly determines the collaborative supervision flow of the best circulation route; determines whether the cross-border data meets the standards of the supervision platform and issues an early warning, and transmits the generated early warning signal after the judgment to the data sharing center; adjusts the cross-border data circulation route according to the subsequent sensitivity of the supervision platform in the collaborative supervision flow.

Description

Technical Field

[0001] The present invention relates to the field of data supervision technology, and specifically to a system and method for supervising the security risks of cross-border data circulation based on big data technology. Background Art

[0002] The popularity of the Internet has broken geographical restrictions, allowing data to be quickly transmitted and shared around the world. The application of emerging technologies such as cloud computing, the Internet of Things, and big data has further accelerated the cross-border flow of data. Enterprises can store data in the cloud and share and transmit data between branches or partners in different countries; the widespread application of IoT devices has also generated a large amount of cross-border data, such as vehicle data in intelligent transportation systems and production equipment data in industrial Internet; with the rise of the digital economy and the widespread application of technologies such as big data and artificial intelligence, the importance of cross-border data circulation to economic development and social life has become increasingly significant, but it has also brought more complex and severe security risks, such as data ownership issues and the impact of geographical factors on data flow. Today, when conducting risk supervision on cross-border data, we can only passively check the cross-border data risks when the data is transmitted to the corresponding location, and the corresponding location cannot share data in the entire cross-border data circulation route, resulting in slow risk checks on cross-border data, and users cannot understand the detailed standards of each region when conducting cross-border data transmission, which seriously affects the user's data transmission efficiency. Summary of the invention

[0003] The purpose of the present invention is to provide a data cross-border circulation security risk supervision system and method based on big data technology to solve the problems raised in the prior art.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] A method for monitoring the security risks of cross-border data circulation based on big data technology, the method comprising the following steps:

[0006] S100, collecting all cross-border data in circulation in historical records, extracting data features of each cross-border data, and classifying all cross-border data according to the data features;

[0007] Furthermore, the specific steps to classify all cross-border data according to data characteristics are as follows:

[0008] S101. Collect all cross-border data in circulation in the historical records, extract the text contained in each cross-border data, and set the phrase type contained in the text of each cross-border data to be , Indicates the 1st, 2nd, 3rd, ..., nth phrases contained in each cross-border data extracted, where n is a positive integer; extract the number of each phrase in the cross-border data text respectively, and calculate the importance of each word in the cross-border data text. The formula is:

[0009] ;

[0010] In the formula, represents the importance of the i-th word in the cross-border data text, represents the number of the i-th word in the cross-border data text, M represents the total number of cross-border data text, Indicates the number of cross-border data texts with the i-th word in M ​​cross-border data texts; after n calculations, the importance of the n words in each cross-border data text is obtained, and the word with the greatest importance is selected as the data feature T of the corresponding cross-border data;

[0011] S102. Calculate the importance of each word for each cross-border data collected, and obtain the data characteristics of all cross-border data circulated in the collected historical records: , represents the data features of the 1st, 2nd, 3rd, ..., kth cross-border data circulated in the collected historical records, where k is a positive integer; the data features of each cross-border data are compared, and the cross-border data with the same data features are classified as the same type of cross-border data, and the types of cross-border data are obtained as follows: , Represents the 1st, 2nd, 3rd, ..., pth type of cross-border data after classification, where p is a positive integer.

[0012] Different countries and regions have different regulations and regulatory requirements for cross-border data flows. By classifying cross-border data, it is possible to clearly identify which data belongs to different categories such as personal information, commercial data, and security-critical data; classified cross-border data can implement different security protection strategies based on its importance and sensitivity; in the process of cross-border data flow, if data leakage or other security incidents occur, accurate classification helps to quickly determine the scope and type of data affected; in the context of cross-border data flow, accurate classification demonstrates the professionalism and standardization of data management by the data provider, which helps to enhance mutual trust with the region where the data recipient is located.

[0013] S200. Collect the regulatory platforms of all cross-border data in circulation in the historical records, match the types of cross-border data with the regulatory platforms, and perform primary data classification on the regulatory platforms; extract the circulation position of each cross-border data in the historical records, and perform secondary position classification on the regulatory platforms;

[0014] Furthermore, the specific steps for classifying the primary data of the regulatory platform are as follows:

[0015] Collect all the regulatory platforms of cross-border data in the historical records when they are in circulation, and extract the regulatory platform data set A= for each cross-border data , represents the 1st, 2nd, 3rd, ..., hth regulatory platform for each cross-border data, where h is a positive integer; the regulatory platforms are classified into the following categories according to the total number of cross-border data types: , It means that after the first-level classification of the regulatory platforms, the data sets of the 1st, 2nd, 3rd, ..., pth regulatory platforms are obtained;

[0016] The specific steps of performing secondary location classification on the supervision platform in S200 are:

[0017] S201, extract the circulation position of each cross-border data in the historical records, and obtain the circulation position set of the cross-border data: , represents the 1st, 2nd, 3rd, ..., tth circulation position of each cross-border data extracted, where t is a positive integer; according to the cross-border data circulation position, the regulatory platform of the corresponding position is found in the regulatory platform data set A of each cross-border data, and the regulatory platforms with the same position in the p regulatory platform data set A are classified into the same position regulatory platforms to form the regulatory platform position set B. After the second position classification, the regulatory platform position set is obtained as , It means that after the secondary classification, the 1st, 2nd, 3rd, ..., tth regulatory platform location sets are obtained.

[0018] There are differences in data protection standards, regulatory environments, and network security conditions in different regions. By using geographic location as the basis for secondary classification, the regulatory platform can fully consider the risk factors of different regions and strengthen supervision of data from or flowing to high-risk areas. When users transmit data across borders, they can accurately determine the specifications, standards, and procedures that need to be followed based on the type of data and the target geographic location, make compliance preparations in advance, avoid violations caused by lack of understanding of relevant requirements, reduce the legal risks faced by enterprises, and also improve the efficiency of cross-border data circulation.

[0019] S300. In each regulatory platform, data standards for cross-border data are collected according to the type of cross-border data and the platform location, and the sensitivity of each regulatory platform to cross-border data is calculated based on the collected data standards;

[0020] Furthermore, the specific steps for calculating the sensitivity of each regulatory platform to cross-border data based on the collected data standards are as follows:

[0021] S301. Extract data standards from the cross-border data specifications of all regulatory platforms and obtain all the impact directions after cross-border data leakage. , Indicates the 1st, 2nd, 3rd, ..., xth impact direction after cross-border data leakage, where x is a positive integer; the different impact degrees of each impact direction are digitized, and the digitized impact degrees are sorted from small to large and divided into five equal parts to obtain five levels of impact degree;

[0022] S302. A cross-border data impact assessment matrix is ​​set up in each regulatory platform based on the impact direction and impact degree. The vertical direction of the matrix represents the impact direction, and the horizontal direction represents the impact degree. Specifically:

[0023] ;

[0024] In the matrix, 1-5 represents the five levels of impact. - Indicates the 1st to xth impact directions, 0 / 1 indicates the selection, extracts the data standards for cross-border data in the corresponding regulatory platform, extracts the impact directions and the impact degree of each impact direction in the data standards, searches in the matrix, and marks 1 in the corresponding matrix cell when it meets the data standards of the corresponding regulatory platform, and marks 0 if it does not exist;

[0025] S303. After drawing the impact assessment matrix and marking it in each regulatory platform using the data standard, the marking results of the impact assessment matrix are used to calculate the sensitivity of each regulatory platform to cross-border data. The formula is:

[0026] ;

[0027] In the formula, Sen represents the calculated sensitivity of each regulatory platform to cross-border data, 5x represents the total number of all tags in the impact assessment matrix, y represents the yth tag in the impact assessment matrix, and y belongs to 1 to 5x; D represents the degree of influence of each tag in the impact assessment matrix; the sensitivity of each regulatory platform to cross-border data is calculated using the formula.

[0028] After clarifying the sensitivity of each regulatory platform to cross-border data, it is possible to clearly identify which platforms need to pay close attention to specific cross-border data and implement key supervision. This effectively reduces the risk of personal privacy data leakage. Different regulatory platforms have different levels of sensitivity to cross-border data, which means that their focus and investment in supervision should be different. By accurately calculating the sensitivity, more professional and experienced human resources can be allocated to regulatory areas with high sensitivity to cross-border data.

[0029] S400. Collect the circulation routes of all cross-border data in the historical records, extract the corresponding supervision platform according to the location in the circulation route, and build a collaborative supervision flow; establish a data sharing center in each collaborative supervision flow;

[0030] Furthermore, the specific steps to establish a data sharing center in each collaborative supervision flow are:

[0031] S401. Collect the circulation routes of all cross-border data in the historical records, extract the corresponding supervision platform according to the position in the circulation route, and use the supervision platform in the extracted circulation route to form a collaborative supervision flow. , It represents the 1st, 2nd, 3rd, ..., gth regulatory platforms for cross-border data from the initial location to the destination, J1 represents the regulatory platform at the initial location, and Jg represents the regulatory platform at the destination; a data sharing center is established in the collaborative regulatory circulation.

[0032] S500: When cross-border data needs to be circulated, the origin and destination of the cross-border data are determined in real time, the best circulation route is selected, and the coordinated supervision flow of the best circulation route is determined accordingly;

[0033] Furthermore, the specific steps of the coordinated supervision flow corresponding to determining the best circulation route are:

[0034] S501. When cross-border data needs to be circulated, the origin and destination of the cross-border data are determined in real time, and all circulation routes from the origin to the destination are extracted. , Represents the 1st, 2nd, 3rd, ..., c circulation routes from the initial point to the destination, where c is a positive integer; extracts the sensitivity of each regulatory platform in the collaborative regulatory flow in each circulation route to cross-border data, extracts the maximum sensitivity in each collaborative regulatory flow as the difficulty of the corresponding circulation route, selects the circulation route with the least difficulty among the c circulation routes as the optimal circulation route for cross-border data circulation, and determines the collaborative regulatory flow in the optimal circulation route.

[0035] S600. When cross-border data circulates according to the best circulation route, the cross-border data supervision strategy is constructed by using the sensitivity of each regulatory platform in the collaborative supervision flow to the cross-border data, judging whether the cross-border data meets the standards of the regulatory platform and issuing warnings, and transmitting the warning signals generated after the judgment to the data sharing center; the cross-border data circulation route is adjusted according to the sensitivity of the subsequent regulatory platforms in the collaborative supervision flow.

[0036] When different regulatory platforms supervise cross-border data flows, they often need to collect and analyze a large amount of identical or similar data, such as basic information of enterprises, basic records of cross-border data transmission, etc. By establishing a data sharing center, each platform can directly obtain the required data without having to repeat data collection work, thus saving a lot of manpower, material resources and time costs, and investing more resources in core regulatory business.

[0037] With the real-time data provided by the data sharing center, once there is an abnormal situation in cross-border data flow or the risk index exceeds the preset threshold, the early warning mechanism can be quickly triggered and the early warning information can be pushed to the relevant regulatory platforms in a timely manner. Each platform can obtain accurate risk warnings at the first time and then take targeted measures to respond.

[0038] Furthermore, the specific steps to determine whether cross-border data meets the regulatory platform standards are:

[0039] S601. When cross-border data circulates according to the best circulation route, each regulatory platform in the collaborative regulatory flow conducts security checks on the cross-border data according to regional regulations. The standard for all inspection directions of cross-border data by the regulatory platform is , It represents the standard for extracting the first, second, third, ..., e inspection directions of cross-border data by the regulatory platform, where e is a positive integer. The cross-border data regulatory strategy is constructed by using the sensitivity of each regulatory platform in the collaborative regulatory flow to cross-border data. The formula is:

[0040] ;

[0041] In the formula, Ta represents the construction of cross-border data supervision strategy, and Sen represents the sensitivity of each supervision platform in the collaborative supervision flow to cross-border data;

[0042] S602. Each regulatory platform in the collaborative regulatory flow uses the calculated cross-border data regulatory strategy to check the cross-border data. When one of the inspection directions of the cross-border data exceeds the standard of the cross-border data regulatory strategy, it is judged that the cross-border data does not meet the regulatory platform standard and an early warning is issued. After that, the early warning regulatory platform transmits the early warning signal to the data sharing center. In the collaborative regulatory flow, the sensitivity of the subsequent regulatory platform and the early warning regulatory platform is judged. When the sensitivity of the subsequent regulatory platform is less than that of the early warning regulatory platform, the cross-border data searches for a regulatory platform of the same type with a sensitivity less than that of the early warning regulatory platform in the first-level classification of the regulatory platform for transfer, and then reaches the subsequent regulatory platform in the collaborative regulatory flow after transfer.

[0043] When the sensitivity of the subsequent supervision platform is greater than that of the early warning supervision platform, the cross-border data will be sent directly back to the initial location for rectification.

[0044] The data cross-border circulation security risk supervision system based on big data technology includes data collection module, classification module, sensitivity calculation module, collaborative supervision flow construction module, optimal circulation route selection module, and inspection and adjustment module;

[0045] The data collection module is used to collect the circulation routes and circulation locations of cross-border data in historical records, and to collect the data standards of the regulatory platform for cross-border data;

[0046] The classification module is used to classify all cross-border data, and then to classify all regulatory platforms according to the type of cross-border data, and to classify them according to the location of cross-border data circulation;

[0047] The sensitivity calculation module is used to draw and mark the impact assessment matrix using the data standards for cross-border data in each regulatory platform, and then calculate the sensitivity;

[0048] The collaborative supervision flow construction module is used to extract the supervision platform, construct the collaborative supervision flow, and establish a data sharing center according to the location of the circulation route of cross-border data;

[0049] The optimal circulation route selection module is used to judge all circulation routes from the origin to the destination of the cross-border data and obtain the optimal circulation route;

[0050] The inspection and adjustment module is used to formulate cross-border data supervision strategies according to the sensitivity of each supervision platform in the collaborative supervision flow when cross-border data is circulated, inspect and issue warnings on cross-border data, and transmit warning signals to the data sharing center; and adjust the cross-border data circulation route according to the sensitivity of subsequent supervision platforms in the collaborative supervision flow.

[0051] The classification module includes the cross-border data classification unit and the regulatory platform classification unit;

[0052] The cross-border data classification unit is used to extract feature data of all cross-border data and classify the cross-border data using the feature data;

[0053] The classification unit of the regulatory platform is used to perform primary classification based on the type of cross-border data and to perform secondary classification based on the cross-border data circulation location.

[0054] The inspection and adjustment module includes a supervision strategy building unit, an inspection unit and a route adjustment unit;

[0055] The regulatory strategy building unit is used to formulate regulatory strategies using the sensitivity of each regulatory platform to cross-border data;

[0056] The inspection unit is used to inspect cross-border data and issue warnings using the supervision strategy formulated by each supervision platform in the collaborative supervision flow, and transmit the warning signal to the data sharing center;

[0057] The route adjustment unit is used to determine the sensitivity of the subsequent supervision platform and the early warning supervision platform, and adjust the circulation route of cross-border data.

[0058] Compared with the prior art, the present invention has the following beneficial effects:

[0059] 1. After the present invention classifies the regulatory platform into two levels, when users transmit data across borders, they can accurately determine the specifications, standards and procedures that need to be followed based on the type of data and the target geographic location, make compliance preparations in advance, and avoid violations caused by lack of understanding of relevant requirements.

[0060] 2. The present invention aims at different regulatory platforms with different sensitivities to cross-border data, and the focus and investment level in regulatory work should be different. By accurately calculating the sensitivity, more professional and experienced human resources can be allocated to regulatory areas with high sensitivity to cross-border data.

[0061] 3. After the present invention establishes a data sharing center in the collaborative supervision flow, relying on the real-time data provided by the data sharing center, once an abnormal situation occurs in the cross-border data flow or the risk index exceeds the preset threshold, the early warning mechanism can be quickly triggered and the early warning information can be pushed to the relevant supervision platform in a timely manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 This is a module distribution diagram of the data cross-border circulation security risk supervision system based on big data technology of the present invention;

[0063] Figure 2 It is a schematic diagram of the steps of the method for supervising the security risks of cross-border data circulation based on big data technology of the present invention. DETAILED DESCRIPTION

[0064] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0065] Example: Figure 1-Figure 2 As shown, the present invention provides a technical solution.

[0066] A method for monitoring the security risks of cross-border data circulation based on big data technology, the method comprising the following steps:

[0067] S100, collecting all cross-border data in circulation in historical records, extracting data features of each cross-border data, and classifying all cross-border data according to the data features;

[0068] Furthermore, the specific steps to classify all cross-border data according to data characteristics are as follows:

[0069] S101. Collect all cross-border data in circulation in the historical records, extract the text contained in each cross-border data, and set the phrase type contained in the text of each cross-border data to be , Indicates the 1st, 2nd, 3rd, ..., nth phrases contained in each cross-border data extracted, where n is a positive integer; extract the number of each phrase in the cross-border data text respectively, and calculate the importance of each word in the cross-border data text. The formula is:

[0070] ;

[0071] In the formula, represents the importance of the i-th word in the cross-border data text, represents the number of the i-th word in the cross-border data text, M represents the total number of cross-border data text, Indicates the number of cross-border data texts with the i-th word in M ​​cross-border data texts; after n calculations, the importance of the n words in each cross-border data text is obtained, and the word with the greatest importance is selected as the data feature T of the corresponding cross-border data;

[0072] S102. Calculate the importance of each word for each cross-border data collected, and obtain the data characteristics of all cross-border data circulated in the collected historical records: , represents the data features of the 1st, 2nd, 3rd, ..., kth cross-border data circulated in the collected historical records, where k is a positive integer; the data features of each cross-border data are compared, and the cross-border data with the same data features are classified as the same type of cross-border data, and the types of cross-border data are obtained as follows: , Represents the 1st, 2nd, 3rd, ..., pth type of cross-border data after classification, where p is a positive integer.

[0073] Different countries and regions have different regulations and regulatory requirements for cross-border data flows. By classifying cross-border data, it is possible to clearly identify which data belongs to different categories such as personal information, commercial data, and security-critical data; classified cross-border data can implement different security protection strategies based on its importance and sensitivity; in the process of cross-border data flow, if data leakage or other security incidents occur, accurate classification helps to quickly determine the scope and type of data affected; in the context of cross-border data flow, accurate classification demonstrates the professionalism and standardization of data management by the data provider, which helps to enhance mutual trust with the region where the data recipient is located.

[0074] S200. Collect the regulatory platforms of all cross-border data in circulation in the historical records, match the types of cross-border data with the regulatory platforms, and perform primary data classification on the regulatory platforms; extract the circulation position of each cross-border data in the historical records, and perform secondary position classification on the regulatory platforms;

[0075] Furthermore, the specific steps for classifying the primary data of the regulatory platform are as follows:

[0076] Collect all the regulatory platforms of cross-border data in the historical records when they are in circulation, and extract the regulatory platform data set A= for each cross-border data , represents the 1st, 2nd, 3rd, ..., hth regulatory platform for each cross-border data, where h is a positive integer; the regulatory platforms are classified into the following categories according to the total number of cross-border data types: , It means that after the first-level classification of the regulatory platforms, the data sets of the 1st, 2nd, 3rd, ..., pth regulatory platforms are obtained;

[0077] The specific steps of performing secondary location classification on the supervision platform in S200 are:

[0078] S201, extract the circulation position of each cross-border data in the historical records, and obtain the circulation position set of the cross-border data: , represents the 1st, 2nd, 3rd, ..., tth circulation position of each cross-border data extracted, where t is a positive integer; according to the cross-border data circulation position, the regulatory platform of the corresponding position is found in the regulatory platform data set A of each cross-border data, and the regulatory platforms with the same position in the p regulatory platform data set A are classified into the same position regulatory platforms to form the regulatory platform position set B. After the second position classification, the regulatory platform position set is obtained as , It means that after the secondary classification, the 1st, 2nd, 3rd, ..., tth regulatory platform location sets are obtained.

[0079] There are differences in data protection standards, regulatory environments, and network security conditions in different regions. By using geographic location as the basis for secondary classification, the regulatory platform can fully consider the risk factors of different regions and strengthen supervision of data from or flowing to high-risk areas. When users transmit data across borders, they can accurately determine the specifications, standards, and procedures that need to be followed based on the type of data and the target geographic location, make compliance preparations in advance, avoid violations caused by lack of understanding of relevant requirements, reduce the legal risks faced by enterprises, and also improve the efficiency of cross-border data circulation.

[0080] S300. In each regulatory platform, data standards for cross-border data are collected according to the type of cross-border data and the platform location, and the sensitivity of each regulatory platform to cross-border data is calculated based on the collected data standards;

[0081] Furthermore, the specific steps for calculating the sensitivity of each regulatory platform to cross-border data based on the collected data standards are as follows:

[0082] S301. Extract data standards from the cross-border data specifications of all regulatory platforms and obtain all the impact directions after cross-border data leakage. , Indicates the 1st, 2nd, 3rd, ..., xth impact direction after cross-border data leakage, where x is a positive integer; the different impact degrees of each impact direction are digitized, and the digitized impact degrees are sorted from small to large and divided into five equal parts to obtain five levels of impact degree;

[0083] S302. A cross-border data impact assessment matrix is ​​set up in each regulatory platform based on the impact direction and impact degree. The vertical direction of the matrix represents the impact direction, and the horizontal direction represents the impact degree. Specifically:

[0084] ;

[0085] In the matrix, 1-5 represents the five levels of impact. - Indicates the 1st to xth impact directions, 0 / 1 indicates the selection, extracts the data standards for cross-border data in the corresponding regulatory platform, extracts the impact directions and the impact degree of each impact direction in the data standards, searches in the matrix, and marks 1 in the corresponding matrix cell when it meets the data standards of the corresponding regulatory platform, and marks 0 if it does not exist;

[0086] S303. After drawing the impact assessment matrix and marking it in each regulatory platform using the data standard, the marking results of the impact assessment matrix are used to calculate the sensitivity of each regulatory platform to cross-border data. The formula is:

[0087] ;

[0088] In the formula, Sen represents the calculated sensitivity of each regulatory platform to cross-border data, 5x represents the total number of all tags in the impact assessment matrix, y represents the yth tag in the impact assessment matrix, and y belongs to 1 to 5x; D represents the degree of influence of each tag in the impact assessment matrix; the sensitivity of each regulatory platform to cross-border data is calculated using the formula.

[0089] After clarifying the sensitivity of each regulatory platform to cross-border data, it is possible to clearly identify which platforms need to pay close attention to specific cross-border data and implement key supervision. This effectively reduces the risk of personal privacy data leakage. Different regulatory platforms have different levels of sensitivity to cross-border data, which means that their focus and investment in supervision should be different. By accurately calculating the sensitivity, more professional and experienced human resources can be allocated to regulatory areas with high sensitivity to cross-border data.

[0090] S400. Collect the circulation routes of all cross-border data in the historical records, extract the corresponding supervision platform according to the location in the circulation route, and build a collaborative supervision flow; establish a data sharing center in each collaborative supervision flow;

[0091] Furthermore, the specific steps to establish a data sharing center in each collaborative supervision flow are:

[0092] S401. Collect the circulation routes of all cross-border data in the historical records, extract the corresponding supervision platform according to the position in the circulation route, and use the supervision platform in the extracted circulation route to form a collaborative supervision flow. , It represents the 1st, 2nd, 3rd, ..., gth regulatory platforms for cross-border data from the initial location to the destination, J1 represents the regulatory platform at the initial location, and Jg represents the regulatory platform at the destination; a data sharing center is established in the collaborative regulatory circulation.

[0093] S500: When cross-border data needs to be circulated, the origin and destination of the cross-border data are determined in real time, the best circulation route is selected, and the coordinated supervision flow of the best circulation route is determined accordingly;

[0094] Furthermore, the specific steps of the coordinated supervision flow corresponding to determining the best circulation route are:

[0095] S501. When cross-border data needs to be circulated, the origin and destination of the cross-border data are determined in real time, and all circulation routes from the origin to the destination are extracted. , Represents the 1st, 2nd, 3rd, ..., c circulation routes from the initial point to the destination, where c is a positive integer; extracts the sensitivity of each regulatory platform in the collaborative regulatory flow in each circulation route to cross-border data, extracts the maximum sensitivity in each collaborative regulatory flow as the difficulty of the corresponding circulation route, selects the circulation route with the least difficulty among the c circulation routes as the optimal circulation route for cross-border data circulation, and determines the collaborative regulatory flow in the optimal circulation route.

[0096] S600. When cross-border data circulates according to the best circulation route, the cross-border data supervision strategy is constructed by using the sensitivity of each regulatory platform in the collaborative supervision flow to the cross-border data, judging whether the cross-border data meets the standards of the regulatory platform and issuing warnings, and transmitting the warning signals generated after the judgment to the data sharing center; the cross-border data circulation route is adjusted according to the sensitivity of the subsequent regulatory platforms in the collaborative supervision flow.

[0097] When different regulatory platforms supervise cross-border data flows, they often need to collect and analyze a large amount of identical or similar data, such as basic information of enterprises, basic records of cross-border data transmission, etc. By establishing a data sharing center, each platform can directly obtain the required data without having to repeat data collection work, thus saving a lot of manpower, material resources and time costs, and investing more resources in core regulatory business.

[0098] With the real-time data provided by the data sharing center, once there is an abnormal situation in cross-border data flow or the risk index exceeds the preset threshold, the early warning mechanism can be quickly triggered and the early warning information can be pushed to the relevant regulatory platforms in a timely manner. Each platform can obtain accurate risk warnings at the first time and then take targeted measures to respond.

[0099] Furthermore, the specific steps to determine whether cross-border data meets the regulatory platform standards are:

[0100] S601. When cross-border data circulates according to the best circulation route, each regulatory platform in the collaborative regulatory flow conducts security checks on the cross-border data according to regional regulations. The standard for all inspection directions of cross-border data by the regulatory platform is , It represents the standard for extracting the first, second, third, ..., e inspection directions of cross-border data by the regulatory platform, where e is a positive integer. The cross-border data regulatory strategy is constructed by using the sensitivity of each regulatory platform in the collaborative regulatory flow to cross-border data. The formula is:

[0101] ;

[0102] In the formula, Ta represents the construction of cross-border data supervision strategy, and Sen represents the sensitivity of each supervision platform in the collaborative supervision flow to cross-border data;

[0103] S602. Each regulatory platform in the collaborative regulatory flow uses the calculated cross-border data regulatory strategy to check the cross-border data. When one of the inspection directions of the cross-border data exceeds the standard of the cross-border data regulatory strategy, it is judged that the cross-border data does not meet the regulatory platform standard and an early warning is issued. After that, the early warning regulatory platform transmits the early warning signal to the data sharing center. In the collaborative regulatory flow, the sensitivity of the subsequent regulatory platform and the early warning regulatory platform is judged. When the sensitivity of the subsequent regulatory platform is less than that of the early warning regulatory platform, the cross-border data searches for a regulatory platform of the same type with a sensitivity less than that of the early warning regulatory platform in the first-level classification of the regulatory platform for transfer, and then reaches the subsequent regulatory platform in the collaborative regulatory flow after transfer.

[0104] When the sensitivity of the subsequent supervision platform is greater than that of the early warning supervision platform, the cross-border data will be sent directly back to the initial location for rectification.

[0105] The data cross-border circulation security risk supervision system based on big data technology includes data collection module, classification module, sensitivity calculation module, collaborative supervision flow construction module, optimal circulation route selection module, and inspection and adjustment module;

[0106] The data collection module is used to collect the circulation routes and circulation locations of cross-border data in historical records, and to collect the data standards of the regulatory platform for cross-border data;

[0107] The classification module is used to classify all cross-border data, and then to classify all regulatory platforms according to the type of cross-border data, and to classify them according to the location of cross-border data circulation;

[0108] The sensitivity calculation module is used to draw and mark the impact assessment matrix using the data standards for cross-border data in each regulatory platform, and then calculate the sensitivity;

[0109] The collaborative supervision flow construction module is used to extract the supervision platform, construct the collaborative supervision flow, and establish a data sharing center according to the location of the circulation route of cross-border data;

[0110] The optimal circulation route selection module is used to judge all circulation routes from the origin to the destination of the cross-border data and obtain the optimal circulation route;

[0111] The inspection and adjustment module is used to formulate cross-border data supervision strategies according to the sensitivity of each supervision platform in the collaborative supervision flow when cross-border data is circulated, inspect and issue warnings on cross-border data, and transmit warning signals to the data sharing center; and adjust the cross-border data circulation route according to the sensitivity of subsequent supervision platforms in the collaborative supervision flow.

[0112] The classification module includes the cross-border data classification unit and the regulatory platform classification unit;

[0113] The cross-border data classification unit is used to extract feature data of all cross-border data and classify the cross-border data using the feature data;

[0114] The classification unit of the regulatory platform is used to perform primary classification based on the type of cross-border data and to perform secondary classification based on the cross-border data circulation location.

[0115] The inspection and adjustment module includes a supervision strategy building unit, an inspection unit and a route adjustment unit;

[0116] The regulatory strategy building unit is used to formulate regulatory strategies using the sensitivity of each regulatory platform to cross-border data;

[0117] The inspection unit is used to inspect cross-border data and issue warnings using the supervision strategy formulated by each supervision platform in the collaborative supervision flow, and transmit the warning signal to the data sharing center;

[0118] The route adjustment unit is used to determine the sensitivity of the subsequent supervision platform and the early warning supervision platform, and adjust the circulation route of cross-border data.

[0119] Example 1: The sensitivity of a regulatory platform to cross-border data is calculated, and the impact direction and degree of the regulatory platform in the region on cross-border data are extracted and marked in the impact assessment matrix, specifically:

[0120] ;

[0121] The sensitivity calculated using the formula is 0.6;

[0122] Example 2: When inspecting cross-border data in a collaborative supervision flow, the collaborative supervision flow is set to be the initial location J1→J2→J3→destination J4; the cross-border data is inspected in the J2 supervision platform, and the sensitivity of the J2 supervision platform is set to 0.6, and the inspection direction includes the data content volume and the number of data types; the inspection direction is calculated using the sensitivity to obtain the supervision strategy, and after determining that the cross-border data does not meet the standards of the J2 supervision platform, an early warning signal is transmitted to the data sharing center; the sensitivity of the subsequent J3 supervision platform is 0.8; the cross-border data is sent back to the initial location for rectification.

[0123] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A method for monitoring the security risks of cross-border data circulation based on big data technology, characterized by: The method comprises the following steps: S100, collecting all cross-border data in circulation in historical records, extracting data features of each cross-border data, and classifying all cross-border data according to the data features; S200. Collect the regulatory platforms of all cross-border data in circulation in the historical records, match the types of cross-border data with the regulatory platforms, and perform primary data classification on the regulatory platforms; extract the circulation position of each cross-border data in the historical records, and perform secondary position classification on the regulatory platforms; S300. In each regulatory platform, data standards for cross-border data are collected according to the type of cross-border data and the platform location, and the sensitivity of each regulatory platform to cross-border data is calculated based on the collected data standards; The specific steps to calculate the sensitivity of each regulatory platform to cross-border data based on the collected data standards are as follows: S301. Extract data standards from the cross-border data specifications of all regulatory platforms and obtain all the impact directions after cross-border data leakage. , Indicates the 1st, 2nd, 3rd, ..., xth impact direction after cross-border data leakage, where x is a positive integer; the different impact degrees of each impact direction are digitized, and the digitized impact degrees are sorted from small to large and divided into five equal parts to obtain five levels of impact degree; S302. A cross-border data impact assessment matrix is ​​set up in each regulatory platform based on the impact direction and impact degree. The vertical direction of the matrix represents the impact direction, and the horizontal direction represents the impact degree. Specifically: ； In the matrix, 1-5 represents the five levels of impact. - Indicates the 1st to xth impact directions, 0 / 1 indicates the selection, extracts the data standards for cross-border data in the corresponding regulatory platform, extracts the impact directions and the impact degree of each impact direction in the data standards, searches in the matrix, and marks 1 in the corresponding matrix cell when it meets the data standards of the corresponding regulatory platform, and marks 0 if it does not exist; S303. After drawing the impact assessment matrix and marking it in each regulatory platform using the data standard, the marking results of the impact assessment matrix are used to calculate the sensitivity of each regulatory platform to cross-border data. The formula is: ； In the formula, Sen represents the calculated sensitivity of each regulatory platform to cross-border data, 5x represents the total number of all tags in the impact assessment matrix, y represents the yth tag in the impact assessment matrix, and y belongs to 1 to 5x; D represents the impact degree of each tag in the impact assessment matrix; the sensitivity of each regulatory platform to cross-border data is calculated using the formula; S400. Collect the circulation routes of all cross-border data in the historical records, extract the corresponding supervision platform according to the location in the circulation route, and build a collaborative supervision flow; establish a data sharing center in each collaborative supervision flow; S500: When cross-border data needs to be circulated, the origin and destination of the cross-border data are determined in real time, the best circulation route is selected, and the coordinated supervision flow of the best circulation route is determined accordingly; The specific steps of the collaborative supervision flow to determine the best circulation route are: S501. When cross-border data needs to be circulated, the origin and destination of the cross-border data are determined in real time, and all circulation routes from the origin to the destination are extracted. , Represent the 1st, 2nd, 3rd, ..., cth circulation routes from the initial point to the destination, where c is a positive integer; extract the sensitivity of each regulatory platform in the collaborative regulatory flow to cross-border data in each circulation route, extract the maximum sensitivity in each collaborative regulatory flow as the difficulty of the corresponding circulation route, select the circulation route with the least difficulty among the c circulation routes as the optimal circulation route for cross-border data circulation, and determine the collaborative regulatory flow in the optimal circulation route; S600. When cross-border data circulates according to the best circulation route, the cross-border data supervision strategy is constructed by using the sensitivity of each regulatory platform in the collaborative supervision flow to the cross-border data, judging whether the cross-border data meets the standards of the regulatory platform and issuing warnings, and transmitting the warning signals generated after the judgment to the data sharing center; the cross-border data circulation route is adjusted according to the sensitivity of the subsequent regulatory platforms in the collaborative supervision flow.

2. The method for monitoring the security risks of cross-border data circulation based on big data technology according to claim 1 is characterized by: The specific steps of classifying all cross-border data according to data characteristics in S100 are: S101. Collect all cross-border data in circulation in the historical records, extract the text contained in each cross-border data, and set the phrase type contained in the text of each cross-border data to be , Indicates the 1st, 2nd, 3rd, ..., nth phrases contained in each cross-border data extracted, where n is a positive integer; extract the number of each phrase in the cross-border data text respectively, and calculate the importance of each word in the cross-border data text. The formula is: ； In the formula, represents the importance of the i-th word in the cross-border data text, represents the number of the i-th word in the cross-border data text, M represents the total number of cross-border data text, Indicates the number of cross-border data texts with the i-th word in M ​​cross-border data texts; after n calculations, the importance of the n words in each cross-border data text is obtained, and the word with the greatest importance is selected as the data feature T of the corresponding cross-border data; S102. Calculate the importance of each word for each cross-border data collected, and obtain the data characteristics of all cross-border data circulated in the collected historical records: , represents the data features of the 1st, 2nd, 3rd, ..., kth cross-border data circulated in the collected historical records, where k is a positive integer; the data features of each cross-border data are compared, and the cross-border data with the same data features are classified as the same type of cross-border data, and the types of cross-border data are obtained as follows: , Represents the 1st, 2nd, 3rd, ..., pth type of cross-border data after classification, where p is a positive integer.

3. The method for monitoring the security risks of cross-border data circulation based on big data technology according to claim 2 is characterized by: The specific steps of classifying the primary data of the supervision platform in S200 are: Collect all the regulatory platforms of cross-border data in the historical records when they are in circulation, and extract the regulatory platform data set A= for each cross-border data , represents the 1st, 2nd, 3rd, ..., hth regulatory platform for each cross-border data, where h is a positive integer; the regulatory platforms are classified into the following categories according to the total number of cross-border data types: , It means that after the first-level classification of the regulatory platforms, the data sets of the 1st, 2nd, 3rd, ..., pth regulatory platforms are obtained; The specific steps of performing secondary location classification on the supervision platform in S200 are: S201, extract the circulation position of each cross-border data in the historical records, and obtain the circulation position set of the cross-border data: , represents the 1st, 2nd, 3rd, ..., tth circulation position of each cross-border data extracted, where t is a positive integer; according to the cross-border data circulation position, the regulatory platform of the corresponding position is found in the regulatory platform data set A of each cross-border data, and the regulatory platforms with the same position in the p regulatory platform data set A are classified into the same position regulatory platforms to form the regulatory platform position set B. After the second position classification, the regulatory platform position set is obtained as , It means that after the secondary classification, the 1st, 2nd, 3rd, ..., tth regulatory platform location sets are obtained.

4. The method for monitoring the security risks of cross-border data circulation based on big data technology according to claim 1 is characterized by: The specific steps of establishing a data sharing center in each collaborative supervision flow in S400 are: S401. Collect the circulation routes of all cross-border data in the historical records, extract the corresponding supervision platform according to the position in the circulation route, and use the supervision platform in the extracted circulation route to form a collaborative supervision flow. , It represents the 1st, 2nd, 3rd, ..., gth regulatory platforms for cross-border data from the initial location to the destination, J1 represents the regulatory platform at the initial location, and Jg represents the regulatory platform at the destination; a data sharing center is established in the collaborative regulatory circulation.

5. The method for monitoring the security risks of cross-border data circulation based on big data technology according to claim 4 is characterized by: The specific steps of determining whether the cross-border data complies with the regulatory platform standards in S600 are: S601. When cross-border data circulates according to the best circulation route, each regulatory platform in the collaborative regulatory flow conducts security checks on the cross-border data according to regional regulations. The standard for all inspection directions of cross-border data by the regulatory platform is , It represents the standard for extracting the first, second, third, ..., e inspection directions of cross-border data by the regulatory platform, where e is a positive integer. The cross-border data regulatory strategy is constructed by using the sensitivity of each regulatory platform in the collaborative regulatory flow to cross-border data. The formula is: ； In the formula, Ta represents the construction of cross-border data supervision strategy, and Sen represents the sensitivity of each supervision platform in the collaborative supervision flow to cross-border data; S602. Each regulatory platform in the collaborative regulatory flow uses the calculated cross-border data regulatory strategy to check the cross-border data. When one of the inspection directions of the cross-border data exceeds the standard of the cross-border data regulatory strategy, it is judged that the cross-border data does not meet the regulatory platform standard and an early warning is issued. After that, the early warning regulatory platform transmits the early warning signal to the data sharing center. In the collaborative regulatory flow, the sensitivity of the subsequent regulatory platform and the early warning regulatory platform is judged. When the sensitivity of the subsequent regulatory platform is less than that of the early warning regulatory platform, the cross-border data searches for a regulatory platform of the same type with a sensitivity less than that of the early warning regulatory platform in the first-level classification of the regulatory platform for transfer, and then reaches the subsequent regulatory platform in the collaborative regulatory flow after transfer. When the sensitivity of the subsequent supervision platform is greater than that of the early warning supervision platform, the cross-border data will be sent directly back to the initial location for rectification.

6. A data cross-border circulation security risk supervision system based on big data technology using the data cross-border circulation security risk supervision method based on big data technology as described in any one of claims 1 to 5, characterized in that: The data cross-border circulation security risk supervision system includes data collection module, classification module, sensitivity calculation module, collaborative supervision flow construction module, optimal circulation route selection module, and inspection and adjustment module; The data collection module is used to collect the circulation routes and circulation locations of cross-border data in historical records, and to collect the data standards of the regulatory platform for cross-border data; The classification module is used to classify all cross-border data, and then to classify all regulatory platforms according to the type of cross-border data, and to classify them according to the location of cross-border data circulation; The sensitivity calculation module is used to draw and mark the impact assessment matrix using the data standards for cross-border data in each regulatory platform, and then calculate the sensitivity; The collaborative supervision flow construction module is used to extract the supervision platform, construct the collaborative supervision flow, and establish a data sharing center according to the location of the circulation route of cross-border data; The optimal circulation route selection module is used to judge all circulation routes from the origin to the destination of the cross-border data and obtain the optimal circulation route; The inspection and adjustment module is used to formulate cross-border data supervision strategies according to the sensitivity of each supervision platform in the collaborative supervision flow when cross-border data is circulated, inspect and issue warnings on cross-border data, and transmit warning signals to the data sharing center; and adjust the cross-border data circulation route according to the sensitivity of subsequent supervision platforms in the collaborative supervision flow.

7. The data cross-border circulation security risk supervision system based on big data technology according to claim 6 is characterized by: The classification module includes a cross-border data classification unit and a regulatory platform classification unit; The cross-border data classification unit is used to extract feature data of all cross-border data and classify the cross-border data using the feature data; The classification unit of the regulatory platform is used to perform primary classification based on the type of cross-border data and to perform secondary classification based on the cross-border data circulation location.

8. The data cross-border circulation security risk supervision system based on big data technology according to claim 6 is characterized by: The inspection and adjustment module includes a supervision strategy construction unit, an inspection unit and a route adjustment unit; The regulatory strategy building unit is used to formulate regulatory strategies using the sensitivity of each regulatory platform to cross-border data; The inspection unit is used to inspect cross-border data and issue warnings using the supervision strategy formulated by each supervision platform in the collaborative supervision flow, and transmit the warning signal to the data sharing center; The route adjustment unit is used to determine the sensitivity of the subsequent supervision platform and the early warning supervision platform, and adjust the circulation route of cross-border data.

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