Human resource management information integration method based on block chain

Abstract

The invention discloses a human resource management information integration method based on a block chain, and the method comprises the steps: collecting human resource information, and carrying out the dynamic structural processing of the human resource information, and obtaining a structural data set; dividing the data into a plurality of data fragments, and encrypting the plurality of data fragments by using an inner product function encryption algorithm to obtain encrypted data fragments; storing the data in an alliance block chain network; generating an autonomous identity identifier for each user, binding the autonomous identity identifier of the user with a cryptographic key thereof, and storing the autonomous identity identifier in an alliance block chain; when the user requests to access the encrypted data fragment, verifying the verifiable certificate and authority of the user through an intelligent contract mechanism; in an encryption state, directly performing homomorphic calculation on the processed data fragments to obtain an analysis result; and the public key of the target receiver is used to encrypt the analysis result to obtain an encrypted analysis result, the encrypted analysis result is stored on the alliance block chain and is distributed to the authorized user, and the authorized user decrypts the result through the private key.

Description

Technical Field

[0001] The present invention relates to the technical field of blockchain technology and human resource information management, and in particular to a human resource management information integration method based on blockchain. Background Art

[0002] With the rapid development of information technology and the Internet, traditional human resource management systems usually rely on centralized databases, which have problems such as data silos, information asymmetry and low data security.

[0003] At present, there is a contradiction between data privacy protection and secure sharing. How to achieve data sharing and collaboration while protecting personal privacy is an urgent problem to be solved. Secondly, the existing system lacks granularity and dynamism in data encryption, permission control and access management, and it is difficult to meet complex business needs. For example, traditional access control mechanisms are difficult to support permission management based on multiple dimensions such as role, time, location and context. Thirdly, traditional encryption methods are inefficient when processing calculations and analysis of encrypted data, and cannot support homomorphic computing or function encryption, which limits the application value of data and makes it impossible to directly analyze and process data in an encrypted state. In addition, existing technologies lack unified standards and specifications for identity authentication and permission management, resulting in limited interoperability and scalability of the system, making it difficult to achieve cross-organizational and cross-platform human resources information integration and sharing.

[0004] In summary, the existing blockchain-based human resource management information integration method has problems such as insufficient data security, imperfect privacy protection, inflexible access control, and low computing efficiency. The present invention provides a blockchain-based human resource management information integration method to solve the above problems. Summary of the Invention

[0005] The purpose of this section is to summarize some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the abstract of the specification and the title of the invention of this application to avoid blurring the purpose of this section, the abstract of the specification and the title of the invention, and such simplifications or omissions cannot be used to limit the scope of the invention.

[0006] In view of the above existing problems, the present invention is proposed.

[0007] Therefore, the technical problem solved by the present invention is to solve the problems of insufficient data security, imperfect privacy protection and inflexible access control in the prior art.

[0008] To solve the above technical problems, the present invention provides the following technical solutions: Step 1: Collect human resource information from multiple data sources, perform dynamic structural processing on it, and obtain a structured data set;

[0009] Step 2: dividing the structured data set into multiple data segments, and encrypting the multiple data segments using an inner product function encryption algorithm to obtain encrypted data segments;

[0010] Step 3: Store the encrypted data fragment in the alliance blockchain network. The data storage location is determined by the node number of the data storage;

[0011] Step 4: Generate an autonomous identity for each user, bind the user's autonomous identity to their cryptographic key, and store it on the consortium blockchain;

[0012] Step 5: When the user requests access to the encrypted data segment, the user's verifiable credentials and permissions are verified through a smart contract mechanism, where:

[0013] If the verification fails, further access will be denied;

[0014] If the verification is successful, the user uses his private key and the function decryption algorithm to decrypt the encrypted data segment requested for access, and obtains the result of the data segment processed by the decryption function;

[0015] Step 6: In the encrypted state, directly perform homomorphic calculation on the data fragment processed in step 5 to obtain the analysis result;

[0016] Step 7: Use the public key of the target recipient to encrypt the analysis results, obtain the encrypted analysis results, store them on the alliance blockchain, and distribute them to authorized users. Authorized users decrypt them using their private key to obtain the results.

[0017] As a preferred solution of the blockchain-based human resource management information integration method of the present invention, the collected human resource information is cleaned and represented as an initial data set D:

[0018] D={d1,d2,…,d m}

[0019] Among them, d i represents the i-th original data record, and m is the total amount of data.

[0020] As a preferred solution of the blockchain-based human resource management information integration method of the present invention, a structured data set is obtained, including:

[0021] Parse each data record and extract key attributes;

[0022] Mapping the key attributes of the data records to a unified data schema S using a schema matching algorithm;

[0023] If a new attribute field is encountered, the schema S is dynamically updated;

[0024] After the above processing, the structured data set D′ is obtained:

[0025] D′={d′1,d′2,…,d′ n}

[0026] Where d′ i is the structured data record, and n is the total amount of processed data.

[0027] As a preferred solution of the blockchain-based human resource management information integration method of the present invention, the structured data set is divided into multiple data segments, including:

[0028] Set the number of shards k based on system performance and security requirements;

[0029] Traverse the structured data set and assign each data record to the corresponding data segment D j middle;

[0030] Use a hash function to calculate the specific attributes of the data record to obtain the shard index;

[0031] Add the data record to the corresponding shard to obtain k data fragments D0, D1, ..., D k-1 ,Each data segment contains several data records.

[0032] As a preferred solution of the blockchain-based human resource management information integration method described in the present invention, the alliance blockchain network is composed of nodes of multiple trusted institutions or organizations, and each node represents a participant.

[0033] As a preferred solution of the blockchain-based human resources management information integration method of the present invention, it also includes:

[0034] Each participant installs the blockchain node software, configures network parameters and node identities;

[0035] Each node completes the initialization of the blockchain network through the consensus protocol;

[0036] Assign a unique node identifier NodeID to each node i , and establish trust relationships between nodes;

[0037] For each encrypted data segment E(D s )Calculate the hash value H(E(D s )), storage node number P(E(D s ));

[0038] The encrypted data segment E(D s ) is stored in the number P(E(D s ))'s node.

[0039] As a preferred solution of the blockchain-based human resource management information integration method described in the present invention, the submitted access request at least includes an autonomous identity identifier, an identifier of the encrypted data segment requested for access, and a function f to be executed.

[0040] As a preferred solution of the human resource management information integration method based on blockchain described in the present invention, the ECC public key pk rec Encrypt the encrypted aggregation result E(R); publish the encrypted result as transaction data to the blockchain network; record the transaction hash value, timestamp, sender and receiver identities; notify the authorized target receiver that new analysis results are available; the target receiver obtains the encrypted result from the blockchain; use the receiver's private key sk rec Decrypt and get the final analysis result R.

[0041] Beneficial effects of the present invention:

[0042] 1. By collecting human resources information from multiple data sources and performing dynamic structural processing, unified integration and standardized management of heterogeneous data are achieved, improving data consistency and integrity, laying the foundation for efficient system operation and data accuracy;

[0043] 2. By dividing structured data sets into multiple data fragments and encrypting them using the inner product function encryption algorithm, fine-grained encryption protection of data is achieved, ensuring the security of data during storage and transmission, preventing the leakage of sensitive information, enhancing data security and supporting controlled computing, meeting the dual requirements of data privacy protection and business needs;

[0044] 3. By storing encrypted data fragments in the alliance blockchain network and determining the data storage location based on the node number, distributed and secure data storage is achieved. By leveraging the decentralization and immutability of the blockchain, data integrity and traceability are guaranteed, data storage security and system reliability are improved, and single point failures and data tampering risks are prevented.

[0045] 4. By generating an autonomous identity for each user and binding it to a cryptographic key, which is then stored on the blockchain, trusted management and secure authentication of user identities are achieved, ensuring the uniqueness and non-repudiation of user identities, facilitating permission control and operation traceability, enhancing system security and user management efficiency, and supporting fine-grained permission control and compliance requirements.

[0046] 5. By using a smart contract mechanism to verify the user's verifiable credentials and permissions when the user requests access to encrypted data fragments, automated and intelligent permission management is achieved, ensuring that only authorized users can access specific data fragments, preventing unauthorized access, strengthening data access security and improving permission management efficiency, thereby ensuring data confidentiality and secure system operation;

[0047] 6. By performing homomorphic calculations on processed data fragments in an encrypted state, direct analysis and processing of sensitive data is achieved without decryption. Utilizing the characteristics of homomorphic encryption, operations can be performed on ciphertext, protecting data privacy while meeting data processing requirements. Data analysis is achieved under the premise of ensuring data privacy, improving the security and efficiency of data processing.

[0048] 7. By encrypting the analysis results using the public key of the target recipient and storing the encrypted results on the blockchain for distribution to authorized users, the secure transmission and sharing of the analysis results is achieved, ensuring that only authorized users can decrypt and obtain the analysis results, preventing the results from being leaked or tampered with during transmission, ensuring the secure sharing of analysis results and improving data utilization, thereby promoting the full realization of data value. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be derived from these drawings without inventive effort. Among them:

[0050] Figure 1 This is a flowchart of the blockchain-based human resources management information integration method shown in the present invention. DETAILED DESCRIPTION

[0051] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, but not all of the embodiments.

[0052] Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in this field without making any creative work should fall within the scope of protection of the present invention.

[0053] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0054] According to an embodiment of the present invention, Figure 1 The flowchart shown is a human resource management information integration method based on blockchain, which specifically includes the following steps:

[0055] Step 1: Collect human resources information from multiple data sources, dynamically structure it, and obtain a structured data set. Note that:

[0056] Collect human resources information from multiple data sources (such as internal human resources management systems, training and performance management systems, employee attendance and payroll systems);

[0057] The collected original human resource information is cleaned (such as missing value processing, outlier detection and duplicate value deletion) and represented as the initial data set D:

[0058] D={d1,d2,…,d m}

[0059] Among them, d i represents the i-th original data record, and m is the total amount of data;

[0060] For each data record d i Parse and extract key attributes;

[0061] Use pattern matching algorithm to convert d i The attributes are mapped to a unified data schema S;

[0062] If a new attribute field is encountered, the schema S is dynamically updated to ensure the flexibility of the data structure;

[0063] For example, unify the formats of date, time, and numerical values, such as unifying the date format to YYYY-MM-DD;

[0064] For example, the text encoding is unified into UTF-8 to ensure cross-platform compatibility;

[0065] After the above processing, the structured data set D′ is obtained:

[0066] D′={d′1,d′2,…,d′ n}

[0067] Where d′ i is the structured data record, n is the total amount of processed data;

[0068] Step 2: Divide the structured data set into multiple data segments, and encrypt each data segment using the inner product function encryption algorithm to obtain encrypted data segments. The following should be noted in this step:

[0069] Set the number of shards k based on system performance and security requirements;

[0070] Traverse the structured data set D′ and record each data record d i Assigned to the corresponding data segment D j middle;

[0071] Use the hash function to calculate the specific attributes of the data record to obtain the shard index s:

[0072] s=H(d i .attribute)modk

[0073] Among them, d i .attribute represents the attribute value used for sharding, mod is the modulo operation, and the value range of s is 0 to k-1;

[0074] Record the data i Add to the corresponding shard to obtain k data fragments D0, D1, ..., D k-1 , each data segment contains several data records; its mathematical expression formula is:

[0075] D τ =D1∪D2∪…∪D k

[0076] Among them, D i is the i-th data fragment, k is the total number of data fragments;

[0077] Furthermore, the inner product function encryption algorithm is used in the embodiment of the present invention, which allows the inner product of the data vector and the function vector to be calculated in the ciphertext state, so as to achieve fine-grained access control;

[0078] In an optional embodiment, a security parameter λ is set to determine the key length, and its mathematical expression is:

[0079] (pk,msk)←Setup(1 λ )

[0080] Among them, Setup is the key generation algorithm, pk is the public key, msk is the master key, and λ is the security parameter;

[0081] For each data segment, each data record d i Convert to attribute vector

[0082]

[0083] Among them, x ij Indicates the j-th attribute value of the i-th data, and n is the total number of attributes;

[0084] For each data vector To encrypt:

[0085]

[0086] Among them, Encrypt is the encryption algorithm of inner product function encryption, is the encrypted data vector;

[0087] Get encrypted data fragment

[0088] Step 3: Store the encrypted data fragment in the consortium blockchain network (the consortium blockchain network uses the Byzantine Fault Tolerance (BFT) consensus mechanism). The data storage location is determined by calculating the hash value of the encrypted data fragment and the number of storage nodes to obtain the node number for the data storage. Note that:

[0089] The consortium blockchain network consists of nodes from multiple trusted institutions or organizations, each representing a participant;

[0090] Each participant installs the blockchain node software, configures network parameters and node identities;

[0091] Each node completes the initialization of the blockchain network through the consensus protocol;

[0092] Among them, the Byzantine Fault Tolerance (BFT) consensus mechanism (such as the PBFT protocol) is used to ensure the consistency and reliability of the system even when some nodes are malicious or faulty;

[0093] Specifically, each node is assigned a unique node identifier NodeID i , and establish trust relationships between nodes;

[0094] For each encrypted data segment E(D s )Calculate the hash value H(E(D s )):

[0095] H(E(D s ))=Hash(E(D s ))

[0096] Wherein, Hash is a secure hash function (such as SHA-256);

[0097] Calculate the storage node number P(E(D s )):

[0098] P(E(D s ))=H(E(D s ))modN

[0099] Where N is the total number of nodes in the network, and mod is the modulo operation;

[0100] The encrypted data fragment E(D s ) is stored in the number P(E(D s ))'s node;

[0101] Step 4: Generate a self-sovereign identity for each user (including a distributed identifier (DID) and verifiable credentials, stored and managed in accordance with W3C DID and VC standards), bind the user's self-sovereign identity to their cryptographic key, and store it on the consortium blockchain. Notes on this step:

[0102] Generate a unique distributed identifier DID for each user u u :

[0103] DID u =did:example:user u

[0104] Among them, user u A unique identifier for the user;

[0105] According to the W3C Verifiable Credentials standard, a credential VC is created for user u containing identity information and attributes. u , which specifically includes user identity information, authority attributes, issuer information and validity period;

[0106] Use the issuer's private key to VC u Digitally sign to ensure its integrity and authenticity;

[0107] Furthermore, the user generates a public-private key pair:

[0108] (pk u ,sk u )←KeyGen(1 λ )

[0109] Among them, KeyGen is the key generation algorithm;

[0110] The user's DID, VC and public key pk u Binding to form a self-sovereign identity SSI u ;

[0111] Will SSI u Stored on the blockchain in the form of DID u VC u 、pk u ;

[0112] Step 5: When a user requests access to an encrypted data segment, the smart contract (which evaluates the user's permissions and the data segment's access policy and grants decryption permission only if the user's permissions satisfy the data segment's access policy) verifies the user's verifiable credentials and permissions. If the verification passes, the user uses their private key and the function decryption algorithm to decrypt the encrypted data segment, obtaining the result of the function processing of the data segment, rather than the plaintext content of the data segment. Note that:

[0113] User u submits an access request, including: self-sovereign identity SSI u (including DID u ,VC u ,pk u ), the encrypted data segment identifier E(D s ) and the function f you want to execute;

[0114] Verify VC u Digital signature to ensure that the certificate has not been tampered with;

[0115] Check VC u validity period and revocation status;

[0116] From VC u Extract user permissions P u ;

[0117] Get data fragment E(D s ) access policy AP s ;

[0118] Determine whether it satisfies: P u =AP s

[0119] If P u Meet AP s , then the verification is passed;

[0120] Generate the function decryption key sk using the master key msk and function f f :

[0121] sk f =KeyGen(msk,f)

[0122] Use the user's public key P u Encrypted sk f :

[0123] E(sk f )=Encrypt(pk u ,sk f )

[0124] The user uses the private key sk u Decryption E(sk f ):

[0125] sk f =Decrypt(sk u ,E(sk f ))

[0126] User use sk f For the encrypted data segment E(D s ) to decrypt and obtain the function calculation result:

[0127] R s =Decrypt(sk f ,E(D s ))

[0128] Among them, R s =f(D s );

[0129] In the embodiment of the present invention, the main purpose of step S5 is to allow the user to obtain the data segment D without obtaining the original data plaintext. s The result R after calculating the specific function f s In order to better understand the purpose, the following is a detailed description of R s What's included:

[0130] R s =f(D s )

[0131] Among them, D s is the original data segment, which contains multiple data records, f is the specific function that the user is authorized to execute, R s It is the function f acting on the data segment D s The calculation results obtained later;

[0132] R s Contains only the output of function f, not the original data segment D s The plain text content;

[0133] If f is a function that performs statistical calculations on the data, such as sum, average, maximum, or minimum, then R s It will be a numerical value, such as calculating the total sales volume or the average employee performance rating;

[0134] If f is a function that processes each data record and returns a result, then R s It will be a vector or list consisting of multiple elements, such as extracting a data set of a specific field or calculating the bonus amount for each employee;

[0135] If f involves multidimensional data processing, such as matrix operations and image processing, then R s It may be a matrix or a multidimensional array, such as calculating a correlation matrix;

[0136] If f is a model training function, such as linear regression or neural network training, then R s It will contain model parameters or structural information, such as trained model weights and decision tree structures;

[0137] That is R s It is the function f acting on the data segment D s The calculated result, R s The specific content depends on the definition of function f and the user's permission settings. s It can meet specific business needs without accessing the original data, ensuring data security and privacy;

[0138] Furthermore, users can only obtain the calculation results of functions within their authority and cannot obtain other information beyond their authority. The authority is verified by the smart contract in the above steps to ensure security; R s Does not include original data D s Any plaintext information cannot be passed through R s Reverse D s ,This ensures the confidentiality of data and prevents the leakage of sensitive information;

[0139] To better understand the implementation process of the method of the present invention, the following describes in detail the specific implementation process of steps S1 to S5 using the human resources information management of an example company. The example company is a medium-sized enterprise with multiple departments (such as R&D, Marketing, and Human Resources) and approximately 100 employees. The company hopes to integrate human resources information in a secure and efficient manner for data analysis and decision support while protecting employees' personal privacy.

[0140] Internal human resources management system: including basic employee information, positions, and salaries;

[0141] Training and performance management system: including employee training records and performance evaluation results;

[0142] Employee attendance system: includes employee attendance records and leave information;

[0143] The collected raw data is represented as:

[0144] D={d1,d2,…,d 150}

[0145] Among them, d i represents the i-th original data record, and a total of 150 data records were collected;

[0146] Example data record d1:

[0147] {

[0148] "employee_id":"E001",

[0149] "name":"Zhang San",

[0150] "department":"R&D Department",

[0151] "position":"Software Engineer",

[0152] "salary":15000,

[0153] "hire_date":"2020-03-15",

[0154] "performance_score":85

[0155] }

[0156] Example data record d 50 :

[0157] {

[0158] "employee_id":"E050",

[0159] "name":"Li Si",

[0160] "department":"Marketing Department",

[0161] "position":"Marketing Manager",

[0162] "salary":20000,

[0163] "hire_date":"2019-07-20",

[0164] "performance_score":90

[0165] }

[0166] Thought, lasts 10 seconds;

[0167] For each data d i Parsing to extract key attributes such as employee number, name, department, position, salary, date of employment, and performance rating;

[0168] Unified data model S: Establish a unified data model, including the following fields:

[0169] {

[0170] "employee_id":String,

[0171] "name":String,

[0172] "department":String,

[0173] "position":String,

[0174] "salary":Integer,

[0175] "hire_date":Date,

[0176] "performance_score": Integer

[0177] }

[0178] Dynamically update the schema: If a new attribute field is encountered (such as a newly added training record), the schema S is updated to include the new field;

[0179] Unify the date format to YYYY-MM-DD, for example, "2020-3-15" is converted to "2020-03-15";

[0180] Unify values ​​such as salary and performance ratings into integer or floating point formats;

[0181] Encode all text data as UTF-8 to ensure compatibility across different systems;

[0182] For missing performance ratings, the departmental average performance rating was used to fill in the missing performance ratings;

[0183] Use statistical methods to detect abnormally high or low salary data, such as records exceeding twice the average salary, and conduct manual verification;

[0184] According to the employee id As a unique identifier to remove duplicate employee records;

[0185] After processing, a structured data set is obtained:

[0186] D′={d′1,d′2,…,d′ n}

[0187] Where n = 100, indicating that the number of valid employee data records after processing is 100;

[0188] The number of shards is the number of company departments. Assuming the company has three departments: R&D, Marketing, and HR, then k = 3.

[0189] For each data record d′ i , sharding according to the department attribute:

[0190]

[0191] Record the data d′ i Add to the corresponding shard D s , we get 3 data fragments:

[0192] D0: Data records of the R&D department, a total of 50 records;

[0193] D1: Data records of the marketing department, a total of 30 records;

[0194] D2: Data records of the Human Resources Department, a total of 20 records;

[0195] Set the security parameter λ to 128 to determine the key length;

[0196] (pk,msk)←Setup(1 128 )

[0197] Select the attributes that need to be encrypted, such as performance score ;

[0198] For each data record d′ i , extract attribute values ​​and form vector

[0199]

[0200] For example, for employee d′1:

[0201]

[0202] right Encrypt and get ciphertext Get the encrypted data fragment:

[0203]

[0204] For the R&D department D0, there is encrypted data E(D0);

[0205] Different departments within the company serve as blockchain nodes:

[0206] Node 0: R&D server

[0207] Node 1: Marketing Department Server

[0208] Node 2: Human Resources Department Server

[0209] Adopt a Byzantine Fault Tolerant (BFT) consensus mechanism, such as the PBFT protocol;

[0210] Each department installs the blockchain node software on its server and configures network parameters and node identities;

[0211] The nodes complete the initialization of the blockchain network through the consensus protocol and generate the genesis block;

[0212] Assign a unique node identifier NodeID to each node i ;

[0213] Use the SHA-256 hash function to calculate the hash value H(E(Ds)) for each encrypted data fragment E(Ds); calculate the storage node number P(E(Ds) s )):

[0214] P(E(D s ))=H(E(D s ))modN

[0215] Where, N=3 (total number of nodes);

[0216] For example, if H(E(D0))mod3=1, then E(D0) is stored on node 1;

[0217] The encrypted data fragment E(D s ) is stored in the number P(E(D s ))'s node;

[0218] User type: such as R&D manager, Xiao Wang;

[0219] Generate a DID for Xiao Wang:

[0220] DID 王经理 =did:example:wang manager

[0221] For example, a verifiable credential (VC) is generated, and its credential content is as follows:

[0222]

[0223]

[0224] Use company private key to VC 王经理Digital signature;

[0225] Generate a public-private key pair:

[0226] (pk 王经理 ,sk 王经理 )←KeyGen(1 128 )

[0227] Bind Xiao Wang’s DID, VC and public key to form a self-sovereign identity SSI 王经理 ;

[0228] Store it on the blockchain, including: DID 王经理 , VC 王经理 , pk 王经理 ;

[0229] Request content:

[0230] User: Xiao Wang (R&D Manager)

[0231] Self-Sovereign Identity: SSI 王经理

[0232] Encrypted data fragment requested for access: E(D0) (R&D department data)

[0233] Function you want to execute: Calculate the average performance score of R&D department employees

[0234] Verify VC 王经理 Digital signature to ensure that the certificate has not been tampered with;

[0235] Check the validity period of the certificate;

[0236] From VC 王经理 Extract permissions:

[0237] P 王经理 ={″view performance ″}

[0238] Get the access policy for data segment E (D0):

[0239] AP0={"view performance "}

[0240] Determine whether:

[0241] P 王经理 =AP0

[0242] Because Xiao Wang's permissions include view performance , verification passed;

[0243] Generate the function decryption key sk using the master key msk and function f f :

[0244] Function f: Calculates the average performance score, that is:

[0245]

[0246] Among them, x i2 It is a performance rating;

[0247] Generate a key:

[0248]

[0249] in, Indicates that only performance score attributes are extracted;

[0250] Use Xiao Wang's public key pk 王经理 Encrypted sk f :

[0251] E(sk f )=Encrypt(pk 王经理 ,sk f )

[0252] Xiao Wang uses the private key sk 王经理 Decryption E(sk f ):

[0253] sk f =Decrypt(sk 王经理 ,E(sk f ))

[0254] For each encrypted data vector Execute function decryption:

[0255]

[0256] Xiao Wang receives the performance rating x of all employees in the R&D department i2 , but cannot obtain other sensitive information such as salary;

[0257] Calculate the average performance rating:

[0258]

[0259] Where n0 = 50 (number of employees in the R&D department);

[0260] For example, assuming the total performance score is 4250, then:

[0261]

[0262] In an optional implementation, the embodiment of the present invention further includes the implementation of the following steps 6 and 7. By performing homomorphic computation on the processed data fragments in an encrypted state, direct analysis and processing of sensitive data is achieved without decryption, thereby achieving data analysis while protecting data privacy, thereby improving the security and efficiency of data processing. At the same time, by encrypting the analysis results using the public key of the target recipient, and storing the encrypted results on the blockchain and distributing them to authorized users, secure transmission and sharing of the analysis results are achieved, ensuring that only authorized users can decrypt and obtain the analysis results, and preventing the leakage or tampering of the results during transmission.

[0263] Step 6: In the encrypted state, directly perform homomorphic calculations on the data fragments processed in step 5 to obtain analysis results. The following points need to be explained in this step:

[0264] The Paillier encryption algorithm is used, which has additive homomorphism. Its mathematical expression is:

[0265] E(m1)·E(m2)modn 2 =E(m1+m2modn)

[0266] Public key: pk HE =(n,g)

[0267] Private key: sk HE =(λ,μ)

[0268] Where n = pq, p and q are large prime numbers;

[0269] The calculation results are:

[0270] E(R s )=Paillier Encrypt (pk HE ,R s )

[0271] If there are calculation results for multiple users, aggregation is required, such as summation:

[0272]

[0273] E(R) is the encrypted aggregation result, which is still in an encrypted state and cannot be read directly in plain text;

[0274] Step 7: Use the target recipient's public key to encrypt the analysis results (elliptic curve cryptography algorithm), obtain the encrypted analysis results, store them on the consortium blockchain, and distribute them to authorized users. Authorized users decrypt the results using their private key. The following points need to be noted in this step:

[0275] Use the target recipient's ECC public key pkrec Encrypt the encrypted aggregation result E(R):

[0276] E ECC (E(R))=ECC Encrypt (pk rec ,E(R))

[0277] E ECC (E(R)) is published to the blockchain network as transaction data;

[0278] Record relevant metadata, such as transaction hashes, timestamps, and sender and receiver identities;

[0279] Notify authorized users (recipients) that new analysis results are available;

[0280] Users obtain E from the blockchain ECC (E(R));

[0281] Use the receiver's private key sk rec Decryption:

[0282] E(R)=ECC Decrypt (sk rec ,E ECC (E(R)))

[0283] Use the Paillier private key sk HE Decryption:

[0284] R=Paillier Decrypt (sk HE ,E(R))

[0285] The receiver obtains the final analysis result R, which can be used for further business decision-making;

[0286] Specifically, R is the aggregated analysis result obtained through homomorphic encryption calculations, which may include statistical indicators, model outputs, and trend analysis, such as the average employee performance, personnel turnover statistics between departments, and the distribution of overall salary levels;

[0287] As an example, Company A is defined as a large enterprise with multiple departments and rich human resources data, and Company B is its partner. It hopes to obtain the overall employee satisfaction statistics of Company A for market analysis and cooperation strategy formulation. However, Company A does not want to disclose the original data of any employee, but is willing to share the analysis results after secure processing. This embodiment applies the above steps 6 and 7, that is, performs homomorphic calculations in an encrypted state to obtain the analysis results, and uses the public key of the partner (Company B) to encrypt the results and store them on the blockchain for secure access. The following detailed example is provided to enable non-technical personnel to better understand the application of the steps proposed in the embodiments of the present invention. Specifically:

[0288] Select the Paillier encryption algorithm, which has additive homomorphism and allows addition operations to be performed in the ciphertext state. Define p = 103, q = 109, and calculate n and λ:

[0289] n=p×q=103×109=11227

[0290] λ=lcm(p-1,q-1)=lcm(102,108)=1836

[0291] Select g = n + 1 = 11228 and calculate μ:

[0292] μ=(L(g λ modn 2 )) -1 modn

[0293] Public key: pk HE =(n,g)

[0294] Private key: sk HE =(λ,μ)

[0295] Define the average employee satisfaction scores of multiple departments obtained by Company A through the implementation process of step 5 above as follows:

[0296] R1=80 (Department 1)

[0297] R2=85(Department 2)

[0298] R3=78 (Department 3)

[0299] For each R s , select a random number calculate:

[0300]

[0301] Taking R1=80 as an example, select the random number r1=5000 and get:

[0302] E(R1)=11228 80 ×5000 11227 mod11227 2

[0303] Then calculate the sum of the average employee satisfaction scores of all departments:

[0304] E(R)=E(80)×E(85)×E(78)modn 2

[0305] Among them, E(R) is the encrypted result of the total satisfaction score, which is still ciphertext;

[0306] Company A performs ECC encryption on the encrypted aggregation result E(R):

[0307] E ECC (E(R))=ECC Encrypt (pk rec ,E(R))

[0308] E ECC (E(R)) is published to the blockchain network as transaction data;

[0309] The recorded metadata is: transaction hash, timestamp, sender ID (Company A) and receiver ID (Company B);

[0310] Notify Company B that new analytical results are available;

[0311] Company B obtains E from the blockchain ECC (E(R)), where:

[0312] Since Company B does not have the Paillier private key, it cannot directly decrypt E(R). Therefore, Company A uses its Paillier private key sk HE Decrypt E(R) to get R;

[0313] Use company B's public key pk rec Perform ECC encryption on R:

[0314] E ECC (R)=ECC Encrypt (pk rec ,R)

[0315] E ECC (R) published on the blockchain for Company B to access;

[0316] Company B uses its private key sk rec Perform ECC decryption:

[0317] E(R)=ECC Decrypt (skrec ,E ECC (E(R)))

[0318] For example, Company B obtains a total employee satisfaction score of R = R1 + R2 + R3

[0319] =80+85+78=243;

[0320] Calculate the average satisfaction:

[0321]

[0322] The above examples demonstrate the practical application of the method of the present invention in data sharing among partners. Company A uses homomorphic encryption and ECC encryption technology to securely share the human resources analysis results with Company B without leaking the original data, thereby preventing the leakage of sensitive information.

[0323] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A human resource management information integration method based on blockchain, characterized in that: include: Step 1: Collect human resource information from multiple data sources, perform dynamic structural processing on it, and obtain a structured data set; Step 2: dividing the structured data set into multiple data segments, and encrypting the multiple data segments using an inner product function encryption algorithm to obtain encrypted data segments; Step 3: Store the encrypted data fragment in the alliance blockchain network. The data storage location is determined by the node number of the data storage; Step 4: Generate an autonomous identity for each user, bind the user's autonomous identity to their cryptographic key, and store it on the consortium blockchain; Step 5: When the user requests access to the encrypted data segment, the user's verifiable credentials and permissions are verified through a smart contract mechanism, where: If the verification fails, further access will be denied; If the verification is successful, the user uses his private key and the function decryption algorithm to decrypt the encrypted data segment requested for access, and obtains the result of the data segment processed by the decryption function; Step 6: In the encrypted state, directly perform homomorphic calculation on the data fragment processed in step 5 to obtain the analysis result; Step 7: Use the public key of the target recipient to encrypt the analysis results, obtain the encrypted analysis results, store them on the alliance blockchain, and distribute them to authorized users. Authorized users decrypt them using their private key to obtain the results.

2. The human resource management information integration method based on blockchain according to claim 1 is characterized in that: The collected human resources information is cleaned and represented as an initial data set D: D={d1,d2,…,d m } Among them, d i represents the i-th original data record, and m is the total amount of data.

3. The human resource management information integration method based on blockchain according to claim 2 is characterized in that: Get a structured data set, including: Parse each data record and extract key attributes; Mapping the key attributes of the data records to a unified data schema S using a schema matching algorithm; If a new attribute field is encountered, the schema S is dynamically updated; After the above processing, the structured data set D′ is obtained: D′={d′1,d′2,…,d′ n } Where d′ i is the structured data record, and n is the total amount of processed data.

4. The human resource management information integration method based on blockchain according to claim 3 is characterized in that: The structured data set is divided into multiple data segments, including: Set the number of shards k based on system performance and security requirements; Traverse the structured data set and assign each data record to the corresponding data segment D j middle; Use a hash function to calculate the specific attributes of the data record to obtain the shard index; Add the data record to the corresponding shard to obtain k data fragments D0, D1, ..., D k-1 ,Each data segment contains several data records.

5. The human resource management information integration method based on blockchain according to claim 1 is characterized in that: The alliance blockchain network is composed of nodes from multiple trusted institutions or organizations, and each node represents a participant.

6. The human resource management information integration method based on blockchain according to claim 5 is characterized in that: Also includes: Each participant installs the blockchain node software, configures network parameters and node identities; Each node completes the initialization of the blockchain network through the consensus protocol; Assign a unique node identifier NodeID to each node i , and establish trust relationships between nodes; For each encrypted data segment E(D s )Calculate the hash value H(E(D s )), storage node number P(E(D s )); The encrypted data segment E(D s ) is stored in the number P(E(D s ))'s node.

7. The human resource management information integration method based on blockchain according to claim 1 is characterized in that: The submitted access request at least includes the autonomous identity, the identifier of the encrypted data segment requested to be accessed, and the function f that is desired to be executed.

8. The human resource management information integration method based on blockchain according to claim 1 is characterized in that: Use the target recipient's ECC public key pk rec Encrypt the encrypted aggregation result E(R); publish the encrypted result as transaction data to the blockchain network; Record transaction hash values, timestamps, and sender and receiver identities; Notifying the authorized target recipient that new analysis results are available; the target recipient obtains the encrypted results from the blockchain; Use the receiver's private key sk rec Decrypt and get the final analysis result R.

Images