Personnel information management system based on block chain

Abstract

The invention relates to the technical field of personnel information management, in particular to a personnel information management system based on a block chain, and the system comprises the following steps: S1, obtaining user information in a personnel file system; s2, processing the user information through user information anti-interference processing; s3, performing security detection and defense on the user information through an information security processing algorithm; and S4, storing the user data subjected to security processing. According to the invention, user information is subjected to anti-interference processing and safety processing, so that the anti-interference capability of user information processing in the personnel archive system is improved, the safety and reliability of information processing are ensured, and meanwhile, the defense capability of the system is improved by monitoring and defending data of each module through the safety defense module; and the security of the user information is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of personnel information management, and in particular to a personnel information management system based on blockchain. Background Art

[0002] In recent years, the big data + personnel information management model has further improved the utilization rate of personnel information management resources and the intelligence level of personnel information management services. However, the security risks of communication networks increase the probability of attacks on important data information related to personnel information management services, and introduce some problems that need to be improved, such as user information security processing problems. How to improve the above problems and other threats is a technical problem that needs to be solved urgently.

[0003] The information security processing methods in the prior art focus on unilaterally processing user information securely or avoiding intrusion attacks, and cannot ensure the security of the environment in which the user information is located while ensuring the secure and efficient processing of user information. The present invention monitors external attacks while securely processing user information and takes defensive measures in a timely manner to improve the security and reliability of user information. Summary of the invention

[0004] The purpose of the present invention is to solve the defects mentioned in the above-mentioned background technology by proposing a personnel information management system based on blockchain.

[0005] The technical solution adopted by the present invention is as follows:

[0006] Provide a blockchain-based personnel information management system, which includes the following steps:

[0007] S1: Obtain user information in the personnel file system;

[0008] S2: Processing the user information through user information anti-interference processing;

[0009] S3: Perform security detection and defense on user information through information security processing algorithms;

[0010] S4: Storing the user data after security processing.

[0011] As a preferred technical solution of the present invention: during the anti-interference processing of user information in S2, the safe processing range of the user information is obtained by testing the Euclidean distance between the user information in the personnel file system, and the user information is normalized to achieve safe processing of the user information.

[0012] As a preferred technical solution of the present invention: during the user information anti-interference processing, the Euclidean distance d(p,q) between the test user information is as follows:

[0013]

[0014] Among them, p, q, p1,…p n ,q1,…q n They all represent user information in the personnel file system; there is a basic data neighborhood between each user information:

[0015] N={q|q∈D∧d(p,q)≤σ}

[0016] Among them, D represents the scope of user information security processing, and σ represents the scope of user information collection;

[0017] Normalize the user information to obtain the normalized user information X:

[0018]

[0019] Among them, x represents the user information variable, x min Indicates the minimum value of the user information variable, x max Indicates the maximum value of the user information variable, x min and x max All are obtained according to the user information security processing scope D.

[0020] As the preferred technical solution of the present invention: in the information security processing algorithm of S3, the risk classification of user information security in the personnel file system is carried out through a risk classification algorithm, and at the same time, the user information is monitored for security processing through a security processing algorithm, and a defense strategy is adopted to perform security defense on user information with abnormalities in the monitoring.

[0021] As a preferred technical solution of the present invention: In the risk division algorithm, let the horizontal vector of the network intrusion signal be represented by a, the vertical vector of the network intrusion data be represented by b, and the initial result of the network intrusion feature signal be represented by c, and the defense coefficient k is obtained:

[0022]

[0023] Among them, f represents the derivative of different types of user information security risk characteristics, and the relationship between f and the input normalized user information X is: get:

[0024]

[0025] Assuming the intrusion defense probability is α, the impact of abnormal signals on the network is β, the calculated user information security risk metric E is as follows:

[0026]

[0027] Where m represents the estimated adjustment amount, and h represents the network threshold.

[0028] As a preferred technical solution of the present invention: in the risk classification algorithm, a user information security risk threshold is set, and the risk level is divided based on the set user information security risk threshold.

[0029] As a preferred technical solution of the present invention: In the security processing algorithm, the user information security data is searched based on the time scale, and a data entropy model g(t) is designed and established:

[0030] g(t)=[(τ1,t1,y1),(τ2,t2,y2),…,(τ l ,t l ,y l )]

[0031] Among them, y represents the security data transmitted according to the user information, τ represents the number of iterations, and t represents the error data signal;

[0032] Set the time interval to complete the calculation of the error data attribute entropy H:

[0033]

[0034] Wherein, w represents the security constant, r=1,…,u represents the number of information in the original state, and p(r) represents the peak signal received by the user security information within a specified time interval.

[0035] As a preferred technical solution of the present invention: the defense strategy includes firewall, intrusion monitoring and anti-virus technology.

[0036] As a preferred technical solution of the present invention: in the defense strategy, the vulnerability area is located and defended by monitoring each module.

[0037] As a preferred technical solution of the present invention: it also includes:

[0038] Information collection module: used to obtain user information in the personnel file system;

[0039] Information processing module: used to process user information through user information anti-interference processing;

[0040] Processing and defense module: used to monitor and defend user information through information security processing algorithms;

[0041] Information storage module: used to store user data that has been securely processed.

[0042] Compared with the prior art, the personnel information management system based on blockchain provided by the present invention has the following beneficial effects:

[0043] The present invention processes user information securely by performing anti-interference processing on user information, thereby improving the anti-interference ability of user information processing in a personnel file system and ensuring the security and reliability of information processing. At the same time, the security defense module monitors and defends the data of each module to improve the defense capability of the system and the security of user information. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 A method flow chart of a preferred embodiment of the present invention;

[0045] Figure 2 It is a system block diagram of a preferred embodiment of the present invention.

[0046] The meanings of the marks in the figure are as follows: 100, information acquisition module; 200, information processing module; 300, processing and defense module; 400, information storage module. DETAILED DESCRIPTION

[0047] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of this embodiment can be combined with each other. The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] Reference Figure 1 The preferred embodiment of the present invention provides a personnel information management system based on blockchain, and the management software includes the following operating steps:

[0049] S1: Obtain user information in the personnel file system;

[0050] S2: Processing the user information through user information anti-interference processing;

[0051] S3: Monitor and defend user information through information security processing algorithms;

[0052] S4: Storing the user data after security processing.

[0053] During the anti-interference processing of user information in S2, the safe processing range of user information is obtained by testing the Euclidean distance between user information in the personnel file system, and the user information is normalized to achieve safe processing of the user information.

[0054] During the user information anti-interference processing, the Euclidean distance d(p,q) between the test user information is as follows:

[0055]

[0056] Among them, p, q, p1,…p n ,q1,…q n They all represent user information in the personnel file system; there is a basic data neighborhood between each user information:

[0057] N={q|q∈D∧d(p,q)≤σ}

[0058] Among them, D represents the scope of user information security processing, and σ represents the scope of user information collection;

[0059] Normalize the user information to obtain the normalized user information X:

[0060]

[0061] Among them, x represents the user information variable, x min Indicates the minimum value of the user information variable, x max Indicates the maximum value of the user information variable, x min and x max All are obtained according to the user information security processing scope D.

[0062] In the information security processing algorithm of S3, the risk classification algorithm is used to classify the user information security in the personnel file system. At the same time, the user information is monitored for security processing through the security processing algorithm, and a defense strategy is adopted to perform security defense on the user information with abnormalities in the monitoring.

[0063] In the risk division algorithm, let the horizontal vector of the network intrusion signal be represented by a, the vertical vector of the network intrusion data be represented by b, and the initial result of the network intrusion feature signal be represented by c, and the defense coefficient k is obtained:

[0064]

[0065] Among them, f represents the derivative of different types of user information security risk characteristics, and the relationship between f and the input normalized user information X is: get:

[0066]

[0067] Assuming the intrusion defense probability is α, the impact of abnormal signals on the network is β, the calculated user information security risk metric E is as follows:

[0068]

[0069] Where m represents the estimated adjustment amount, and h represents the network threshold.

[0070] In the risk classification algorithm, a user information security risk threshold is set, and risk levels are classified based on the set user information security risk threshold.

[0071] In the security processing algorithm, the user information security data is searched based on the time scale, and a data entropy model g(t) is designed and established:

[0072] g(t)=[(τ1,t1,y1),(τ2,t2,y2),...,(τ l ,t l ,y l )]

[0073] Among them, y represents the security data transmitted according to the user information, τ represents the number of iterations, and t represents the error data signal;

[0074] Set the time interval to complete the calculation of the error data attribute entropy H:

[0075]

[0076] Wherein, w represents the security constant, r=1,…,u represents the number of information in the original state, and p(r) represents the peak signal received by the user security information within a specified time interval.

[0077] The defense strategy includes firewalls, intrusion detection and anti-virus technology.

[0078] In the defense strategy, vulnerability areas are located and defended by monitoring each module.

[0079] Also includes:

[0080] Information collection module 100: used to obtain user information in the personnel file system;

[0081] Information processing module 200: used to process user information through user information anti-interference processing;

[0082] Processing and defense module 300: used to perform security monitoring and defense on user information through information security processing algorithm;

[0083] Information storage module 400: used to store user data that has been security processed.

[0084] In this embodiment, the information collection module 100 collects user information data in the personnel file system, such as user historical personnel data information, and the information processing module 200 processes the collected user historical personnel data information, and quickly processes the user information data in the system. By processing the user information, the anti-interference ability of user information processing in the personnel file system can be effectively improved, and the security and reliability of information processing can be guaranteed.

[0085] At the same time, the processing defense module 300 performs security detection and defense on the user information in the system, constructs different types of user information risk categories, collects user information features, calculates the optimal feature fitting distribution, and determines the personnel information management user information security risk value at different confidence levels. And the coefficient of variation N; According to the user information security expectation A and standard deviation P, we get:

[0086]

[0087] Calculate f′(x):

[0088]

[0089] Where x represents the input user information, Q represents the user information risk weight matrix, Q = D -1 , C represents the feature matrix, f(x) represents the user information security risk feature; the relationship between f′(X) and the input user information satisfies Substituting the defense coefficient, we get:

[0090]

[0091] The calculated user information security risk metrics are as follows:

[0092]

[0093] Set the user information security risk threshold to divide the risk level. For example, set 5 and 10 as the thresholds, and estimate the risk level by comparing the calculated risk value with the threshold.

[0094] At the same time, the user information data received in the system is monitored through the security processing algorithm, and the user information security data is searched based on the time scale, and the data entropy model g(t) is designed and established:

[0095] g(t)=[(τ1,t1,y1),(τ2,t2,y2),…,(τ l ,t l ,y l )]

[0096] Among them, y represents the security data transmitted according to the user information, τ represents the number of iterations, and t represents the error data signal;

[0097] Set the time interval to 15s, extract the corresponding user information and operation information, and complete the calculation of the error data attribute entropy H:

[0098]

[0099] Wherein, w represents the security constant, r = 1,…,9, and p(r) represents the peak signal of the user security information received within a specified time interval.

[0100] To strengthen the system information security protection effect and improve the security of user information.

[0101] Based on the occurrence of user information security threats, it is roughly divided into three levels, including the information collection module 100 of user information security events, which is responsible for collecting original user information security data, including the status of the host, database and application system under the threat situation, and judging the difference between it and the normal situation; the second is the information processing layer 200 of the user information security threat event, which can find the crux of the problem by analyzing the problem specifically, and can also judge the general direction of the problem; the last is the information storage module 400 of the user information security threat problem, which finds the problem and solves it through firewall, intrusion monitoring or anti-virus technology, and displays the problem and solution, based on which the security defense module 300 is optimized. After the processing and monitoring and defense of user information are completed, the information storage module 400 is provided to store it in the database for storage.

[0102] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

[0103] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. The personnel information management system based on blockchain is characterized by: The management software includes the following steps: S1: Obtain user information in the personnel file system; S2: Processing the user information through user information anti-interference processing; S3: Monitor and defend user information through information security processing algorithms; S4: Storing the user data after security processing.

2. The blockchain-based personnel information management system according to claim 1, characterized in that: During the anti-interference processing of user information in S2, the safe processing range of user information is obtained by testing the Euclidean distance between user information in the personnel file system, and the user information is normalized to achieve safe processing of the user information.

3. The blockchain-based personnel information management system according to claim 2 is characterized in that: During the user information anti-interference processing, the Euclidean distance d(p,q) between the test user information is as follows: Among them, p, q, p1,…p n ,q1,…q n They all represent user information in the personnel file system; there is a basic data neighborhood between each user information: N={q|q∈D∧d(p,q)≤σ} Among them, D represents the scope of user information security processing, and σ represents the scope of user information collection; Normalize the user information to obtain the normalized user information X: Among them, x represents the user information variable, x min Indicates the minimum value of the user information variable, x max Indicates the maximum value of the user information variable, x min and x max All are obtained according to the user information security processing scope D.

4. The blockchain-based personnel information management system according to claim 3 is characterized in that: In the information security processing algorithm of S3, the risk classification algorithm is used to classify the user information security in the personnel file system, and at the same time, the user information is monitored for security processing through the security processing algorithm, and a defense strategy is adopted to perform security defense on the user information with abnormalities in the monitoring.

5. The blockchain-based personnel information management system according to claim 4 is characterized in that: In the risk division algorithm, let the horizontal vector of the network intrusion signal be represented by a, the vertical vector of the network intrusion data be represented by b, and the initial result of the network intrusion feature signal be represented by c, and the defense coefficient k is obtained: Among them, f represents the derivative of different types of user information security risk characteristics, and the relationship between f and the input normalized user information X is: get: Assuming the intrusion defense probability is α, the impact of abnormal signals on the network is β, the calculated user information security risk metric E is as follows: Where m represents the estimated adjustment amount, and h represents the network threshold.

6. The blockchain-based personnel information management system according to claim 5 is characterized in that: In the risk classification algorithm, a user information security risk threshold is set, and risk levels are classified based on the set user information security risk threshold.

7. The blockchain-based personnel information management system according to claim 6 is characterized in that: In the security processing algorithm, the user information security data is searched based on the time scale, and a data entropy model g(t) is designed and established: g(t)=[(τ1,t1,y1),(τ2,t2,y2),…,(τ l ,t l ,y l )] Among them, y represents the security data transmitted according to the user information, τ represents the number of iterations, and t represents the error data signal; Set the time interval to complete the calculation of the error data attribute entropy H: Wherein, w represents the security constant, r=1,…,u represents the number of information in the original state, and p(r) represents the peak signal received by the user security information within a specified time interval.

8. The blockchain-based personnel information management system according to claim 7, characterized in that: The defense strategy includes firewalls, intrusion detection and anti-virus technology.

9. The blockchain-based personnel information management system according to claim 8, characterized in that: In the defense strategy, vulnerability areas are located and defended by monitoring each module.

10. The blockchain-based personnel information management system according to claim 9, characterized in that: The management software also includes: Information collection module (100): used to obtain user information in the personnel file system; Information processing module (200): used for processing user information through user information anti-interference processing; Processing and defense module (300): used to perform security monitoring and defense on user information through information security processing algorithm; Information storage module (400): used to store user data that has been securely processed.

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