Network data security detection system

Abstract

The invention discloses a network data security detection system, and relates to the technical field of data security detection. The system comprises a data acquisition unit, an initial processing unit, a target data processing unit and a storage unit. According to the method, the target data is acquired through the data acquisition unit, the quantitative information of the target data is extracted, the initial processing unit performs initial processing according to the quantitative information of the target data, and the confidentiality level of the target data is acquired; the target data processing unit performs mapping processing according to the secrecy level of the target data, and replaces the feature characters with mapping characters to form secure secrecy data; the storage unit is used for storing the security and confidentiality data in a classified manner according to different confidentiality levels; the verification unit performs security detection on a user reading the target data, so that the security protection level of the data is improved, specific information content is accurately identified, and the accuracy of information identification, extraction and processing of the target data is greatly improved; and information security can be protected, and information loss is avoided.

Description

Technical Field

[0001] The invention belongs to the technical field of data security detection, and in particular relates to a network data security detection system. Background Art

[0002] In the network security business, common network security threats include: information leakage, information theft, data tampering, data deletion, computer viruses, etc. The unpredictability and concealment of network security attacks make the attacks more rampant and destructive in the entire network. Network data information security has become a common focus of attention in all countries around the world. The main manifestations are:

[0003] First: There is a lack of efficient and accurate monitoring technology for cyber crimes such as information leakage, tampering, and system intrusion;

[0004] Second: There are generally problems such as limited technology and management level, weak network security protection capabilities, etc., and their website servers have become the "hardest hit areas" of attacks;

[0005] Third: While carrying out security control for confidential data, it is impossible to quickly detect and analyze various network data information, data processing is difficult, and there are problems such as untimely, low efficiency and errors in information processing.

[0006] For example, Chinese patent CN118133296A provides a virtual-real combination of industrial Internet information security inspection and testing platform. The platform consists of the following parts: platform basic support system, platform resource system, network and environment simulation system, behavior simulation system, data acquisition system, situation awareness and evaluation system, platform operation and maintenance guarantee system, inspection and testing configuration and management system. By building an inspection and testing simulation network in a virtual-real combination and interconnecting it with the physical network, the platform can simulate a real business network and realize the inspection, testing, verification and continuous improvement of industrial Internet equipment and network information security. Through this platform, it is possible to avoid the damage of information security detection to real equipment and business networks, providing an effective method for industrial Internet information security.

[0007] For example, Chinese patents CN117336097A, CN111740976A, CN115378744A, etc. all use a method of preventing network attacks to ensure network data security, but lack an active way to implement data security analysis, detection and processing to avoid information leakage and other problems caused by network security.

[0008] Therefore, whether it is possible to proactively and effectively respond to various security incidents and proactively prevent target data loss has become one of the key tasks of network security supervision. This application specifically provides a network data security detection system. Summary of the invention

[0009] The purpose of the present invention is to provide a network data security detection system, which solves the existing problems by analyzing the level of target data and the characteristics of the target data itself and performing security detection in combination with the identity level of the reading user.

[0010] To solve the above technical problems, the present invention is achieved through the following technical solutions:

[0011] The present invention is a network data security detection system, comprising:

[0012] A data acquisition unit, the data acquisition unit is used to acquire target data and extract quantitative information of the target data, the quantitative information includes: confidentiality level of the target data, readers (people who want to read the target information or administrators who mark the level of the target data), marking information (i.e., information about the administrator marking the level of the preliminary data);

[0013] A primary processing unit, wherein the primary processing unit performs primary processing according to the quantitative information of the target data to obtain the confidentiality level of the target data;

[0014] A target data processing unit, wherein the target data processing unit performs mapping processing according to the confidentiality level of the target data, replaces the characteristic characters with mapping characters, and forms secure and confidential data;

[0015] A storage unit, wherein the storage unit stores security and confidentiality data in a classified manner according to different confidentiality levels;

[0016] A verification unit is used to perform security detection on a user who reads the target data.

[0017] Furthermore, the initial processing unit includes:

[0018] Data extraction set, which is used to extract any target data and marked as preliminary data;

[0019] The traceability set is used to obtain the administrator who reads the preliminary data and marks the level of the preliminary data, marks it as a direct administrator, and obtains the identity level corresponding to the direct administrator. The identity level is divided into initial level, intermediate level and advanced level;

[0020] Level extraction set, which is used to obtain the confidentiality level set by the direct administrator for the target data. The confidentiality level is divided into initial level, intermediate level and advanced level;

[0021] The historical data extraction set is used to obtain the confidentiality level set by the direct administrator for all target data in the recent T1 period, which is marked as a level aggregate;

[0022] Historical data analysis set, which is used to judge the preliminary rationality of the preliminary data classification based on the data rules within the grade set;

[0023] The preliminary processing set is used to mark the confidentiality level of preliminary data with preliminary rationality > X1 as confidentiality level. If the preliminary rationality is ≤ X1, the intermediate and senior administrators jointly set the confidentiality level for the preliminary data;

[0024] Among them, T1 and X1 are preset values.

[0025] Furthermore, the historical data analysis set includes:

[0026] The confidentiality level conversion subset is used to obtain the confidentiality level corresponding to all target data in the level set, and convert the confidentiality level data respectively, and convert the initial level, intermediate level and advanced level to X2, X3 and X4 respectively, and X2<X3<X4; the level set after data conversion is marked as L{L1, L2, L3, ..., Lm}, where m is a positive integer;

[0027] The confidential analysis subset is used to calculate the average value of all data in the level set L, which is marked as the evaluation average value Lp1;

[0028] The historical analysis subset is used to obtain the corresponding level aggregates of all other administrators in the recent T1 time, marked as the comparison large aggregate, and calculate the average value of all data in the comparison large aggregate (calculated according to the calculation principle of the evaluation average value Lp1), marked as the comparison average value Lp;

[0029] Determine the subset, which is used to:

[0030] When the administrator's status level is classified as beginner or intermediate:

[0031] If Lp1<Lp, and Up1<Up or if Lp>Lp, and Up1<Up, then select X5 smallest values ​​and X5 largest values ​​from the level set, and obtain the corresponding target data, marked as the target data group Bj, j=1, 2, 3, ......, 2*X5, and obtain preliminary rationality according to the characteristics of the target data group;

[0032] Otherwise, Lp1*X4+Lp*X2 is taken as the preliminary rationality;

[0033] When the administrator's identity level is divided into advanced level:

[0034] If Lp1<Lp, and Up1≥Up, then select X5 smallest values ​​and X5 largest values ​​from the level set, and obtain the corresponding target data, marked as the target data group Bj, j=1, 2, 3, ..., 2*X5, and obtain preliminary rationality according to the characteristics of the target data group;

[0035] Otherwise, Lp1*X2+Lp*X3 is taken as the preliminary rationality;

[0036] Among them, X2, X3, X4, and X5 are all preset values, Up1 and Up are the standard deviations of the data in the corresponding level set, X5 is a positive integer and 2*X5<m.

[0037] Furthermore, the following steps are performed when the judgment subset obtains preliminary rationality:

[0038] Extract the X6 group of feature words in the target data group: re-arrange the elements in the target data group Bj from large to small to form a sequence BL t , t=1, 2, 3, ..., 2*X5, calculate the average value LU of all elements, and take the integer part of LU. If the integer part of LU is an even number, then take out X6 elements with even t in turn. If the integer part of LU is an odd number, then take out X6 elements with odd t in turn. Mark the taken elements as feature elements, obtain the target data corresponding to the feature elements, and respectively obtain the feature words in the target data that are the same as the feature words in the database to obtain X6 groups of feature words; if there are less than X6 elements, take out all the elements;

[0039] Target data with a matching degree of more than 90% with the feature words of group X6 are selected from the database and marked as the comparison data group;

[0040] Obtain the confidentiality level and the average value corresponding to the target data group, the confidentiality level and the average value corresponding to the confidentiality level corresponding to the comparison data group, and mark the obtained average values ​​as BP1 and BP2 respectively.

[0041] If |BP1-BP2|≤BP, then BL2*X4+BL 2*X5 *X as preliminary plausibility;

[0042] Otherwise, BL 2*X5 As a preliminary rationale;

[0043] X6 and BP are preset values, and X6 is a positive integer.

[0044] Furthermore, the target data processing unit performs the following steps when performing mapping processing according to the confidentiality level of the target data:

[0045] Perform character segmentation processing on the target data, divide the target data into several character paragraphs, each character paragraph contains several characters, obtain the number of occurrences of each character paragraph, and simultaneously divide a common character, which is pre-set and is the most frequently used character in the corresponding field, but does not contain technical content (that is, a character that does not disclose secrets);

[0046] The character paragraph after removing the common characters is marked as a characteristic character, and the characteristic characters whose occurrence times exceed the preset value C1 are marked as replacement characters;

[0047] The replacement character is represented by a graphic element in the form of a quantized value, and the graphic element is marked as a mapping character;

[0048] Establish a mapping relationship between mapping characters and replacement characters;

[0049] The common characters of the target data are retained, and the replacement characters are replaced with mapping characters to form new target data, which are marked as secure and confidential data;

[0050] The above encryption and decryption methods only exist on the set smart devices, which are automatically encrypted and decrypted using the encrypted direction method for matching. When sharing, the user's identity must be authenticated before the decryption method on the matching smart device can be called. Even if the user's password is stolen on other devices, the decryption method cannot be used.

[0051] Furthermore, the replacement character is expressed in a quantitative form using other elements:

[0052] Get a quantized value corresponding to the replacement character, each character corresponds to a quantized value;

[0053] Assigning a quantitative value to a graphic element;

[0054] The mapping method is: the quantized value is consistent with a certain value of the graphic element;

[0055] The graphic element is a circle, a square or other shapes, and a certain value of the graphic element is a perimeter or an area, etc.

[0056] Furthermore, the verification unit performs the following steps when performing security detection:

[0057] Get the identity level of the user who wants to read the target data;

[0058] Get the confidentiality level of the target data you want to read;

[0059] If the identity level matches the confidentiality level, the security check passes, the verification unit grants the corresponding user reading authority, and sends the storage location of the target data;

[0060] Otherwise, the safety test fails.

[0061] Furthermore, the storage unit stores the security and confidentiality data in categories in:

[0062] For security and confidentiality data with an initial confidentiality level, it is stored in the primary storage module;

[0063] For security and confidentiality data with a medium confidentiality level, it is stored in the secondary storage module;

[0064] For security and confidentiality data with a high confidentiality level, it is stored in the third-level storage module;

[0065] The first-level storage module, the second-level storage module, and the third-level storage module are preset storage modules, and the security levels increase in sequence (here, the existing technology is used to encrypt or otherwise process the storage module so that the security level of the storage module meets the requirements).

[0066] The present invention has the following beneficial effects:

[0067] The present invention acquires target data through a data acquisition unit, and extracts quantitative information of the target data; the initial processing unit performs preliminary processing according to the quantitative information of the target data to acquire the confidentiality level of the target data; the target data processing unit performs mapping processing according to the confidentiality level of the target data, replaces characteristic characters with mapping characters, and forms secure and confidential data; the storage unit stores the secure and confidential data in categories according to different confidentiality levels; the verification unit performs security detection on users who read the target data, improves the security protection level of the data, accurately identifies specific information content, and greatly improves the accuracy of identifying, extracting, and processing target data information; and can protect information security to avoid information loss.

[0068] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for describing the embodiments are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0070] Figure 1 A structural diagram of a network data security detection system of the present invention;

[0071] Figure 2 is a structural diagram of the primary processing unit of the present invention;

[0072] Figure 3It is a structural diagram of the historical data analysis set of the present invention. DETAILED DESCRIPTION

[0073] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0074] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0075] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0076] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0077] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0078] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0079] Embodiment 1:

[0080] As an embodiment provided by the present invention, preferably, please refer to Figure 1-3 As shown, the present invention is a network data security detection system, comprising: a data acquisition unit initial processing unit, a target data processing unit, a storage unit, and a verification unit, wherein the data acquisition unit initial processing unit, the target data processing unit, the storage unit, and the verification unit are all connected to the processor in communication, specifically:

[0081] A data acquisition unit is used to acquire target data and extract quantitative information of the target data (i.e., all data analyzed and processed by the system or data marked by the administrator or sensitive data identified by the prior art), the quantitative information includes: confidentiality level of the target data (the confidentiality level here is the level set by the administrator for the target data for the first time, which has not yet been tested for security), readers (including administrators, persons who want to read the target data, etc.), marking information (information of the administrator marking the level of the preliminary data);

[0082] The initial processing unit performs initial processing according to the quantitative information of the target data to obtain the confidentiality level of the target data (the confidentiality level here is the confidentiality level obtained after the administrator sets the level for the target data for the first time and undergoes initial processing, that is, the confidentiality level after security testing);

[0083] A target data processing unit performs mapping processing according to the confidentiality level of the target data, replaces the characteristic characters with mapping characters, and forms secure and confidential data;

[0084] A storage unit that stores security and confidentiality data in categories according to different confidentiality levels;

[0085] The verification unit is used to perform security detection on the user who reads the target data.

[0086] As an embodiment provided by the present invention, preferably, the initial processing unit includes:

[0087] Data extraction set, which is used to extract any target data and marked as preliminary data;

[0088] The traceability set is used to obtain the administrator who reads the preliminary data and marks the level of the preliminary data, marks it as a direct administrator, and obtains the identity level corresponding to the direct administrator. The identity level is divided into initial level, intermediate level and advanced level;

[0089] Level extraction set, which is used to obtain the confidentiality level set by the direct administrator for the target data. The confidentiality level is divided into initial level, intermediate level and advanced level;

[0090] The historical data extraction set is used to obtain the confidentiality level set by the direct administrator for all target data in the recent T1 period, which is marked as a level aggregate;

[0091] Historical data analysis set, which is used to judge the preliminary rationality of the preliminary data classification based on the data rules within the grade set;

[0092] The preliminary processing set is used to mark the confidentiality level of preliminary data with preliminary rationality > X1 as confidentiality level. If the preliminary rationality is ≤ X1, the intermediate and senior administrators jointly set the confidentiality level for the preliminary data;

[0093] Among them, T1 and X1 are preset values.

[0094] As an embodiment provided by the present invention, preferably, the initial processing unit performs the following steps when performing the initial rationality analysis:

[0095] Step S1: extract any target data and mark it as preliminary data;

[0096] Step S2: Obtain an administrator who reads the preliminary data and marks the level for the preliminary data, mark it as a direct administrator, and obtain the identity level corresponding to the direct administrator, which is divided into initial level, intermediate level and advanced level; for example, for the target data "network security protection level requirements to achieve the protection level to meet the purpose of being invulnerable, that is, the protection level reaches level 1", the administrator whose identity level is marked as "advanced level" is divided into initial level, here, the administrator is the first administrator to see the target data, that is, the first administrator to see the target data must set the level for the target data he sees;

[0097] Step S3: Obtain the confidentiality level set by the direct administrator for the target data, which is divided into initial level, intermediate level and advanced level;

[0098] Step S4: Obtain the confidentiality level set by the direct administrator for all target data in the recent T1 time, and mark it as a level aggregate. For example, the level aggregate includes the confidentiality levels set for different target data. The elements in the level aggregate are: initial level, intermediate level, intermediate level, advanced level, intermediate level, initial level. In this application, the mutual difference and disorder of the set are not considered, that is, it can be repeated and sorted, just for the convenience of expression using the concept of set;

[0099] Step S5: judging the preliminary rationality of the preliminary data level division according to the data rules in the level aggregate;

[0100] The confidentiality level of preliminary data with preliminary rationality > X1 is marked as confidentiality level. If preliminary rationality ≤ X1, the intermediate and senior administrators jointly set the confidentiality level for the preliminary data;

[0101] Among them, T1 and X1 are preset values

[0102] As an embodiment provided by the present invention, preferably, the historical data analysis set includes:

[0103] The confidentiality level conversion subset is used to obtain the confidentiality level corresponding to all target data in the level set, and convert the confidentiality level data respectively. The initial level, intermediate level and advanced level are converted to X2, X3 and X4 respectively, and X2<X3<X4; the level set after data conversion is marked as L{L1, L2, L3, …, Lm}, where m is a positive integer; if X2=2, X3=3, X4=4, then the elements in the level set are: initial level, intermediate level, intermediate level, advanced level, intermediate level, initial level. After data conversion, the level set is marked as L{2, 3, 3, 4, 3, 2}

[0104] The confidential analysis subset is used to calculate the average value of all data in the level set L, which is marked as the evaluation average value Lp1;

[0105] The historical analysis subset is used to obtain the corresponding level aggregate of all other administrators in the recent T1 time, marked as the comparison large aggregate, and calculate the average value of all data in the comparison large aggregate (calculated according to the calculation principle of the evaluation average value Lp1), marked as the comparison average value Lp; for example, the elements in the level aggregate corresponding to all other administrators in the recent T1 time are: initial level, intermediate level, intermediate level, senior level, intermediate level, initial level, initial level, intermediate level, intermediate level, senior level, intermediate level, initial level, initial level, intermediate level, intermediate level, senior level, intermediate level, initial level, then after data conversion, the comparison large aggregate is {2, 3, 3, 4, 3, 2, 2, 3, 3, 4, 3, 2, 2, 3, 3, 4, 3, 2};

[0106] Determine the subset, which is used to:

[0107] When the administrator's status level is classified as beginner or intermediate:

[0108] If Lp1<Lp, and Up1<Up or if Lp>Lp, and Up1<Up, then select X5 smallest values ​​and X5 largest values ​​from the level set, and obtain the corresponding target data, marked as the target data set Bj, j=1, 2, 3, ......, 2*X5, and obtain preliminary rationality according to the characteristics of the target data set; if 2*X5 elements are not satisfied, then all elements in the level set are taken out as the target data set;

[0109] Otherwise, Lp1*X4+Lp*X2 is taken as the preliminary rationality;

[0110] When the administrator's identity level is divided into advanced level:

[0111] If Lp1<Lp, and Up1≥Up, then select X5 smallest values ​​and X5 largest values ​​from the level set, and obtain the corresponding target data, marked as the target data set Bj, j=1, 2, 3, ..., 2*X5, and obtain preliminary rationality according to the characteristics of the target data set; if 2*X5 elements are not satisfied, then all elements in the level set are taken out as the target data set;

[0112] Otherwise, Lp1*X2+Lp*X3 is taken as the preliminary rationality;

[0113] Among them, X2, X3, X4, and X5 are all preset values, Up1 and Up are the standard deviations of the data in the corresponding level set, X5 is a positive integer and 2*X5<m.

[0114] As an embodiment provided by the present invention, preferably, the following steps are performed when the determination subset obtains preliminary rationality:

[0115] Extract the X6 group of feature words in the target data group: re-arrange the elements in the target data group Bj from large to small to form a sequence BL t , t=1, 2, 3, ..., 2*X5, calculate the average value LU of all elements, and take the integer part of LU. If the integer part of LU is an even number, then take out X6 elements with even t in turn. If the integer part of LU is an odd number, then take out X6 elements with odd t in turn. Mark the taken elements as feature elements, obtain the target data corresponding to the feature elements, and respectively obtain the feature words in the target data that are the same as the feature words in the database to obtain X6 groups of feature words; if there are less than X6 elements, take out all the elements;

[0116] The target data with a matching degree of more than 90% with the characteristic words of group X6 are respectively screened out from the database by the processor and marked as a comparison data group;

[0117] Obtain the confidentiality level and the average value corresponding to the target data group, the confidentiality level and the average value corresponding to the confidentiality level corresponding to the comparison data group, and mark the obtained average values ​​as BP1 and BP2 respectively.

[0118] If |BP1-BP2|≤BP, then BL2*X4+BL 2*X5 *X as preliminary plausibility;

[0119] Otherwise, BL 2*X5 As a preliminary rationale;

[0120] X6 and BP are preset values, and X6 is a positive integer.

[0121] As an embodiment provided by the present invention, preferably, the target data processing unit performs the following steps when performing mapping processing according to the confidentiality level of the target data:

[0122] Perform character segmentation processing on the target data, divide the target data into several character segments (it can be divided into two characters per segment or other existing character segmentation methods), each character segment contains several characters, obtain the number of occurrences of each character segment, and simultaneously divide a common character;

[0123] As an embodiment provided by the present invention, preferably, the commonly used characters are pre-set and are characters that are most frequently used in the corresponding field but do not contain technical content (that is, characters that do not disclose secrets);

[0124] The character paragraph after removing the common characters is marked as a characteristic character, and the characteristic characters whose occurrence times exceed the preset value C1 are marked as replacement characters;

[0125] The replacement character is represented by the number of characters or the graphic element in the form of a quantified value, and the graphic element is marked as a mapped character;

[0126] Establish a mapping relationship between mapping characters and replacement characters;

[0127] The common characters of the target data are retained, and the alternative characters are replaced with mapping characters to form new target data, which are marked as secure and confidential data.

[0128] As an embodiment provided by the present invention, preferably, the replacement character is expressed in a quantified form using the number of characters or other elements as follows:

[0129] Get a quantized value corresponding to the replacement character, each character corresponds to a quantized value;

[0130] Assigning a quantitative value to a graphic element;

[0131] The mapping method is: the quantized value is consistent with a certain value of the graphic element;

[0132] The graphic elements are circles, squares or other shapes;

[0133] A certain value of the graphic element is a perimeter or an area, etc.

[0134] As an embodiment provided by the present invention, preferably, the verification unit performs the following steps when performing security detection:

[0135] Get the identity level of the user who wants to read the target data;

[0136] Get the confidentiality level of the target data you want to read;

[0137] If the identity level matches the confidentiality level, the security check passes, the verification unit grants the corresponding user reading authority, and sends the storage location of the target data;

[0138] Otherwise, the safety test fails.

[0139] As an embodiment provided by the present invention, preferably, the storage unit stores the security and confidentiality data in categories in:

[0140] For security and confidentiality data with an initial confidentiality level, it is stored in the primary storage module;

[0141] For security and confidentiality data with a medium confidentiality level, it is stored in the secondary storage module;

[0142] For security and confidentiality data with a high confidentiality level, it is stored in the third-level storage module;

[0143] The first-level storage module, the second-level storage module, and the third-level storage module are preset storage modules, and the security levels increase in sequence.

[0144] As an embodiment provided by the present invention, preferably, the storage module is encrypted or otherwise processed using existing technologies so that the security level of the storage module meets the requirements.

[0145] Embodiment 2:

[0146] As the second embodiment provided by the present invention, preferably, based on embodiment one, the above encryption and decryption method only exists on the set smart device, which is automatically encrypted and decrypted using the encrypted direction method for matching. When sharing, the user's identity must be authenticated before the decryption method on the corresponding smart device can be called. Even if the user's password is stolen on other devices, the decryption method cannot be used.

[0147] Embodiment three:

[0148] As the third embodiment provided by the present invention, preferably, based on embodiments one and two, the present invention is a network data security detection system. Therefore, in the subsequent reading process of the target data, the system still provides a method for continuous data security detection, continuously performs security detection on the data, and promptly corrects the sensitive target data to data with a higher confidentiality level.

[0149] As an embodiment provided by the present invention, preferably, the initial processing unit performs initial processing according to the quantitative information of the target data, and further performs the following steps when obtaining the confidentiality level of the target data:

[0150] When the preliminary rationality is ≤X1, the confidentiality level set for the target data by the intermediate and senior administrators will be marked as the verified confidentiality level;

[0151] Select a verification confidentiality level. When the verification confidentiality level is marked with time T30, extract the preliminary data corresponding to the verification confidentiality level and mark it as data to be analyzed. T30 is the preset value.

[0152] Extract quantitative information corresponding to the data to be analyzed;

[0153] Obtain the reading levels of all users who have read the data to be analyzed based on the quantitative information; the reading levels include elementary readability, intermediate readability, and advanced readability;

[0154] Obtain the encryption weights assigned to the data to be analyzed by all users who have read the data to be analyzed, where the encryption weights corresponding to primary readable, intermediate readable, and advanced readable users are QZ1, QZ2, and QZ3 respectively;

[0155] Get the total encrypted weight, and mark the total encrypted weight after the following cumulative multiplication or accumulation as the total encrypted weight:

[0156] Each time a high-level readable user reads the document, the encryption weight will be multiplied by QZ3.

[0157] Each time an intermediate readable user reads the document, the encryption weight will be increased by QZ2.

[0158] Each time a primary readable user reads the data, the encryption weight will be increased by -QZ0.

[0159] When the total encryption weight is greater than QZ, the preset administrator will set the confidentiality level for the data to be analyzed. Otherwise, the confidentiality level set by the intermediate and senior administrators for the target data will continue to be maintained;

[0160] Among them, -QZ0, QZ1, QZ2, QZ3, QZ are all preset values, and -QZ0<QZ1<QZ2<QZ3

[0161] A network data security detection system obtains target data through a data acquisition unit and extracts quantitative information of the target data; a preliminary processing unit performs preliminary processing according to the quantitative information of the target data to obtain the confidentiality level of the target data; a target data processing unit performs mapping processing according to the confidentiality level of the target data, replaces characteristic characters with mapping characters, and forms secure and confidential data; a storage unit stores secure and confidential data in categories according to different confidentiality levels; a verification unit performs security detection on users who read the target data, improves the security protection level of the data, accurately identifies specific information content, and greatly improves the accuracy of identifying, extracting, and processing target data information; and can protect information security and avoid information loss.

[0162] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0163] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A network data security detection system, characterized in that: include: A data acquisition unit, which is used to acquire target data and extract quantitative information of the target data, the quantitative information including: confidentiality level of the target data, reader, and marking information; A primary processing unit, which performs preliminary processing according to the quantitative information of the target data to obtain the confidentiality level of the target data; A target data processing unit performs mapping processing according to the confidentiality level of the target data, replaces the characteristic characters with mapping characters, and forms secure and confidential data; A storage unit that stores security and confidentiality data in categories according to different confidentiality levels; The verification unit is used to perform security detection on the user who reads the target data.

2. A network data security detection system according to claim 1, characterized in that: The initial processing unit comprises: Data extraction set, which is used to extract any target data and marked as preliminary data; The traceability set is used to obtain the administrator who reads the preliminary data and marks the level of the preliminary data, marks it as a direct administrator, and obtains the identity level corresponding to the direct administrator. The identity level is divided into initial level, intermediate level and advanced level; Level acquisition set, which is used to obtain the confidentiality level set by the direct administrator for the target data. The confidentiality level is divided into initial level, intermediate level and advanced level; The historical data extraction set is used to obtain the confidentiality level set by the direct administrator for all target data in the recent T1 period, which is marked as a level aggregate; Historical data analysis set, which is used to judge the preliminary rationality of the preliminary data classification based on the data rules within the grade set; The preliminary processing set is used to mark the confidentiality level of preliminary data with preliminary rationality > X1 as confidentiality level. If the preliminary rationality is ≤ X1, the intermediate and senior administrators jointly set the confidentiality level for the preliminary data; Among them, T1 and X1 are preset values.

3. A network data security detection system according to claim 2, characterized in that: The historical data analysis set includes: The confidentiality level conversion subset is used to obtain the confidentiality level corresponding to all target data in the level set, and convert the confidentiality level data respectively, and convert the initial level, intermediate level and advanced level to X2, X3 and X4 respectively, and X2<X3<X4; the level set after data conversion is marked as L{L1, L2, L3, ..., Lm}, where m is a positive integer; The confidential analysis subset is used to calculate the average value of all data in the level set L, which is marked as the evaluation average value Lp1; The historical analysis subset is used to obtain the corresponding level aggregates of all other administrators in the recent T1 time, marked as the comparison large aggregate, and calculate the average value of all data in the comparison large aggregate, marked as the comparison average value Lp; Determine the subset, which is used to: When the administrator's status level is classified as beginner or intermediate: If Lp1<Lp, and Up1<Up or if Lp>Lp, and Up1<Up, then select X5 smallest values ​​and X5 largest values ​​from the level set, and obtain the corresponding target data, marked as the target data group Bj, j=1, 2, 3, ......, 2*X5, and obtain preliminary rationality according to the characteristics of the target data group; Otherwise, Lp1*X4+Lp*X2 is taken as the preliminary rationality; When the administrator's identity level is divided into advanced level: If Lp1<Lp, and Up1≥Up, then select X5 smallest values ​​and X5 largest values ​​from the level set, and obtain the corresponding target data, marked as the target data group Bj, j=1, 2, 3, ..., 2*X5, and obtain preliminary rationality according to the characteristics of the target data group; Otherwise, Lp1*X2+Lp*X3 is taken as the preliminary rationality; Among them, X2, X3, X4, and X5 are all preset values, Up1 and Up are the standard deviations of the data in the corresponding level set, X5 is a positive integer and 2*X5<m.

4. A network data security detection system according to claim 3, characterized in that: The following steps are performed when the judgment subset obtains preliminary rationality: Extract the X6 group of feature words in the target data group: re-arrange the elements in the target data group Bj from large to small to form a sequence BL t , t=1, 2, 3, ..., 2*X5, calculate the average value LU of all elements, and take the integer part of LU. If the integer part of LU is an even number, then take out X6 elements whose t is an even number in sequence. If the integer part of LU is an odd number, then take out X6 elements whose t is an odd number in sequence, mark the taken elements as feature elements, obtain the target data corresponding to the feature elements, respectively obtain the feature words in the target data that are the same as the feature words in the database, and obtain X6 groups of feature words; If there are less than X6 elements, all elements will be taken out; The processor selects target data with a matching degree of more than 90% with the feature words of group X6 from the database and marks them as comparison data groups; Obtain the confidentiality level and the average value corresponding to the target data group, the confidentiality level and the average value corresponding to the confidentiality level corresponding to the comparison data group, and mark the obtained average values ​​as BP1 and BP2 respectively. If |BP1-BP2|≤BP, then BL2*X4+BL 2*X5 *X as preliminary plausibility; Otherwise, BL 2*X5 As a preliminary rationality; X6 and BP are preset values, and X6 is a positive integer.

5. A network data security detection system according to claim 1, characterized in that: The target data processing unit performs the following steps when mapping the target data according to the confidentiality level of the target data: Perform character segmentation processing on the target data, divide the target data into several character paragraphs, each character paragraph contains several characters, obtain the number of occurrences of each character paragraph, and simultaneously divide a common character, wherein the common character is pre-set and is the character that is most frequently used in the corresponding field but does not contain technical content; The character paragraph after removing the common characters is marked as a characteristic character, and the characteristic characters whose occurrence times exceed the preset value C1 are marked as replacement characters; The replacement character is represented by a graphic element in the form of a quantized value, and the graphic element is marked as a mapping character; Establish a mapping relationship between mapping characters and replacement characters; The common characters of the target data are retained, and the alternative characters are replaced with the mapping characters to form new target data, which are marked as secure and confidential data.

6. A network data security detection system according to claim 1, characterized in that: The quantified form of the replacement character is expressed as: Get a quantized value corresponding to the replacement character, each character corresponds to a quantized value; Assigning a quantitative value to a graphic element; The mapping method is: the quantized value is consistent with a certain value of the graphic element; The graphic element is a circle or a square, and a certain value of the graphic element is a perimeter or an area.

7. A network data security detection system according to claim 1, characterized in that: The verification unit performs the following steps when performing security detection: Get the identity level of the user who wants to read the target data; Get the confidentiality level of the target data you want to read; If the identity level matches the confidentiality level, the security check passes, the verification unit grants the corresponding user reading authority, and sends the storage location of the target data; Otherwise, the safety test fails.

8. A network data security detection system according to claim 1, characterized in that: The storage unit stores the security and confidentiality data in categories: For security and confidentiality data with an initial confidentiality level, it is stored in the primary storage module; For security and confidentiality data with a medium confidentiality level, it is stored in the secondary storage module; For security and confidentiality data with a high confidentiality level, it is stored in the third-level storage module; The first-level storage module, the second-level storage module, and the third-level storage module are preset storage modules, and the security levels increase in sequence.

9. A network data security detection system according to claim 1, characterized in that: The initial processing unit performs initial processing according to the quantitative information of the target data, and further performs the following steps when obtaining the confidentiality level of the target data: When the preliminary rationality is ≤X1, the confidentiality level set for the target data by the intermediate and senior administrators will be marked as the verified confidentiality level; Select a verification confidentiality level. When the verification confidentiality level is marked with time T30, extract the preliminary data corresponding to the verification confidentiality level and mark it as data to be analyzed. T30 is the preset value. Extract quantitative information corresponding to the data to be analyzed; Obtain the reading levels of all users who have read the data to be analyzed based on the quantitative information; the reading levels include elementary readability, intermediate readability, and advanced readability; Obtain the encryption weights assigned to the data to be analyzed by all users who have read the data to be analyzed, where the encryption weights corresponding to primary readable, intermediate readable, and advanced readable users are QZ1, QZ2, and QZ3 respectively; Get the total encrypted weight, and mark the total encrypted weight after the following cumulative multiplication or accumulation as the total encrypted weight: Each time a high-level readable user reads the document, the encryption weight will be multiplied by QZ3. Each time an intermediate readable user reads the document, the encryption weight will be increased by QZ2. Each time a primary readable user reads the data, the encryption weight will be increased by -QZ0. When the total encryption weight is greater than QZ, the preset administrator will set the confidentiality level for the data to be analyzed. Otherwise, the confidentiality level set by the intermediate and senior administrators for the target data will continue to be maintained; Among them, -QZ0, QZ1, QZ2, QZ3, and QZ are all preset values, and -QZ0<QZ1<QZ2<QZ3.

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