Sensitive data detection method, device, computer equipment and storage medium

Abstract

The embodiment of the present application belongs to the field of information security technology and relates to a sensitive data detection method, including obtaining the data type of the issued data upon receiving the issued data, and determining whether the issued data is text data according to the data type; when determining that the issued data is text data, detecting the text type of the text data and obtaining the feature code corresponding to the text data; matching the feature code with the standard feature code stored in the database to determine whether sensitive information exists in the text data; when determining that sensitive information exists in the text data, calculating the base sensitivity of the text data, and desensitizing the text data whose base sensitivity is not less than a preset threshold. The present application also provides a sensitive data detection device, a computer device and a storage medium. In addition, the present application also relates to blockchain technology, and the issued data can be stored in a blockchain node. The present application improves the recognition efficiency and accuracy of privacy data and protects the security of personal information.

Description

Technical Field

[0001] The present application relates to the field of information security technology, and in particular to a sensitive data detection method, apparatus, computer equipment and storage medium. Background Art

[0002] With the rapid development of the information technology industry, using electronic devices such as mobile phones and computers for office or daily information processing has become an indispensable part of people's lives, and more and more people are beginning to communicate information through electronic devices. However, while information technology brings convenience, the problem of information leakage is becoming more and more serious, and information security issues are also being taken seriously by more and more people. In Internet applications, a lot of information includes relatively sensitive information. If this information is transmitted directly on the network, it will easily cause user privacy leakage.

[0003] At present, in order to avoid the leakage of user privacy data, protect user information security, and reduce the possibility of users being harassed or even defrauded, when receiving user information data, it is usually necessary to rely on manual judgment of user information data, and when possible privacy data is manually screened out, the data is encrypted, etc. However, when a large amount of user information data is received at the same time, the current data processing method cannot realize the rapid detection and screening of privacy data, which leads to the failure of timely warning of privacy data, and further leads to the problem of privacy data leakage. Summary of the invention

[0004] The purpose of the embodiments of the present application is to propose a sensitive data detection method, apparatus, computer equipment and storage medium, aiming to solve the technical problem of privacy data leakage.

[0005] In order to solve the above technical problems, the present application embodiment provides a sensitive data detection method, which adopts the following technical solution:

[0006] A sensitive data detection method comprises the following steps:

[0007] When receiving the sent data, obtaining the data type of the sent data, and determining whether the sent data is text data according to the data type;

[0008] When it is determined that the sent data is the text data, detecting the text type of the text data, and determining a feature code corresponding to the text data according to the text type;

[0009] Matching the feature code with a standard feature code stored in a database to determine whether sensitive information exists in the text data;

[0010] When it is determined that the sensitive information exists in the text data, the base sensitivity of the text data is calculated, and the text data whose base sensitivity is not less than a preset threshold is desensitized.

[0011] Further, the step of calculating the base sensitivity of the text data includes:

[0012] Obtaining a benchmark score for the text data;

[0013] A base sensitivity of the text data is determined according to the benchmark score.

[0014] Further, the step of determining the base sensitivity of the text data according to the benchmark score includes:

[0015] Acquire preset marked privacy data from the database, and calculate the matching degree between the text data and the marked privacy data;

[0016] The base sensitivity of the text data is calculated according to the matching degree and the benchmark score.

[0017] Furthermore, the step of determining the feature code corresponding to the text data according to the text type includes:

[0018] The text type includes a digital type, a letter type and a character type. The text data is symbolized according to the text type, and the symbolized text data is a feature code corresponding to the text data.

[0019] Furthermore, the step of matching the feature code with a standard feature code stored in a database to determine whether sensitive information exists in the text data includes:

[0020] Identify keywords in the feature code through grammatical analysis, and obtain documents including the keywords according to a document list constructed based on standard feature codes stored in a database;

[0021] The correlation between the document and the feature code is obtained, and whether sensitive information exists in the text data is determined according to the correlation.

[0022] Furthermore, after the step of determining whether sensitive information exists in the text data, the sensitive data detection method further includes:

[0023] When it is determined that the sensitive information exists in the text data, the sent data is sent to the front-end page to detect whether the sent data is completely used by the front-end page. If there is unused data in the front-end page, it is determined that the sent data is excessive and an alarm prompt message is sent.

[0024] Further, after the step of determining whether the sent data is text data according to the data type, the sensitive data detection further includes:

[0025] When it is determined that the sent data is non-text data, determining whether the sent data is image data according to the data type;

[0026] When it is determined that the sent data is the image data, extracting image information in the image data and the use authority of the information provider, determining whether the image data includes sensitive information according to the image information and the use authority, and if the image data includes the sensitive information, marking and storing the image data;

[0027] When it is determined that the sent data is audio data or video data, the voice data in the audio data or the video data is identified, and it is determined whether the voice data includes sensitive information. If the voice data includes the sensitive information, the audio data or the video data is marked for storage.

[0028] In order to solve the above technical problems, the embodiment of the present application further provides a sensitive data detection device, which adopts the following technical solution:

[0029] A first confirmation module is used to obtain a data type of the sent data when receiving the sent data, and determine whether the sent data is text data according to the data type;

[0030] an acquisition module, configured to detect a text type of the text data when determining that the sent data is the text data, and determine a feature code corresponding to the text data according to the text type;

[0031] A second confirmation module is used to match the feature code with a standard feature code stored in a database to determine whether sensitive information exists in the text data;

[0032] The desensitization module is used to calculate the base sensitivity of the text data when it is determined that the sensitive information exists in the text data, and perform desensitization processing on the text data whose base sensitivity is not less than a preset threshold.

[0033] In order to solve the above technical problems, an embodiment of the present application also provides a computer device, including a memory and a processor, and computer-readable instructions stored in the memory and executable on the processor, and the processor implements the steps of the above-mentioned sensitive data detection method when executing the computer-readable instructions.

[0034] In order to solve the above technical problems, an embodiment of the present application also provides a computer-readable storage medium, characterized in that computer-readable instructions are stored on the computer-readable storage medium, and when the computer-readable instructions are executed by the processor, the steps of the above-mentioned sensitive data detection method are implemented.

[0035] The above-mentioned sensitive data detection method, device, computer equipment and storage medium obtain the data type of the sent data when receiving the sent data, and determine whether the sent data is text data according to the data type, so as to process different data according to the data type; when it is determined that the sent data is the text data, the text type of the text data is detected, and the feature code corresponding to the text data is determined according to the text type, wherein the feature code is used to represent the feature information of the text data, and text data of different text types correspond to different types of feature codes; the feature code is matched with the standard feature code stored in the database to determine whether there is sensitive information in the text data. When it is determined that there is sensitive information in the text data, the base sensitivity of the text data is calculated, and the base sensitivity can be used to measure the sensitivity of the text data. When the base sensitivity is obtained, the text data whose base sensitivity is not less than a preset threshold is desensitized, thereby solving the technical problem of privacy data leakage. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the scheme in the present application, a brief introduction is given below to the drawings required for use in the description of the embodiments of the present application. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0037] Figure 1 is an exemplary system architecture diagram to which the present application may be applied;

[0038] Figure 2 A flowchart of an embodiment of a sensitive data detection method;

[0039] Figure 3 is a structural schematic diagram of an embodiment of a sensitive data detection device according to the present application;

[0040] Figure 4 It is a structural diagram of an embodiment of a computer device according to the present application.

[0041] Figure numerals: 600 sensitive data detection device; 610 first confirmation module; 620 acquisition module; 630 second confirmation module; 640 desensitization module. DETAILED DESCRIPTION

[0042] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by technicians in the technical field of the present application; the terms used in the specification of the application herein are only for the purpose of describing specific embodiments and are not intended to limit the present application; the terms "including" and "having" and any variations thereof in the specification and claims of the present application and the above-mentioned drawings are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of the present application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0043] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0044] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

[0045] like Figure 1 As shown, the system architecture 100 may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0046] Users can use terminal devices 101, 102, 103 to interact with server 105 through network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, 103, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social platform software, etc.

[0047] Terminal devices 101, 102, 103 can be various electronic devices with display screens and supporting web browsing, including but not limited to smart phones, tablet computers, e-book readers, MP3 players (Moving Picture Experts Group Audio Layer III), MP4 (Moving Picture Experts Group Audio Layer IV) players, laptop computers, desktop computers, etc.

[0048] The server 105 may be a server that provides various services, such as a background server that provides support for web pages displayed on the terminal devices 101 , 102 , and 103 .

[0049] It should be noted that the sensitive data detection method provided in the embodiments of the present application is generally executed by the server / terminal, and accordingly, the sensitive data detection device is generally arranged in the server / terminal device.

[0050] It should be understood that Figure 1 The number of terminals, networks and servers in the embodiment is only for illustration. Any number of terminals, networks and servers may be provided according to the implementation requirements.

[0051] Continue to refer Figure 2 , shows a flow chart of an embodiment of a sensitive data detection method according to the present application. The sensitive data detection method comprises the following steps:

[0052] Step S200, when receiving the sent data, obtaining the data type of the sent data, and determining whether the sent data is text data according to the data type;

[0053] The sent data is data received through the early warning interface, and the sent data may be text data, image data, audio data, video data, etc. When the sent data is received through the early warning interface, the data type of the sent data is obtained, and whether the sent data is text data is determined according to the data type, wherein the data type can be determined by the file name of the received file, and sent data of different data types correspond to different file names.

[0054] It should be emphasized that in order to further ensure the privacy and security of the above text data, the above text data can also be stored in a blockchain node.

[0055] Step S300, when it is determined that the sent data is the text data, detecting the text type of the text data, and determining a feature code corresponding to the text data according to the text type;

[0056] When it is determined that the data to be sent is text data, a feature code of the text data is obtained. The feature code is used to represent the feature information of the text data. Text data of different text types correspond to different types of feature codes. Among them, the text types of text data include: certificate type, certificate number type, birthday type, address type, mobile phone number type, etc. When the text data is obtained, the text type of the text data is detected, and the feature code corresponding to the text data is further determined according to the text type. The text feature code of the text data can be determined according to the preset processing rules corresponding to the current text type. For example, for text data whose text type is a telephone number, the preset processing rule of the feature code of the text type is to symbolize the text data of the text type to obtain a regular expression of the text data, and the regular expression is the feature code corresponding to the text data. The feature code corresponding to the text data is obtained, and according to the feature code, it can be further determined whether there is sensitive information in the current text data.

[0057] Step S400, matching the feature code with a standard feature code stored in a database to determine whether sensitive information exists in the text data;

[0058] When the feature code of the text data is obtained, the feature code is matched with the standard feature code stored in the database. If there is a standard feature code matching the feature code of the text data in the database, it is determined that sensitive information exists in the text data; if there is no standard feature code matching the feature code of the text data in the database, it is determined that no sensitive information exists in the text data.

[0059] Step S500, when it is determined that the sensitive information exists in the text data, the base sensitivity of the text data is calculated, and the text data whose base sensitivity is not less than a preset threshold is desensitized.

[0060] When it is determined that there is sensitive information in the text data, the base sensitivity of the text data is obtained, wherein the base sensitivity is used to measure the sensitivity of the text data. The base sensitivity can be determined by the benchmark score of the text data and other measurement parameters, such as the matching degree between the sensitive information in the current text information and the marked privacy data stored in the database and the risk score corresponding to the text information. When the base sensitivity of the text data is calculated, it is determined whether the base sensitivity is not less than the preset threshold. If the base sensitivity is not less than the preset threshold, the text data is desensitized; if the base sensitivity is less than the preset threshold, the text data is temporarily stored.

[0061] In this embodiment, when receiving the sent data, the data type of the sent data is obtained, and whether the sent data is text data is determined according to the data type. Then, when it is determined that the sent data is the text data, the text type of the text data is detected, and a feature code corresponding to the text data is determined according to the text type. Then, the feature code is matched with a standard feature code stored in a database to determine whether there is sensitive information in the text data. Then, when it is determined that there is sensitive information in the text data, the base sensitivity of the text data is calculated, and the text data whose base sensitivity is not less than a preset threshold is desensitized, thereby realizing intelligent determination of privacy data, improving recognition efficiency and accuracy of privacy data, reducing leakage of privacy information, and protecting the security of personal information.

[0062] In some embodiments of the present application, step S500 includes:

[0063] Obtaining a benchmark score for the text data;

[0064] A base sensitivity of the text data is determined according to the benchmark score.

[0065] Each text data of different text types has a preset benchmark score. Different text data of different text types correspond to different benchmark scores. For example, the benchmark score corresponding to the text data of the mobile phone number type is 40 points, and the benchmark score corresponding to the text data of the gender type is 5 points. The benchmark score is a preset value. The benchmark score corresponding to the current text data is obtained, and the basic sensitivity of the text data is further calculated based on the benchmark score.

[0066] In this embodiment, the base sensitivity of text data of different text types is determined, so that whether the current text data needs warning or desensitization processing can be determined more accurately according to the base sensitivity.

[0067] In some embodiments of the present application, determining the base sensitivity of the text data according to the benchmark score includes:

[0068] Acquire preset marked privacy data from the database, and calculate the matching degree between the text data and the marked privacy data;

[0069] The base sensitivity of the text data is calculated according to the matching degree and the benchmark score.

[0070] When the benchmark score of the text data is obtained, the matching degree of the text data is obtained, wherein the matching degree is the matching degree between the sensitive information in the text data and the marked privacy data stored in the database. For example, if the mobile phone number has 11 digits and can only match 10 digits with the marked privacy data, the matching degree is 10 / 11, about 90.9%. A lot of privacy data is pre-stored in the database, and the privacy data is all marked and stored in the database, that is, the pre-stored privacy data is marked according to the data category and then stored, so that the corresponding marked privacy data can be obtained. The matching degree between the sensitive information in the text data and the marked privacy data is obtained, and the matching degree can be expressed in decimals, accurate to a preset number of digits after the decimal point. When the matching degree is obtained, the base sensitivity of the text data is calculated according to the matching degree and the benchmark score of the text data. The specific calculation method can be weighted calculation, such as the benchmark score weight is 20%, the matching degree weight is 80%, and the base sensitivity of the text data is obtained by weighted comprehensive calculation. In addition, the base sensitivity can also be directly obtained by multiplying the matching degree and the benchmark score.

[0071] In this embodiment, accurate calculation of the base sensitivity of text data is achieved, which improves the processing accuracy of text data and the processing speed of whether the text data needs to be desensitized or warned.

[0072] In some embodiments of the present application, step S300 includes:

[0073] The text type includes a digital type, a letter type and a character type. The text data is symbolized according to the text type, and the symbolized text data is a feature code corresponding to the text data.

[0074] The process of symbolization is that when the text data is obtained, the text data is represented by a symbolic expression. The symbolization rules of text data of different text types are different, wherein the text types include digital type, letter type and text type. For text data of digital type, the length of the text data and the number of the first preset digits are obtained, and the specific category of the text data of the digital type is determined according to the length and the number of the first preset digits, such as the ID card category, the mobile phone number category, other categories, etc. Then, the corresponding symbolization processing method is determined according to the corresponding specific category. For example, for a mobile phone number starting with 861 or 1, the length of the number is 13 or 11 digits, and the symbolization processing method corresponding to the mobile phone number category is performed, and the characteristic code of the mobile phone number is obtained as / (86)? 1\d{10} / . For text data other than digital type, such as letters or text, the character string corresponding to the text data is obtained, and the character string is the characteristic code corresponding to the text data.

[0075] In this embodiment, the feature code of the text data is determined, so that the sensitive information in the text data can be accurately determined based on the feature code, thereby improving the detection efficiency of the sensitive information in the text data.

[0076] In some embodiments of the present application, step S400 includes:

[0077] Identify keywords in the feature code through grammatical analysis, and obtain documents including the keywords according to a document list constructed based on standard feature codes stored in a database;

[0078] The correlation between the document and the feature code is obtained, and whether sensitive information exists in the text data is determined according to the correlation.

[0079] When the feature code is obtained, the feature code can be matched and analyzed with the standard feature code pre-stored in the database by means of full-text retrieval analysis. Specifically, the keywords in the feature code are identified through grammatical analysis, and then the documents including the keywords are determined based on the document list constructed according to the standard feature code, and the correlation between the document and the feature code is scored and sorted, with the more relevant documents being ranked higher. In this way, it can be determined whether there is a standard feature code matching the feature code of the current text data in the database. If the correlation of the top document is greater than or equal to the preset correlation value, it is determined that there is a standard feature code matching the feature code of the text data in the database, that is, it is determined that there is sensitive information in the text data; if the correlation of the top document is less than the preset correlation value, it is determined that there is no standard feature code matching the feature code of the text data in the database, that is, it is determined that there is no sensitive information in the text data.

[0080] In this embodiment, accurate judgment of whether sensitive information exists in text data is achieved, further improving the processing efficiency of text data.

[0081] In some embodiments of the present application, after step S400, the following steps are included:

[0082] When it is determined that the sensitive information exists in the text data, the sent data is sent to the front-end page to detect whether the sent data is completely used by the front-end page. If there is unused data in the front-end page, it is determined that the sent data is excessive and an alarm prompt message is sent.

[0083] Before desensitizing the text data, the issued data can also be sent to the front-end interface, and the issued data can be detected again based on the front-end interface to determine whether the issued data is provided in excess. When the issued data is provided in excess, there may also be a risk of sensitive information leakage. Specifically, when it is determined that there is sensitive information in the issued data, the issued data is sent to the front-end page, and it is detected whether the issued data is fully used by the front-end page. Traverse all the issued data through ajax, and then match the issued data through regular expressions, that is, match the issued data with the page data in the front-end page, and determine whether the issued data already exists in the front-end page. If it is fully matched, it means that it already exists, and the risk of leakage is less likely. The issued data that already exists in the front-end page is scored according to a preset scoring method, such as scoring according to the number of times it appears on the front-end page, and the higher the number, the higher the corresponding risk score. If the issued data is not matched in the front-end page, it is determined that the issued data is excessively provided by the current back-end interface, which means that the current issued data is not needed by the current front-end page. At this time, an alarm prompt message is sent to the control center or the designated target person to indicate that there may be a risk of sensitive text information leakage, and the risk score corresponding to the sent data that is not required by the current front-end page is obtained. At this time, the risk score is a preset value. When the risk score of the sent data is obtained, the risk score can be used as one of the measurement parameters of the base sensitivity, and the base sensitivity of the sent data is calculated based on the risk score. Specifically, the risk score is used as one of the measurement parameters of the base sensitivity, and combined with the matching degree and the benchmark score corresponding to the sent data, a comprehensive weighted calculation is performed to obtain the final base sensitivity.

[0084] In this embodiment, it is achieved by detecting whether the sent data is excessive through the front-end page, and further efficiently judging whether there is a risk of sensitive information leakage in the sent data, ensuring double detection of the risk of sensitive information leakage and avoiding the risk of sensitive information leakage.

[0085] In some embodiments of the present application, after step S200, the following steps are included:

[0086] When it is determined that the sent data is non-text data, determining whether the sent data is image data according to the data type;

[0087] When it is determined that the sent data is the image data, extracting image information in the image data and the use authority of the information provider, determining whether the image data includes sensitive information according to the image information and the use authority, and if the image data includes the sensitive information, marking and storing the image data;

[0088] When it is determined that the sent data is audio data or video data, the voice data in the audio data or the video data is identified, and it is determined whether the voice data includes sensitive information. If the voice data includes the sensitive information, the audio data or the video data is marked for storage.

[0089] The sent data includes text data, image data, audio data and video data. When the sent data is determined to be image data according to the data type of the sent data, the image information in the image data is extracted through the face recognition system, and the use authority of the information provider of the image data is obtained. If the image information matches the image information stored in the database, wherein the stored image information is all sensitive image information, and the use authority is unauthorized, it is determined that the image data includes sensitive information, the image data is marked as stored as sensitive image data, and an alarm prompt message is sent to prompt that the current image data contains sensitive image information; if the image information does not match the image information stored in the database, and the use authority is unauthorized, it is determined that the image data does not include sensitive information, and no alarm prompt message is sent. If the image information matches the image information stored in the database, and the use authority is authorized, it is determined that the image data includes sensitive information, and the image data is marked as stored but no alarm prompt message is sent; if the image information does not match the image information stored in the database, and the use authority is authorized, it is determined that the image data does not include sensitive information, and no alarm prompt message is sent.

[0090] When it is determined that the data to be sent is audio data or video data, the voice data in the audio data or video data is identified to determine whether the voice data includes sensitive information; specifically, the voice data in the audio data or video data is audio recognized to obtain text data corresponding to the voice data, so that it can be determined whether the corresponding voice data includes sensitive information according to whether the text data includes sensitive information. Among them, whether the text data includes sensitive information is the same as the process of judging whether the text data includes sensitive information according to the feature code. If the voice data includes sensitive information, the audio data or video data is also marked and stored, and an alarm prompt message is sent to prompt that there is voice sensitive information in the current audio data or video data. In addition, when the data to be sent is image data, audio data and video data, if there is text information in the image data, audio data and video data, the text information is extracted and processed according to the processing method of the above text data.

[0091] In this embodiment, comprehensive detection and processing of image data, audio data and video data other than text data is achieved, which reduces information leakage and improves information security.

[0092] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through computer-readable instructions, and the computer-readable instructions can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the aforementioned storage medium can be a non-volatile storage medium such as a disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0093] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0094] Further references Figure 3 , as a response to the above Figure 2 In order to realize the method shown in the figure, the present application provides an embodiment of a sensitive data detection device, and the device embodiment is Figure 2 Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.

[0095] like Figure 3 As shown, the sensitive data detection device 600 described in this embodiment includes:

[0096] The first confirmation module 610 is used to obtain the data type of the sent data when receiving the sent data, and determine whether the sent data is text data according to the data type;

[0097] The sent data is data received through the early warning interface, and the sent data may be text data, image data, audio data, video data, etc. When the sent data is received through the early warning interface, the data type of the sent data is obtained, and whether the sent data is text data is determined according to the data type, wherein the data type can be determined by the file name of the received file, and sent data of different data types correspond to different file names.

[0098] It should be emphasized that in order to further ensure the privacy and security of the above text data, the above text data can also be stored in a blockchain node.

[0099] An acquisition module 620, configured to detect a text type of the text data when determining that the sent data is the text data, and determine a feature code corresponding to the text data according to the text type;

[0100] The acquisition module 620 further includes:

[0101] The processing unit is used for the text type including a number type, a letter type and a character type, and performs corresponding symbol processing on the text data according to the text type, and the text data after the symbol processing is obtained as a feature code corresponding to the text data.

[0102] When it is determined that the data to be sent is text data, a feature code of the text data is obtained. The feature code is used to represent the feature information of the text data. Text data of different text types correspond to different types of feature codes. Among them, the text types of text data include: certificate type, certificate number type, birthday type, address type, mobile phone number type, etc. When the text data is obtained, the text type of the text data is detected, and the feature code corresponding to the text data is further determined according to the text type. The text feature code of the text data can be determined according to the preset processing rules corresponding to the current text type. For example, for text data whose text type is a telephone number, the preset processing rule of the feature code of the text type is to symbolize the text data of the text type to obtain a regular expression of the text data, and the regular expression is the feature code corresponding to the text data. The feature code corresponding to the text data is obtained, and according to the feature code, it can be further determined whether there is sensitive information in the current text data.

[0103] A second confirmation module 630 matches the feature code with a standard feature code stored in a database to determine whether sensitive information exists in the text data;

[0104] The second confirmation module 630 further includes:

[0105] An analysis unit, configured to identify keywords in the feature code by grammatical analysis, and obtain documents including the keywords according to a document list constructed based on standard feature codes stored in a database;

[0106] The first confirmation unit is used to obtain the correlation between the document and the feature code, and determine whether sensitive information exists in the text data according to the correlation.

[0107] When the feature code of the text data is obtained, the feature code is matched with the standard feature code stored in the database. If there is a standard feature code matching the feature code of the text data in the database, it is determined that sensitive information exists in the text data; if there is no standard feature code matching the feature code of the text data in the database, it is determined that no sensitive information exists in the text data.

[0108] The desensitization module 640 is used to calculate the base sensitivity of the text data when it is determined that the sensitive information exists in the text data, and perform desensitization processing on the text data whose base sensitivity is not less than a preset threshold.

[0109] Wherein, the desensitization module 640 includes:

[0110] An acquisition unit, used for acquiring a benchmark score of the text data;

[0111] A second confirmation unit is used to determine the base sensitivity of the text data according to the benchmark score.

[0112] Wherein, the second confirmation unit includes:

[0113] A first calculation unit, configured to obtain preset marked privacy data from the database, and calculate a matching degree between the text data and the marked privacy data;

[0114] The second calculation unit is used to calculate the base sensitivity of the text data according to the matching degree and the benchmark score.

[0115] When it is determined that there is sensitive information in the text data, the base sensitivity of the text data is obtained, wherein the base sensitivity is used to measure the sensitivity of the text data. The base sensitivity can be determined by the benchmark score of the text data and other measurement parameters, such as the matching degree between the sensitive information in the current text information and the marked privacy data stored in the database and the risk score corresponding to the text information. When the base sensitivity of the text data is calculated, it is determined whether the base sensitivity is not less than the preset threshold. If the base sensitivity is not less than the preset threshold, the text data is desensitized; if the base sensitivity is less than the preset threshold, the text data is temporarily stored.

[0116] The detection module is used to send the sent data to the front-end page when it is determined that the sensitive information exists in the text data, detect whether the sent data is completely used by the front-end page, and if there is unused data in the front-end page, determine that the sent data is excessive and send an alarm prompt message.

[0117] Before desensitizing the text data, the issued data can also be sent to the front-end interface, and the issued data can be detected again based on the front-end interface to determine whether the issued data is provided in excess. When the issued data is provided in excess, there may also be a risk of sensitive information leakage. Specifically, when it is determined that there is sensitive information in the issued data, the issued data is sent to the front-end page, and it is detected whether the issued data is fully used by the front-end page. Traverse all the issued data through ajax, and then match the issued data through regular expressions, that is, match the issued data with the page data in the front-end page, and determine whether the issued data already exists in the front-end page. If it is fully matched, it means that it already exists, and the risk of leakage is less likely. The issued data that already exists in the front-end page is scored according to a preset scoring method, such as scoring according to the number of times it appears on the front-end page, and the higher the number, the higher the corresponding risk score. If the issued data is not matched in the front-end page, it is determined that the issued data is excessively provided by the current back-end interface, which means that the current issued data is not needed by the current front-end page. At this time, an alarm prompt message is sent to the control center or the designated target person to indicate that there may be a risk of sensitive text information leakage, and the risk score corresponding to the sent data that is not required by the current front-end page is obtained. At this time, the risk score is a preset value. When the risk score of the sent data is obtained, the risk score can be used as one of the measurement parameters of the base sensitivity, and the base sensitivity of the sent data is calculated based on the risk score. Specifically, the risk score is used as one of the measurement parameters of the base sensitivity, and combined with the matching degree and the benchmark score corresponding to the sent data, a comprehensive weighted calculation is performed to obtain the final base sensitivity.

[0118] A third confirmation module is used to determine whether the sent data is image data according to the data type when it is determined that the sent data is non-text data;

[0119] an extraction module, configured to extract image information and the use authority of an information provider from the image data when it is determined that the sent data is the image data, determine whether the image data includes sensitive information according to the image information and the use authority, and if the image data includes the sensitive information, mark and store the image data;

[0120] An identification module is used to identify the voice data in the audio data or the video data when it is determined that the sent data is audio data or video data, determine whether the voice data includes sensitive information, and if the voice data includes the sensitive information, mark and store the audio data or the video data.

[0121] The sent data includes text data, image data, audio data and video data. When the sent data is determined to be image data according to the data type of the sent data, the image information in the image data is extracted through the face recognition system, and the use authority of the information provider of the image data is obtained. If the image information matches the image information stored in the database, wherein the stored image information is all sensitive image information, and the use authority is unauthorized, it is determined that the image data includes sensitive information, the image data is marked as stored as sensitive image data, and an alarm prompt message is sent to prompt that the current image data contains sensitive image information; if the image information does not match the image information stored in the database, and the use authority is unauthorized, it is determined that the image data does not include sensitive information, and no alarm prompt message is sent. If the image information matches the image information stored in the database, and the use authority is authorized, it is determined that the image data includes sensitive information, and the image data is marked as stored but no alarm prompt message is sent; if the image information does not match the image information stored in the database, and the use authority is authorized, it is determined that the image data does not include sensitive information, and no alarm prompt message is sent.

[0122] When it is determined that the data to be sent is audio data or video data, the voice data in the audio data or video data is identified to determine whether the voice data includes sensitive information; specifically, the voice data in the audio data or video data is audio recognized to obtain text data corresponding to the voice data, so that it can be determined whether the corresponding voice data includes sensitive information according to whether the text data includes sensitive information. Among them, whether the text data includes sensitive information is the same as the process of judging whether the text data includes sensitive information according to the feature code. If the voice data includes sensitive information, the audio data or video data is also marked and stored, and an alarm prompt message is sent to prompt that there is voice sensitive information in the current audio data or video data. In addition, when the data to be sent is image data, audio data and video data, if there is text information in the image data, audio data and video data, the text information is extracted and processed according to the processing method of the above text data.

[0123] In this embodiment, intelligent determination of privacy data is achieved, the recognition efficiency and accuracy of privacy data are improved, the leakage of privacy information is reduced, and the security of personal information is protected.

[0124] To solve the above technical problems, the present application also provides a computer device. Figure 4 , Figure 4 This is a basic structural block diagram of the computer device in this embodiment.

[0125] The computer device 7 includes a memory 71, a processor 72, and a network interface 73 that are interconnected through a system bus. It should be noted that the figure only shows a computer device 7 with components 71-73, but it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (Application Specific Integrated Circuit, ASIC), programmable gate arrays (Field-Programmable Gate Array, FPGA), digital processors (Digital Signal Processor, DSP), embedded devices, etc.

[0126] The computer device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The computer device may interact with a user through a keyboard, a mouse, a remote controller, a touch pad, or a voice control device.

[0127] The memory 71 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 71 can be an internal storage unit of the computer device 7, such as a hard disk or memory of the computer device 7. In other embodiments, the memory 71 can also be an external storage device of the computer device 7, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (FlashCard), etc. equipped on the computer device 7. Of course, the memory 71 can also include both the internal storage unit of the computer device 7 and its external storage device. In this embodiment, the memory 71 is generally used to store the operating system and various application software installed on the computer device 7, such as the program code of the sensitive data detection method, etc. In addition, the memory 71 can also be used to temporarily store various types of data that have been output or are to be output.

[0128] The processor 72 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip in some embodiments. The processor 72 is generally used to control the overall operation of the computer device 7. In this embodiment, the processor 72 is used to run the program code stored in the memory 71 or process data, such as running the program code of the sensitive data detection method.

[0129] The network interface 73 may include a wireless network interface or a wired network interface. The network interface 73 is generally used to establish a communication connection between the computer device 7 and other electronic devices.

[0130] The computer device provided in this embodiment realizes intelligent determination of privacy data, improves the recognition efficiency and recognition accuracy of privacy data, reduces the leakage of privacy information, and protects the security of personal information.

[0131] The present application also provides another implementation, namely, providing a computer-readable storage medium, characterized in that computer-readable instructions are stored on the computer-readable storage medium, and the computer-readable instructions implement the steps of the above-mentioned sensitive data detection method when executed by a processor.

[0132] Furthermore, the program storage area may store an operating system, an application required for at least one function, etc.; the data storage area may store data created according to the use of the blockchain node, etc.

[0133] The computer-readable storage medium provided in this embodiment realizes the intelligent determination of privacy data, improves the recognition efficiency and recognition accuracy of privacy data, reduces the leakage of privacy information, and protects the security of personal information.

[0134] The blockchain referred to in this application is a new application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism, encryption algorithm, etc. Blockchain is essentially a decentralized database, a string of data blocks generated by cryptographic methods. Each data block contains a batch of network transaction information, which is used to verify the validity of its information (anti-counterfeiting) and generate the next block. Blockchain can include the underlying blockchain platform, platform product service layer, and application service layer.

[0135] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0136] Obviously, the embodiments described above are only some embodiments of the present application, rather than all embodiments. The preferred embodiments of the present application are given in the accompanying drawings, but they do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present application more thorough and comprehensive. Although the present application is described in detail with reference to the aforementioned embodiments, for those skilled in the art, it is still possible to modify the technical solutions recorded in the aforementioned specific implementation methods, or to perform equivalent replacement of some of the technical features therein. Any equivalent structure made using the contents of the specification and drawings of this application, directly or indirectly used in other related technical fields, is similarly within the scope of patent protection of this application.

Claims

1. A sensitive data detection method, characterized in that: The steps include: When receiving the sent data, obtaining the data type of the sent data, and determining whether the sent data is text data according to the data type; When it is determined that the sent data is the text data, detecting the text type of the text data, and determining a feature code corresponding to the text data according to the text type; Matching the feature code with a standard feature code stored in a database to determine whether sensitive information exists in the text data; When it is determined that the sensitive information exists in the text data, the base sensitivity of the text data is calculated, and the text data whose base sensitivity is not less than a preset threshold is desensitized; The step of matching the feature code with a standard feature code stored in a database to determine whether sensitive information exists in the text data includes: Identify keywords in the feature code through grammatical analysis, and obtain documents including the keywords according to a document list constructed based on standard feature codes stored in a database; Obtaining the correlation between the document and the feature code, and determining whether sensitive information exists in the text data according to the correlation; Among them, the feature code is matched and analyzed with the standard feature code pre-stored in the database through full-text retrieval analysis, the keywords in the feature code are identified through syntax analysis, and then the document including the keyword is determined according to the document link list constructed according to the standard feature code, and the correlation between the document and the feature code is scored and ranked, and the more relevant the document is, the higher it is, so as to determine whether there is a standard feature code matching the feature code of the current text data in the database. If the correlation of the top document is greater than or equal to the preset correlation value, it is determined that there is a standard feature code matching the feature code of the text data in the database, that is, it is determined that sensitive information exists in the text data; if the correlation of the top document is less than the preset correlation value, it is determined that there is no standard feature code matching the feature code of the text data in the database, that is, it is determined that there is no sensitive information in the text data.

2. The sensitive data detection method according to claim 1, characterized in that: The step of calculating the base sensitivity of the text data comprises: Obtaining a benchmark score for the text data; A base sensitivity of the text data is determined according to the benchmark score.

3. The sensitive data detection method according to claim 2, characterized in that: The step of determining the base sensitivity of the text data according to the benchmark score comprises: Acquire preset marked privacy data from the database, and calculate the matching degree between the text data and the marked privacy data; The base sensitivity of the text data is calculated according to the matching degree and the benchmark score.

4. The sensitive data detection method according to claim 1, characterized in that: The step of determining the feature code corresponding to the text data according to the text type comprises: The text type includes a digital type, a letter type and a character type. The text data is symbolized according to the text type, and the symbolized text data is a feature code corresponding to the text data.

5. The sensitive data detection method according to claim 1, characterized in that: After the step of determining whether sensitive information exists in the text data, the sensitive data detection method further includes: When it is determined that the sensitive information exists in the text data, the sent data is sent to the front-end page to detect whether the sent data is completely used by the front-end page. If there is unused data in the front-end page, it is determined that the sent data is excessive and an alarm prompt message is sent.

6. The sensitive data detection method according to claim 1, characterized in that: After the step of determining whether the sent data is text data according to the data type, the sensitive data detection further includes: When it is determined that the sent data is non-text data, determining whether the sent data is image data according to the data type; When it is determined that the sent data is the image data, extracting image information in the image data and the use authority of the information provider, determining whether the image data includes sensitive information according to the image information and the use authority, and if the image data includes the sensitive information, marking and storing the image data; When it is determined that the sent data is audio data or video data, the voice data in the audio data or the video data is identified, and it is determined whether the voice data includes sensitive information. If the voice data includes the sensitive information, the audio data or the video data is marked for storage.

7. A sensitive data detection device, characterized in that: include: A first confirmation module is used to obtain a data type of the sent data when receiving the sent data, and determine whether the sent data is text data according to the data type; an acquisition module, configured to detect a text type of the text data when determining that the sent data is the text data, and determine a feature code corresponding to the text data according to the text type; A second confirmation module is used to match the feature code with a standard feature code stored in a database to determine whether sensitive information exists in the text data; A desensitization module, for calculating the base sensitivity of the text data when it is determined that the sensitive information exists in the text data, and performing desensitization processing on the text data whose base sensitivity is not less than a preset threshold; The second confirmation module further includes: an analysis unit, which is used to identify keywords in the feature code through grammatical analysis, and obtain documents including the keywords according to a document list constructed based on standard feature codes stored in a database; a first confirmation unit, which is used to obtain the correlation between the document and the feature code, and determine whether sensitive information exists in the text data according to the correlation; Among them, the feature code is matched and analyzed with the standard feature code pre-stored in the database through full-text retrieval analysis, the keywords in the feature code are identified through syntax analysis, and then the document including the keyword is determined according to the document link list constructed according to the standard feature code, and the correlation between the document and the feature code is scored and ranked, and the more relevant the document is, the higher it is, so as to determine whether there is a standard feature code matching the feature code of the current text data in the database. If the correlation of the top document is greater than or equal to the preset correlation value, it is determined that there is a standard feature code matching the feature code of the text data in the database, that is, it is determined that sensitive information exists in the text data; if the correlation of the top document is less than the preset correlation value, it is determined that there is no standard feature code matching the feature code of the text data in the database, that is, it is determined that there is no sensitive information in the text data.

8. A computer device comprising a memory and a processor, wherein the memory stores computer-readable instructions, and the processor implements the steps of the sensitive data detection method as described in any one of claims 1 to 6 when executing the computer-readable instructions.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the steps of the sensitive data detection method according to any one of claims 1 to 6.

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