A method and system for secure storage of credit information data

Abstract

This invention provides a secure storage method and system for credit information data, relating to the field of data processing technology. The method includes: constructing a secure storage architecture based on blockchain; acquiring credit information data through data nodes; when a data node initiates an upload request for credit information data to the blockchain, verifying the data node's upload qualification through a supervisory node; collecting transaction requests broadcast in the blockchain network through storage nodes, and concatenating the hash values ​​of each credit information data fragment into a hash vector after collecting a preset number of legitimate credit information data fragments; setting an index value for the hash vector through storage nodes, making a commitment to the hash vector based on a bilinear mapping, placing the calculated commitment value into the block header, and storing the collected credit information data fragments into the block body to generate a new block; and adding the generated block to the blockchain network through storage nodes based on an improved consensus mechanism of credit decay.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method and system for securely storing credit information data. Background Technology

[0002] Credit data is crucial information for assessing the creditworthiness of individuals or businesses, encompassing multiple aspects such as borrowing records, repayment history, and financial status. It plays a vital role in decision-making in finance, lending, and insurance, helping stakeholders understand an individual's repayment ability and credit risk, thus enabling accurate risk assessments and decisions. Because credit data involves sensitive personal or corporate privacy, its security is paramount. Data breaches or tampering can cause severe financial losses to individuals or businesses and undermine the foundation of trust in the financial system. Therefore, employing effective secure storage solutions, such as blockchain technology, to ensure the integrity, privacy, and verifiability of credit data is key to ensuring the stable operation of the financial industry, enhancing the transparency of the credit system, and preventing fraud.

[0003] Traditional blockchain storage methods primarily use Merkle trees to store data, with the Merkle root serving as the commitment value for the stored data. This method involves a large amount of computation and cannot perform batch verification of the data. Summary of the Invention

[0004] In view of the shortcomings of the prior art, the purpose of this invention is to provide a secure storage method and system for credit data, which can solve the technical problems of the prior art, which uses Merkle trees to store data, uses the Merkle root as a commitment value to make commitments to the stored data, has a large amount of computation, and cannot perform batch verification of data.

[0005] A first aspect of this invention provides a method for securely storing credit information data, comprising:

[0006] S1: Construct a secure storage architecture based on blockchain, which includes: data nodes, storage nodes, and monitoring nodes;

[0007] S2: Obtain credit data through the data nodes;

[0008] S3: Encrypt the credit data through the data node;

[0009] S4: When the data node initiates an upload request for the credit data to the blockchain, the supervisory node verifies whether the data node is qualified to upload. If so, the data node initiates a transaction request containing the credit data, signs the transaction request using a public key, and broadcasts it to the entire blockchain network.

[0010] S5: Through the storage node, collect the transaction requests broadcast in the blockchain network. After collecting a preset number of legitimate credit data fragments, use a hash function to calculate the hash value of each credit data fragment, and concatenate the hash values ​​of each credit data fragment into a hash vector.

[0011] S6: Through the storage node, set an index value for the hash vector, make a commitment to the hash vector based on the bilinear mapping, put the calculated commitment value into the block header, and store the collected credit data fragments into the block body to generate a new block;

[0012] S7: Through the storage node, the generated block is added to the blockchain network based on the improved consensus mechanism of credit decay.

[0013] A second aspect of this invention provides a secure storage system for credit information data, comprising: a processor and a memory;

[0014] The memory stores programs or instructions that can run on the processor, which, when executed by the processor, implement the steps of the secure storage method for credit data as described in the first aspect.

[0015] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0016] (1) In this embodiment of the invention, a commitment is made to the hash vector based on bilinear mapping, the calculated commitment value is put into the block header, and the collected credit data fragments are stored in the block body to generate a new block. The commitment mechanism of bilinear mapping greatly reduces the amount of computation for data verification, without requiring all the computation of the entire data tree. At the same time, the storage proof calculated based on bilinear mapping can be flexibly split and aggregated to facilitate batch verification of data and improve the efficiency of credit data storage.

[0017] (2) In this embodiment of the invention, the generated blocks are added to the blockchain based on the improved consensus mechanism of credit decay. By dynamically adjusting the credit value of nodes, nodes can be incentivized to remain honest and non-compliant behavior can be punished. Compared with traditional consensus mechanisms, this mechanism can ensure that the behavior of nodes is linked to their credit, enhancing the stability and reliability of the blockchain network, thereby improving the fairness and security of the credit data storage system. Attached Figure Description

[0018] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts. Obviously, the drawings described below are merely some embodiments of the present invention, and those skilled in the art can obtain other drawings based on these drawings without any creative effort.

[0019] Figure 1 This is a flowchart illustrating a method for securely storing credit data provided in an embodiment of the present invention.

[0020] Figure 2 This is a schematic diagram of a node in a secure storage architecture provided by an embodiment of the present invention.

[0021] Figure 3 This is a schematic diagram of a comprehensive credit score structure provided in an embodiment of the present invention.

[0022] Figure 4 This is a schematic diagram of the structure of a credit data security storage system provided in an embodiment of the present invention. Detailed Implementation

[0023] To enable those skilled in the art to better understand the technical solutions in the embodiments of the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. It should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0024] The following description, in conjunction with the accompanying drawings, details the secure storage method for credit information data provided by the embodiments of the present invention through specific examples and application scenarios.

[0025] Reference manual attached Figure 1 The diagram illustrates a flowchart of a method for securely storing credit data according to an embodiment of the present invention.

[0026] This invention provides a method for securely storing credit information data, which may include the following steps:

[0027] S1: Build a secure storage architecture based on blockchain.

[0028] Reference manual attached Figure 2 The diagram shows a node schematic of a secure storage architecture provided by an embodiment of the present invention.

[0029] The secure storage architecture includes: data nodes, storage nodes, and monitoring nodes.

[0030] Furthermore, data nodes are the core nodes in the blockchain network responsible for collecting and processing credit data. They acquire credit data from external systems and encrypt it to ensure data privacy and security. Before uploading data to the blockchain, data nodes must initiate an upload request and, according to system regulations, verify their upload eligibility with regulatory nodes to ensure the data's legality. Data nodes are responsible for maintaining the accuracy and integrity of the data, providing original credit information.

[0031] Furthermore, storage nodes are the nodes in a blockchain network responsible for storing and managing block data. Their primary task is to collect broadcast transaction requests, especially credit data fragments, perform hash calculations, and ultimately concatenate the data fragments into a hash vector. Storage nodes are also responsible for generating new blocks and placing the block's commitment value into the block header, ensuring data integrity and security. The role of storage nodes is to ensure that data in the blockchain can be securely stored and efficiently verified.

[0032] Furthermore, the oversight node is a key component of the blockchain network, responsible for controlling and managing the upload eligibility of data nodes. It ensures that each data node's behavior within the system complies with regulations by setting an oversight vector and implementing a bilinear mapping commitment. When a data node requests to upload data, the oversight node performs eligibility verification to confirm whether the node has upload permissions. The role of the oversight node is to guarantee the compliance and credibility of data uploads, preventing malicious nodes from uploading false or non-compliant data.

[0033] It's important to note that data nodes are responsible for collecting and encrypting credit data and initiating upload requests to regulatory nodes. Regulatory nodes verify the upload eligibility of data nodes, ensuring that only compliant nodes can upload data. Once granted upload permission, a data node initiates a transaction request containing encrypted data, signs it with its public key, and broadcasts it to the blockchain network. Subsequently, storage nodes collect these transaction requests, concatenate the hash values ​​of data fragments into hash vectors, and perform a bilinear mapping commitment to ensure data integrity. Finally, storage nodes store the data fragments in a new block and add them to the blockchain. These three elements work together, ensuring the system's security, transparency, and scalability through hierarchical access control, data verification, and efficient storage. The specific operational methods will be described later.

[0034] S2: Obtain credit data through data nodes.

[0035] S3: Encrypt credit data through data nodes.

[0036] Specifically, data is encrypted using symmetric or asymmetric encryption algorithms. Common encryption methods such as AES (symmetric encryption) or RSA (asymmetric encryption) convert the original data into ciphertext, preventing unauthorized access. During encryption, data nodes generate a key, which can be managed securely, such as through a Key Management System (KMS). Only authorized nodes or users with the correct decryption key can recover the encrypted credit data, ensuring its confidentiality and integrity. Simultaneously, data nodes generate a signature for the encrypted data, ensuring it is not tampered with during transmission within the blockchain network.

[0037] S4: When a data node initiates a request to upload credit data to the blockchain, the supervisory node verifies whether the data node is qualified to upload. If so, the data node initiates a transaction request containing the credit data, signs the transaction request using the public key, and broadcasts it to the entire blockchain network.

[0038] In this embodiment of the invention, by verifying the upload eligibility of data nodes through a supervisory node, it is effectively ensured that only authorized and compliant nodes can upload credit data, preventing malicious or non-compliant nodes from uploading false or insecure data. This mechanism enhances data credibility and system security, helping to maintain the integrity and transparency of the blockchain network. Simultaneously, data nodes using public keys to sign transaction requests ensure the immutability and integrity of the data, guaranteeing the security of data transmission and storage within the blockchain network. This effectively prevents potential attacks and data leaks, improving the overall system reliability and trustworthiness.

[0039] In one possible implementation, step S4, which verifies whether a data node is qualified to upload data via a monitoring node, specifically includes sub-steps S401 to S404:

[0040] S401: Through a custodian node, a custodian vector is set, and a commitment is made to the custodian vector based on a bilinear mapping. Each element of the custodian vector represents the upload qualification of a data node, and the commitment is made through a bilinear mapping to ensure that the information of these data nodes cannot be tampered with in the blockchain.

[0041] S402: When a new data node joins the blockchain network, an index is assigned to the new data node in the regulatory vector, and the corresponding checksum is set to 1. This provides the new data node with proof of eligibility for subsequent data upload operations. This step ensures that newly joined nodes are compliantly incorporated into the system and granted appropriate permissions.

[0042] S403: When a data node fails, the checksum corresponding to the data node's index in the regulatory vector is set to 0, indicating that the node is no longer eligible to upload data. The data node's commitment is then updated to reflect its failure status. This step helps ensure that non-compliant or faulty nodes do not continue to participate in data uploading, guaranteeing the normal operation of the system.

[0043] S404: Through the monitoring node, the corresponding verification value is queried according to the index of the data node in the monitoring vector to verify whether the data node is qualified to upload. When the verification value is 1, it means that the data node is qualified to upload; when the verification value is 0, it means that the data node is not qualified to upload. This step ensures that only legitimate and compliant nodes can participate in data uploading, effectively preventing malicious operations by non-compliant nodes.

[0044] S5: Through storage nodes, collect transaction requests broadcast in the blockchain network. After collecting a preset number of legitimate credit data fragments, use a hash function to calculate the hash value of each credit data fragment, and concatenate the hash values ​​of each credit data fragment into a hash vector.

[0045] Specifically, the primary task of storage nodes is to collect transaction requests broadcast on the blockchain network, particularly legitimate fragments involving credit data. Once a sufficient number of legitimate credit data fragments are received, the storage node uses a hash function to hash each fragment, generating a unique hash value. These hash values ​​represent the digital fingerprint of each data fragment, ensuring data integrity and consistency. Next, the storage node concatenates these hash values ​​into a hash vector. This hash vector contains a summary of all credit data fragments, facilitating subsequent verification and storage. The use of hash vectors improves data processing efficiency, reduces storage requirements, and enhances data verifiability and security, ensuring the immutability of data within the blockchain.

[0046] Optionally, there are many types of hash functions, and those skilled in the art can select any hash function according to the actual situation. This invention does not limit the selection.

[0047] S6: By using storage nodes, set index values ​​for hash vectors, make commitments to hash vectors based on bilinear mapping, put the calculated commitment values ​​into the block header, and store the collected credit data fragments into the block body to generate a new block.

[0048] In one possible implementation, the commitment to the hash vector based on the bilinear mapping in S6 specifically includes sub-steps S601 to S603:

[0049] S601: Generate a bilinear mapping:

[0050]

[0051] in, e Represents the bilinear mapping pairing function. G Represents a cyclic addition group. G T Let represent a cyclic multiplicative group. The bilinear mapping pairing function is used to map elements from two cyclic additive groups to a cyclic multiplicative group.

[0052] It should be noted that bilinear mapping can guarantee the verifiability and tamper resistance of data, ensuring that the commitment value of the hash vector can be effectively bound to the data. The properties and principles of bilinear mapping are already well-established and will not be elaborated upon in this invention.

[0053] S602: Generate random generators and a set of random numbers in the cyclic additive group of a bilinear mapping, and compute the commitment basis:

[0054]

[0055] in, h i Indicates the first i A commitment base for data, g Represents a random generator. , r i Indicates the generated first i A random number.

[0056] It should be noted that the use of random generators and random numbers enhances the security of data commitments and ensures the privacy and unpredictability of the data verification process.

[0057] S603: Calculate the commitment value of the hash vector using the commitment basis:

[0058]

[0059] in, D Indicates the commitment value. v i Represents the first in the hash vector i The data, that is, the first data point. i The hash value of a credit data segment. q This represents the total length of the hash vector, which is the total number of credit data fragments.

[0060] It should be noted that using the commitment base to calculate the commitment value of the hash vector can significantly reduce the complexity of verification calculations while ensuring data integrity, and enable batch verification of multiple data fragments, thus improving system efficiency. The commitment value is then used as a digest value and placed in the block header to ensure the integrity and consistency of all data fragments in the hash vector.

[0061] In this embodiment of the invention, a commitment is made to the hash vector based on bilinear mapping, the calculated commitment value is put into the block header, and the collected credit data fragments are stored in the block body to generate a new block. The commitment mechanism of bilinear mapping greatly reduces the amount of computation for data verification without requiring all the computation of the entire data tree. At the same time, the storage proof calculated based on bilinear mapping can be flexibly split and aggregated to facilitate batch verification of data and improve the efficiency of credit data storage.

[0062] S7: Through storage nodes, blocks generated are added to the blockchain network based on an improved consensus mechanism with credit decay.

[0063] It should be noted that the improved consensus mechanism based on credit decay classifies storage nodes into four types: master nodes, committee nodes, alternate nodes, and ordinary nodes.

[0064] Furthermore, the master node is used to initiate elections, participate in voting, and collect node behavior data; the master node is also a member of the committee nodes.

[0065] Furthermore, committee nodes are used to achieve consensus using the PBFT mechanism.

[0066] Furthermore, before entering the committee and becoming a committee node, the alternate node is the same as the ordinary node and does not participate in consensus. When a vacancy occurs in the committee node, the alternate node fills the vacancy in order.

[0067] Furthermore, ordinary nodes do not participate in consensus.

[0068] The credit score of each node employs a two-way credit decay mechanism, ensuring that the credit score of each node consistently remains at a moderate level. For an explanation of this two-way credit decay mechanism, please refer to the section on decay value calculation later in the text.

[0069] In this embodiment of the invention, an improved consensus mechanism based on credit decay adds generated blocks to the blockchain. By dynamically adjusting the credit value of nodes, it incentivizes nodes to maintain honesty and punishes non-compliant behavior. Compared with traditional consensus mechanisms, this mechanism ensures that node behavior is linked to its credit, enhancing the stability and reliability of the blockchain network, thereby improving the fairness and security of the credit data storage system.

[0070] In one possible implementation, the election method for committee nodes is as follows: a comprehensive credit value is calculated by weighting the inter-node voting results with the basic credit value; the nodes are then sorted in descending order of their comprehensive credit values; based on the sorting results, the storage node with the highest comprehensive credit value is determined as the master node; and the nodes ranked higher in the order are then selected as the master nodes. N b One storage node was identified as a committee node. N b Representing a positive integer, the ranking will be... N b +1 to 1.5 N b The storage node was identified as a candidate node.

[0071] In this embodiment of the invention, the credit-based election mechanism ensures that the elected master nodes and committee nodes have high credibility in their behavior by comprehensively weighting credit value and voting results, thereby enhancing the transparency and fairness of the system, while improving the stability of the blockchain network and the security of the credit data storage system.

[0072] Reference manual attached Figure 3 The diagram shows a structural schematic of a comprehensive credit score provided by an embodiment of the present invention.

[0073] Optionally, the calculation method for the comprehensive credit score is as follows:

[0074]

[0075] in, S u Indicates the first u The overall credit score of each node, n u Indicates the first u The number of votes a node receives during the election phase N A This represents the total number of all nodes. α This represents the voting weighting coefficient. C u Indicates the first u The basic credit value of each node.

[0076] Among these, those skilled in the art can set the voting weight coefficient according to the actual situation. α The size is not limited in this invention.

[0077] In this embodiment of the invention, the number of votes a node receives during the election phase and its basic credit score are combined, and a weighted summation method is used to fairly reflect a node's performance and reputation within the network. This is achieved through voting weight coefficients. αThe system can flexibly adjust the influence ratio between voting results and node credit value, balance node behavior performance and credit accumulation, and avoid over-reliance on voting or over-reliance on basic credit value, thereby improving the fairness and flexibility of the election process.

[0078] Optionally, the base credit score is updated based on the decay value, reward value, and penalty value determined using a two-way credit decay mechanism:

[0079]

[0080] in, Indicates the first u The node at the th t +1 base credit value on the block, min indicates taking the smaller value, max indicates taking the larger value. Indicates the first u The node at the th t The basic credit value on each block, Indicates the first u The node at the th t The attenuation value determined by the two-way credit attenuation mechanism on each block. Indicates the first u The node at the th t The reward value on each block, Indicates the first u The node at the th t The penalty value on each block.

[0081] In this embodiment of the invention, by limiting the maximum and minimum values, the credit value of a node is ensured to fluctuate within the range [0, 100], avoiding excessive decay or excessive reward. The decay value changes dynamically according to the node's behavior, the reward value incentivizes nodes to contribute positive behavior, and the penalty value effectively punishes non-compliant behavior. This mechanism not only maintains the fairness and flexibility of the system but also enhances the stability of the blockchain network, ensuring that the behavior of nodes always conforms to network rules, thereby improving overall security and fairness.

[0082] In traditional blockchain node credit update methods, a node's credit is typically updated based on its historical behavior. For example, a node earns points based on its participation in consensus, processing transactions, or verifying data; the higher the points, the greater the node's credit value. These points may be updated periodically based on factors such as node activity and participation. Traditional methods often place too much weight on a node's historical performance, leading to some nodes having persistently high or low credit values, failing to reflect their current behavior. Malicious node behavior can have a long-term negative impact on their credit, while honest nodes may be permanently penalized for temporary errors due to network issues, resulting in persistently low credit values. Traditional credit update methods struggle to represent a node's true credit level. This application employs a unique two-way credit decay mechanism to update node credit.

[0083] Optionally, the calculation method for the attenuation value determined using the two-way credit attenuation mechanism is as follows:

[0084]

[0085] in, k Indicates the attenuation parameter. k It is a positive integer less than 49. k The larger the value, the slower the credit score decays.

[0086] In this embodiment of the invention, in the two-way credit decay mechanism, the credit value of a node, regardless of its initial value, will gradually approach 50 as the blockchain height increases. This means that no matter how a node has performed in the past, its credit value will remain within a reasonable range over time, avoiding the long-term impact of excessively high or low credit values ​​on the node's future behavior.

[0087] Furthermore, different decay formulas are used based on different credit ranges (low, medium, and high credit scores), thus achieving precise credit adjustment. When a node's credit score is low, the decay value is larger, incentivizing the node to improve its behavior. When the credit score is high, the decay value is smaller, helping to maintain the node's motivation and avoid excessive punishment. Decay Parameters k The settings offer flexibility. k The larger the credit score, the slower the credit score decays, allowing the system to balance changes in credit scores according to different needs. The advantage of this approach is that it ensures that a node's credit score fluctuates within a reasonable range, avoiding both excessive penalties and excessive accumulation of node credit, thereby maintaining the network's fairness, stability, and adaptability.

[0088] Optionally, the reward value is calculated as follows:

[0089]

[0090] in, Indicates the first u The node at the th t Scoring of newly generated transactions is continuously verified on each block. a 1, Indicates the first u The node at the th t Scoring of continuously submitted transactions on each block a 2, Indicates the first u The node at the th t Scoring of active response to node requests on each block a 3, β 1. β 2. β 3 represents the reward weighting coefficient.

[0091] Among these, those skilled in the art can set the reward weighting coefficient according to the actual situation. β 1. β 2. β The size of 3 is not limited in this invention.

[0092] In this embodiment of the invention, this reward value calculation method based on node behavior scoring allows for a more detailed evaluation of a node's performance in the consensus process. A node's reward value is a weighted score based on its continuous behavior in validating new transactions, submitting transactions, and responding to requests within a block, ensuring that appropriate rewards are given for each type of contribution made by the node.

[0093] Optionally, the penalty value is calculated as follows:

[0094]

[0095] in, Indicates the first u The node at the th t The penalty value on each block, Indicates the first u The node at the th t Scoring of behavior that continuously submits expired transaction verification information on each block b 1, Indicates the first u The node at the th t Scoring of repeated transaction behavior continuously submitted on each block b 2, Indicates the first u The node at the th t Scoring of behavior that continuously submits error verification messages on each block b 3, Indicates the first u The node at the th t Scoring for persistent failure to verify transactions on a given block.b 4, γ 1. γ 2. γ 3. γ 4 represents the penalty weighting coefficient.

[0096] Among them, those skilled in the art can set the penalty weight coefficient according to the actual situation. γ 1. γ 2. γ 3. γ The size of 4 is not limited in this invention.

[0097] In this embodiment of the invention, by using this penalty value calculation method based on node misconduct scoring, non-compliant behavior of nodes in the consensus process can be accurately assessed, and corresponding penalties can be imposed according to different types of violations.

[0098] Optionally, the penalty value can be determined by dynamically adjusting the penalty intensity.

[0099] The penalty value calculated based on negative behavior is used as the base penalty value. The current blockchain height is obtained, i.e., the block height at the time of consensus. The node's penalty deadline is obtained and compared to the current blockchain height. If the node's penalty deadline is less than the current blockchain height (i.e., the node's penalty has expired), the penalty multiplier is set to 1. Otherwise, the penalty multiplier is increased by 1, but not exceeding 5, and the node's penalty deadline is extended by 20 blocks. Finally, the base penalty value is multiplied by the penalty multiplier to obtain the final penalty value.

[0100] In this embodiment of the invention, by dynamically adjusting the penalty intensity, the strength of the penalty can be flexibly adjusted according to the node's behavior and consensus progress. Specifically, when a node's penalty period expires, its penalty multiplier will revert to 1, avoiding long-term unfair penalties due to temporary errors or network problems. When a node continues to perform poorly, the penalty multiplier will gradually increase, up to a maximum of 5 times, which can more effectively punish repeated malicious behavior while providing nodes with a chance to recover. This approach ensures that the penalty for nodes is both fair and flexible, while avoiding excessive punishment for occasional problems. It helps to balance the fairness of the penalty with the stability of the system, promotes the continuous and positive participation of nodes in consensus, and improves the overall health of the network.

[0101] In one possible implementation, S7 specifically includes sub-steps S701 to S703:

[0102] S701: The storage node initiates an on-chain request as a regular node, and forwards the on-chain request to each committee node through the master node.

[0103] S702: After receiving the on-chain request, each committee node votes and returns the voting results to the storage node.

[0104] S703: When more than half of the committee nodes vote in favor of the on-chain request, the block generated by the storage node is added to the blockchain network.

[0105] In this embodiment of the invention, this onboarding request process ensures that the addition of data storage nodes to the blockchain network undergoes rigorous review and approval. First, the storage node initiates an onboarding request as a regular node, which is then forwarded to committee nodes for voting by the master node. This ensures the joint participation and decision-making of multiple nodes, avoiding control or bias from a single node. The committee nodes decide whether to accept the onboarding request based on the voting results. When more than half of the nodes agree, the democratic and decentralized decision-making process is ensured. This process effectively prevents malicious or non-compliant nodes from arbitrarily joining the blockchain, thereby improving the security, fairness, and transparency of the blockchain network.

[0106] In one possible implementation, after S7, the following is also included:

[0107] S8: Generate data storage proof through the storage node. The data storage proof is used to prove the integrity and correctness of the credit data fragment.

[0108] In this embodiment of the invention, by generating a data storage proof, storage nodes can provide an additional layer of verification for credit data fragments within a block. This proof mechanism allows other users to easily verify the integrity and correctness of data within a block without relying on all nodes of the entire blockchain. The data storage proof provides verifiable evidence of the data, enhancing the transparency and trustworthiness of the blockchain network, ensuring that the data cannot be tampered with, and reducing the computational complexity of the verification process. This mechanism improves system security and user trust in blockchain data, helping to ensure the reliability and long-term validity of credit data.

[0109] In one possible implementation, S8 specifically includes sub-steps S801 and S802:

[0110] S801: Generates a random generator and a set of random numbers through bilinear mapping, and calculates the cross terms between various credit data segments:

[0111]

[0112] in, h i,j Indicates the first i The first credit data fragment and the first jIntersection terms between credit data fragments are used to bind the hash vector to the first... i The location of the first credit data segment is related to the first... j The relationship between the locations of individual credit data segments g Represents a random generator. , r i Indicates the generated first i A random number, r j Indicates the generated first j A random number.

[0113] It should be noted that calculating cross terms through bilinear mapping can bind the relationships between data segments in a hash vector. Cross terms ensure the interdependence and positional association between data segments, increasing the complexity and security of data verification.

[0114] S802: Based on the intersections between various credit data segments, perform cross-validation to generate a data storage proof.

[0115]

[0116] in, Represents a set of credit data fragments I Data storage proof, I This represents a set of credit data fragments. v j Represents the first in the hash vector j The first data point, which is the first data point in the set of credit data fragments. j The hash value of a credit data segment. This indicates that, in addition to the set of credit data fragments, I An index of all credit data fragments except those mentioned above.

[0117] It should be noted that a data storage proof is calculated by cross-validating the hash values ​​of each data fragment in the cross-item and hash vector. This proof verifies the set of data fragments. I The hash value is combined with the hash values ​​of all other data fragments, leveraging the properties of a bilinear mapping to ensure the uniqueness of each data fragment's position in the blockchain and the integrity of the data. Ultimately, the generated data storage proof can be used by any user to verify the correctness and integrity of data fragments within a block, thereby enhancing data credibility and security.

[0118] Reference manual attached Figure 4 The diagram shows a structural schematic of a credit data security storage system provided by an embodiment of the present invention.

[0119] This invention provides a credit data security storage system 20, including: a processor 201 and a memory 202;

[0120] The memory 202 stores programs or instructions that can run on the processor 201. When the program or instructions are executed by the processor 201, they implement the steps of the above-described secure storage method for credit data and achieve the same technical effect. To avoid repetition, the present invention will not elaborate further.

[0121] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the embodiments of the present invention, and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the protection scope of the present invention.

Claims

1. A method for securely storing credit information data, characterized in that, include: S1: Construct a secure storage architecture based on blockchain, which includes: data nodes, storage nodes, and monitoring nodes; S2: Obtain credit data through the data nodes; S3: Encrypt the credit data through the data node; S4: When the data node initiates an upload request for the credit data to the blockchain, the supervisory node verifies whether the data node is qualified to upload. If so, the data node initiates a transaction request containing the credit data, signs the transaction request using a public key, and broadcasts it to the entire blockchain network. S5: Through the storage node, collect the transaction requests broadcast in the blockchain network. After collecting a preset number of legitimate credit data fragments, use a hash function to calculate the hash value of each credit data fragment, and concatenate the hash values ​​of each credit data fragment into a hash vector. S6: Through the storage node, set an index value for the hash vector, make a commitment to the hash vector based on the bilinear mapping, put the calculated commitment value into the block header, and store the collected credit data fragments into the block body to generate a new block; S7: Through the storage node, the generated block is added to the blockchain network based on the improved consensus mechanism of credit decay; In the improved consensus mechanism based on credit decay, the storage nodes are classified into the following types: master node, committee node, alternate node, and ordinary node. The master node is used to initiate elections, participate in voting, and collect node behavior; the master node is also a member of the committee nodes. The committee nodes are used to achieve consensus using the PBFT mechanism. Before entering the committee and becoming a committee node, the candidate node is the same as the ordinary node and does not participate in consensus. When a vacancy occurs in the committee node, the candidate node fills the vacancy in order. The ordinary nodes do not participate in consensus. The credit of each node adopts a two-way credit decay mechanism, so that the credit value of each node always tends to a medium level. Specifically, S7 includes: S701: The storage node initiates an on-chain request as a regular node, and forwards the on-chain request to each committee node through the master node; S702: After receiving the chain entry request, each committee node votes and returns the voting results to the storage node; S703: When more than half of the committee nodes vote in favor of the on-chain request, the block generated by the storage node is added to the blockchain network.

2. The method for securely storing credit information data according to claim 1, characterized in that, The step S4, which verifies whether the data node is qualified to upload data through the monitoring node, specifically includes: S401: Through the regulatory node, a regulatory vector is set, and a commitment is made to the regulatory vector based on a bilinear mapping; S402: When a new data node joins the blockchain network, an index is assigned to the new data node in the regulatory vector, and the verification value corresponding to the index is set to 1, providing the qualification certificate of the index to the new data node; S403: When a data node fails, set the check value corresponding to the index of the data node in the regulatory vector to 0 and update the commitment of the data node. S404: Through the monitoring node, according to the index of the data node in the monitoring vector, query the corresponding verification value to verify whether the data node has the qualification to upload. When the verification value is 1, it means that the data node has the qualification to upload. When the verification value is 0, it means that the data node does not have the qualification to upload.

3. The method for securely storing credit information data according to claim 1, characterized in that, The commitment to the hash vector based on the bilinear mapping in S6 specifically includes: S601: Generate a bilinear mapping; S602: Generate a random generator and a set of random numbers in the cyclic additive group of the bilinear mapping, and calculate the commitment basis; S603: Calculate the commitment value of the hash vector using the commitment base.

4. The method for securely storing credit information data according to claim 1, characterized in that, The election method for the committee nodes is as follows: A comprehensive credit score is calculated by weighting the inter-node voting results with the basic credit score. The nodes are then sorted in descending order of their comprehensive credit scores. Based on this sorting, the storage node with the highest comprehensive credit score is designated as the master node. The nodes ranked higher in the sorting are then... N b One storage node was identified as the committee node. N b Representing a positive integer, the ranking will be... N b +1 to 1.5 N b The storage node was determined as the candidate node.

5. The method for securely storing credit information data according to claim 4, characterized in that, The base credit score is updated based on the attenuation value, reward value, and penalty value determined using the two-way credit attenuation mechanism.

6. The method for securely storing credit information data according to claim 1, characterized in that, Following S7, it also includes: S8: Generate a data storage certificate through the storage node. The data storage certificate is used to prove the integrity and correctness of the credit data fragment.

7. The method for securely storing credit information data according to claim 6, characterized in that, S8 specifically includes: S801: Generates a random generator and a set of random numbers through bilinear mapping, and calculates the cross terms between various credit data segments; S802: Based on the intersections between the various credit data fragments, perform cross-validation to generate the data storage proof.

8. A secure storage system for credit information data, characterized in that, include: processor; A memory storing computer-readable instructions, which, when executed by the processor, implement the secure storage method for credit information data as described in any one of claims 1 to 7.

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