Efficient instrument control data circulation method based on block chain

Abstract

The invention belongs to the technical field of information security, particularly relates to data circulation of a block chain, zero-knowledge proof and confidentiality protection, and particularly provides an efficient instrument control data circulation method based on the block chain, which is used for overcoming the problem of mutual restriction of data correctness and confidentiality in an instrument control data circulation process. According to the method, the regular expression is adopted, so that the data content can be processed, and the defect that an existing data circulation technology is insufficient in data content support is overcome; a challenge mechanism is adopted, so that the whole data set can be prevented from being proved, and the calculation overhead is remarkably reduced; the recursive proof system is adopted to efficiently generate the proof of the challenge data set, the proof is concise, and efficient verification can be carried out on the block chain, so that it is ensured that the proof generation and verification efficiency is further optimized. Based on the core technologies, the efficient data circulation method with correctness and confidentiality guarantee is realized.

Description

Technical Field

[0001] This invention belongs to the field of information security technology, and specifically relates to data flow based on blockchain, zero-knowledge proof and confidentiality protection. It provides a method for efficient instrumentation and control data flow based on blockchain. Background Technology

[0002] Industrial control networks (ICS), including instrumentation and control systems, are a key infrastructure for intelligent manufacturing. By deploying sensors and controllers, they can collect information such as equipment status, process parameters, and quality indicators in real time. HMS Networks' 2025 report predicts that the industrial network market will grow by 7.7% cumulatively by 2030. Massive amounts of industrial data enhance the decision-making flexibility and risk control capabilities of ICS. For example, GE Power's Predix platform uses equipment health monitoring to achieve planned maintenance, and Siemens MindSpher improves equipment efficiency and reduces maintenance costs through real-time analysis. In this process, data flows frequently among multiple parties. Blockchain, due to its decentralized and trustless characteristics, can provide a consensus mechanism acceptable to all parties, solving the trust problem between participants.

[0003] In recent years, research on instrumentation and control (ICS) data flow has developed rapidly, including fine-grained access control and privacy protection technologies, secure data sharing frameworks, fair data transaction protocols, and zero-knowledge proof-based methods. Despite these achievements, data flow for ICS still has shortcomings: First, support for textual information such as descriptions, logs, and documents is limited, ignoring the rich information within the text; second, it is difficult to properly balance data accuracy and confidentiality, as non-compliant data flow leads to additional resource waste, while directly presenting data to the requesting party compromises confidentiality; finally, on-chain overhead is high, hindering practical deployment.

[0004] Therefore, for instrumentation and control data, there is an urgent need to design a data transfer method that can efficiently prove the correctness of the data while protecting its confidentiality. Summary of the Invention

[0005] The purpose of this invention is to provide a blockchain-based method for efficient instrumentation and control data transfer, in order to overcome the problem of mutual constraints between data correctness and confidentiality during the instrumentation and control data transfer process.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] A blockchain-based method for efficient instrumentation and control data transfer, characterized by the following steps:

[0008] Step 1: The data provider (DP) collects data from the management and control equipment to obtain a dataset;

[0009] Step 2: The data provider (DP) preprocesses the dataset using an Indexed Merkle Tree (IMT). Make a commitment, obtain the commitment value of the dataset and distribute it to the Data Requester (DR); and generate a description for the dataset to be displayed on the bulletin board;

[0010] Step 3: The data requester searches for the target dataset from the data provider's bulletin board and sends a data request to the data provider;

[0011] Step 4: After receiving the data request, the data provider generates a certificate and sends it to the blockchain (BC). The smart contract deployed on the blockchain verifies the certificate and returns the verification result to the data provider.

[0012] Step 5: If the verification result is successful, the data provider sends the target dataset to the data requester. The data requester calculates the Merkle root of the received dataset. If it is the same as the promised value, the data requester confirms the transfer and accepts the dataset.

[0013] Furthermore, in step 1, the dataset is represented as : Each data point is represented as follows: ,in, This represents the j-th attribute. This represents the data corresponding to the j-th attribute. Indicates the number of attributes. Indicates the quantity of data.

[0014] Furthermore, in step 2, the Indexed Merkle Tree (IMT) includes: , This refers to the Merkle tree generation algorithm. This represents the Merkle tree existence proof algorithm. This represents the Merkle tree verification algorithm; DP is achieved by calling... Algorithm generates dataset Merkelgen As a dataset The commitment value;

[0015] DP is the dataset Generate description , This indicates the criteria that each attribute should meet. Represents the dataset A brief description; Represented in JSON format, denoted as , This represents the regular expression that the j-th attribute should satisfy.

[0016] Furthermore, in step 3, the data request includes: a description of the challenge index set and the target dataset, wherein the challenge index set is represented as... ,in, Indicates the length of the challenge index set. , Indicates the first A challenge index.

[0017] Furthermore, the specific process of step 4 is as follows:

[0018] Step 4.1: Regular expression preprocessing;

[0019] Concatenate all regular expressions in the dataset description into a single regular expression. Specifically, it is expressed as: , This represents the regular expression that the j-th attribute should satisfy. Indicates the number of attributes;

[0020] Correspondingly, all related data in the dataset are concatenated into a single value. Specifically, it is expressed as: ;

[0021] Step 4.2, Design of IVC function F;

[0022] The IVC function F consists of two sub-functions: regularity checking and Merkle root verification, denoted as follows: and , for the meaning of the first Challenge Index Corresponding challenge data :

[0023] Used to check if data meets a predefined regular expression, the regular expression Compile into an automaton, As input to the automaton, the automaton performs state checks and outputs an identifier. ,when When, it means that the data satisfies the regular expression. ;

[0024] For inspection Does it exist in the dataset? Specifically, DP first calls The algorithm calculates the existence proof of Merkel. Proof of Merkel's existence As input, then execute Algorithm verification Compliance;

[0025] The IVC function F evaluates to 1 when both regularity checks and Merkle root verification are satisfied; otherwise, the IVC function F evaluates to 0.

[0026] Step 4.3: Initialization;

[0027] The Nova proof system is used to prove the correctness of the IVC function F. First, the IVC is calculated to generate the IVC proof. Then, the proof compressor Decider compresses the IVC proof into a concise zero-knowledge proof.

[0028] IVC includes: , respectively, represent the IVC public parameter generation algorithm, the proof key and verification key generation algorithm, the proof generation algorithm, and the proof verification algorithm;

[0029] Decider includes: , respectively, represent the algorithm for generating the Decider's public parameters, the algorithm for generating the proof key and the verification key, the proof generation algorithm, and the proof verification algorithm;

[0030] First, the DP calling algorithm and Generate common parameters for IVC and Decider. and , Indicate the safety parameters; then, call the algorithm. and Generate key pairs for IVC and Decider. and , Indicates the proof key. This indicates the verification key; simultaneously, DP invokes the algorithm. Generate challenge data Merkel's existence proof ;

[0031] Step 4.4: IVC proof generation;

[0032] DP calling algorithm IVC proof for generating the first i challenge data , This represents the initial state for IVC calculation. Indicates the first calculation of IVC step, Indicates that IVC is calculated at the 1st The value of the step, Statement No. Merkel's existence proof for each data point Indicates the first A challenging set of data, Indicates the first The proof is generated step by step; until the final proof is generated. ;

[0033] Step 4.5: IVC verification;

[0034] DP calls the algorithm IVC proof for the validation challenge dataset Legality; Algorithm The result is 0 or 1, with 1 indicating IVC proof. Legal and All IVC calculations are correct; otherwise, terminate the current data transfer process.

[0035] Step 4.6: Generate concise zero-knowledge proofs;

[0036] DP calling algorithm IVC proof Compressed into concise zero-knowledge proofs ;

[0037] Step 4.7: On-chain contract generation;

[0038] The blockchain automatically generates smart contracts using the Sonobe library to verify concise zero-knowledge proofs. ;

[0039] Step 4.8: On-chain proof verification;

[0040] Blockchain (BC) runs smart contracts, and smart contracts call algorithms. The verification result is obtained. If the verification result is 1, it means that the proof is valid.

[0041] Furthermore, in step 5, the process by which the data requester calculates the Merkle root of the received dataset is as follows:

[0042] Call The algorithm recalculates the dataset Merkelgen, represented as , This represents the Merkle tree generation algorithm.

[0043] Based on the above technical solution, the beneficial effects of the present invention are as follows:

[0044] This invention provides a blockchain-based method for efficient instrumentation and control data transfer (referred to as ReDS). ReDS uses regular expressions to process the data content itself, overcoming the shortcomings of existing data transfer technologies in terms of insufficient support for data content. ReDS avoids proving the entire dataset, thereby significantly reducing computational overhead. ReDS uses a recursive proof system to efficiently generate proofs for challenging datasets. These proofs are concise and can be efficiently verified on the blockchain, further improving efficiency.

[0045] In summary, this invention provides a blockchain-based method for efficient instrumentation and control data transfer, which has the following advantages:

[0046] 1) Verifiability: Based on zero-knowledge proof regular expression matching technology, this invention realizes on-chain public verification of the correctness of instrumentation control data;

[0047] 2) Confidentiality: Thanks to the zero-knowledge nature of zero-knowledge proofs, this invention ensures that on-chain verification will not expose any plaintext information of the data;

[0048] 3) Computational efficiency: Thanks to the recursive proof system, this invention ensures the efficiency of the data preprocessing process, as well as the efficiency of the generation and verification of correctness proofs. Attached Figure Description

[0049] Figure 1 A flowchart illustrating the efficient instrumentation and control data transfer method based on blockchain provided by this invention. Detailed Implementation

[0050] To make the objectives, technical solutions, and beneficial effects of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0051] This embodiment provides a blockchain-based method for efficient instrumentation and control data transfer (referred to as ReDS), such as... Figure 1 As shown, it consists of three key entities:

[0052] Data Provider (DP): The DP manages a large number of instrumentation and control devices (such as programmable logic controllers (PLCs) and distributed control systems (DCS)) and collects the instrumentation and control data generated by these devices (such as network data, sensor data, etc.). This data is processed into different forms and then distributed to other participants.

[0053] Data Requester (DR): A DR is an entity that is interested in the data provided by the DP. After obtaining this data, the DR can use it for derivative purposes such as data analysis, customized application development, or compliance auditing. In the instrumentation and control system scenario, the DR can be a collaborator, who obtains data to perform operations such as system optimization and performance improvement.

[0054] Blockchain (BC): BC is a distributed, decentralized network that stores public information in a transparent and immutable manner; correspondingly, smart contracts are deployed on the blockchain and automatically executed when a request is received from a DP or DR; in this invention, BC can be any blockchain platform that supports smart contract execution, such as Ethereum or Hyperledger Fabric.

[0055] The ReDS provided in this embodiment is an interactive data transfer method between DP, DR, and BC. The specific process is as follows: Figure 1 As shown, the red text represents the three entities involved in this invention, the blue text represents the five stages of this invention, and the black text represents the auxiliary components required in this invention.

[0056] Specifically, the blockchain-based efficient instrumentation and control data transfer method includes the following steps:

[0057] Step 1: Data Collection;

[0058] DP manages a group of instrumentation and control equipment The data generated by these devices is collected by designated data acquisition tools and is denoted as a dataset. , is represented as: Each piece of data consists of several attributes and their corresponding values, denoted as . ,in, This represents the j-th attribute. This represents the value corresponding to the j-th attribute. Indicates the number of attributes;

[0059] Step 2, Data Processing;

[0060] DP processes the collected data and then distributes the appropriate portions (i.e., the data's commitment value and descriptive information) to the appropriate entities or devices.

[0061] Data Commitment: This invention employs Indexed Merkle Tree (IMT) to process the dataset. To make a commitment, IMT appends an index to each leaf node. IMT includes three algorithms. , This refers to the Merkle tree generation algorithm. This represents the Merkle tree existence proof algorithm. This represents the Merkle tree verification algorithm; DP is achieved by calling... Algorithm generates dataset Merkelgen As a dataset The commitment value;

[0062] Data Description: DP is the dataset Generate a description ,Should It will be displayed on DP's bulletin board; This indicates the criteria that each attribute should meet. Represents the dataset A brief description; specifically, Represented in JSON format, denoted as , The standard that the j-th attribute should meet is represented by a regular expression in this embodiment;

[0063] Step 3, Data Request;

[0064] The DR searches for datasets of interest from the DP's bulletin board. Once the DR finds data of interest, it will send a data request to the DP, including a challenge index set and the corresponding dataset. A brief description ( The challenge index set is represented as ,in, Indicates the length of the challenge index set. , Indicates the first A challenge index;

[0065] Subsequently, DR began waiting for the verification result sent by BC;

[0066] Step 4: Correctness verification;

[0067] After receiving the challenge information, the DP will generate a proof to demonstrate the correctness of the data without compromising its confidentiality. Subsequently, the proof will be sent to the blockchain (BC). At this point, the deployed smart contract will be automatically triggered to check whether the proof provided by the DP meets the requirements. If the proof does not meet the requirements, the BC will terminate the data transfer process and notify the DP that the data provided is non-compliant.

[0068] The specific process is as follows:

[0069] Step 4.1: Regular expression preprocessing;

[0070] Although each attribute corresponds to a different value, they are all bound by the same regular expression. Therefore, to avoid generating a separate proof for each attribute, all... Concatenate as a single regular expression Specifically, it is expressed as Correspondingly, all related Connect as a single value Since the order of the data remains unchanged, the concatenated data will remain in the same order. and Maintain the correspondence; the final correspondence is: That is, the value corresponding to each challenge index in the challenge index set conforms to the regular expression. Therefore, DP only needs to prove each satisfy ;

[0071] Step 4.2, Design of IVC function F;

[0072] The IVC function F consists of two sub-functions: regularity checking and Merkle root verification, denoted as follows: and , for the meaning of the first Challenge Index Corresponding challenge data :

[0073] Used to check if data meets a predefined regular expression, compiling the regular expression into an automaton. As input to the automaton, the automaton performs state checks and outputs an identifier. ,when When, it means that the data satisfies the regular expression. ;

[0074] For inspection Does it exist in the dataset? Specifically, DP first calls The algorithm calculates the existence proof of Merkel. Proof of Merkel's existence As input, then execute Algorithm verification Compliance;

[0075] When both regularity checks and Merkle root verification are satisfied, the IVC function F evaluates to 1; otherwise, it evaluates to 0. Typically, IVC calculation requires an initial state value, a number of calculations, and a final state. In this invention, the initial state value is set to 0, and the results are accumulated after each IVC calculation. Thus, for a length of... Given a challenging dataset, if each data point satisfies both checks of the IVC function F, then the final state value should be strictly equal to the dataset length. ;

[0076] Step 4.3: Initialization;

[0077] This invention employs the Nova proof system to prove the correctness of the IVC function F computation. Nova is a recursive zero-knowledge proof system that can generate zero-knowledge proofs for multiple data points at once by recursively performing IVC computations. Typically, the Nova proof system first performs IVC computation to generate IVC proofs, and then uses a proof compressor, Decider, to compress the final IVC proofs into concise zero-knowledge proofs. Both IVC and Decider include four algorithms. ,in, This indicates the common parameter generation algorithm. This represents the algorithm for generating the proof key and the verification key. This indicates the proof generation algorithm. This indicates the proof verification algorithm;

[0078] First, the DP calling algorithm and Common parameters required to generate IVC and Decider and , Indicate the safety parameters; then call the algorithm. and The key pair required to generate IVC and Decider and , Indicates the proof key. This represents the verification key, used by IVC and Decider to generate and verify proofs; simultaneously, DP invokes the algorithm. generate Merkel's existence proof ,prove It is indeed a dataset Data in the middle;

[0079] Step 4.4: IVC proof generation;

[0080] DP calling algorithm IVC proof for generating the first i challenge data , This represents the initial state for IVC calculation. Indicates the first calculation of IVC step, Indicates that IVC is calculated at the 1st The value of the step, Statement No. Merkel's existence proof for each data point Indicates the first One data point, Indicates the first The proof is generated step by step; until the final proof is generated. ;

[0081] Step 4.5: IVC verification;

[0082] DP calls the algorithm To verify the IVC proof of the challenge dataset Legality; Algorithm The result is 0 or 1, with 1 indicating IVC proof. Legal and If all IVC calculations are correct, the data can be further compressed into a concise zero-knowledge proof; otherwise, terminate the current data transfer process.

[0083] Step 4.6: Generate concise zero-knowledge proofs;

[0084] The compressor Decider will prove IVC. Compressed into concise zero-knowledge proofs The purpose of the compressor Decider is to prove the final IVC proof. Indeed satisfied This proves that IVC calculated The last proof Valid; DP call algorithm IVC proof Compressed into concise zero-knowledge proofs ;

[0085] Step 4.7: On-chain contract generation;

[0086] Generating zero-knowledge proofs Then, DP further generates verification proofs. This invention generates smart contracts for blockchain verification; it automatically generates smart contracts by applying a variant of Nova—the Sonobe library—based on zero-knowledge proofs. The verification process is reproduced using the Solidity language, thereby achieving efficient on-chain verification of proofs;

[0087] Step 4.8: On-chain proof verification;

[0088] BC runs smart contracts to verify zero-knowledge proofs. The validity of the data is verified by outputting either 0 or 1, where 1 represents a valid proof, meaning that DP has proven that the challenge data of DR satisfies the regular expression standard. Specifically, the smart contract verifies this by calling... The verification result is either 0 or 1, where, The common inputs are represented by the initial state, the number of computations (consistent with the length of the challenge dataset), and the final state. Here, ensuring the equality of the number of computations and the final state value guarantees that all data in the challenge dataset satisfies the regular expression standard. Simultaneously, this proof... It only indicates that the data meets a specific regular expression standard, without exposing other information about the data itself, thus achieving efficient data flow with guarantees of correctness and confidentiality;

[0089] Step 5: Complete data flow;

[0090] If the correctness verification result is 1, then the complete data flow is performed, and DP will process the entire dataset. The data is sent to the DR, who will use the same algorithm to verify its integrity. Recalculate Merkelgen ,if Once established, the DR will confirm the flow process and accept the DP's data.

[0091] The above description is merely a specific embodiment of the present invention. Any feature disclosed in this specification may be replaced by other equivalent or similar features unless otherwise specified. All disclosed features, or steps in all methods or processes, may be combined in any way except for mutually exclusive features and / or steps.

Claims

1. A method for efficient instrumentation and control data transfer based on blockchain, characterized in that, Includes the following steps: Step 1: The data provider (DP) collects data from the management and control equipment to obtain a dataset; Step 2: The data provider (DP) preprocesses the dataset using an Indexed Merkle Tree (IMT). Make a commitment, obtain the commitment value of the dataset and distribute it to the Data Requester (DR); and generate a description for the dataset to be displayed on the bulletin board; Step 3: The data requester searches for the target dataset from the data provider's bulletin board and sends a data request to the data provider; Step 4: After receiving the data request, the data provider generates a certificate and sends it to the blockchain (BC). The smart contract deployed on the blockchain verifies the certificate and returns the verification result to the data provider. Step 5: If the verification result is successful, the data provider sends the target dataset to the data requester. The data requester calculates the Merkle root of the received dataset. If it is the same as the promised value, the data requester confirms the transfer and accepts the dataset.

2. The efficient instrumentation and control data transfer method based on blockchain according to claim 1, characterized in that, In step 1, the dataset is represented as : Each data point is represented as follows: ,in, This represents the j-th attribute. This represents the data corresponding to the j-th attribute. Indicates the number of attributes. Indicates the quantity of data.

3. The efficient instrumentation and control data transfer method based on blockchain according to claim 1, characterized in that, In step 2, the Indexed Merkle Tree (IMT) includes: , This refers to the Merkle tree generation algorithm. This represents the Merkle tree existence proof algorithm. This represents the Merkle tree verification algorithm; DP calls... Algorithm generates dataset Merkelgen As a dataset The value of the commitment.

4. The efficient instrumentation and control data transfer method based on blockchain according to claim 1, characterized in that, In step 2, DP is the dataset. Generate description , This indicates the criteria that each attribute should meet. Represents the dataset A brief description; Represented in JSON format, denoted as , This represents the regular expression that the j-th attribute should satisfy.

5. The efficient instrumentation and control data transfer method based on blockchain according to claim 1, characterized in that, In step 3, the data request includes: a description of the challenge index set and the target dataset, wherein the challenge index set is represented as... ,in, Indicates the length of the challenge index set. , Indicates the first A challenge index.

6. The efficient instrumentation and control data transfer method based on blockchain according to claim 1, characterized in that, The specific process of step 4 is as follows: Step 4.1: Regular expression preprocessing; Concatenate all regular expressions in the dataset description into a single regular expression. Specifically, it is expressed as: , This represents the regular expression that the j-th attribute should satisfy. Indicates the number of attributes; Correspondingly, all related data in the dataset are concatenated into a single value. Specifically, it is expressed as: ; Step 4.2, Design of IVC function F; The IVC function F consists of two sub-functions: regularity checking and Merkle root verification, denoted as follows: and , for the meaning of the first Challenge Index Corresponding challenge data : Used to check if data meets a predefined regular expression, the regular expression Compile into an automaton, As input to the automaton, the automaton performs state checks and outputs an identifier. ,when When, it means that the data satisfies the regular expression. ; For inspection Does it exist in the dataset? Specifically, DP first calls The algorithm calculates the existence proof of Merkel. With Merkel's existence proof As input, then execute Algorithm verification Compliance; The IVC function F evaluates to 1 when both regularity checks and Merkle root verification are satisfied; otherwise, the IVC function F evaluates to 0. Step 4.3: Initialization; The Nova proof system is used to prove the correctness of the IVC function F. First, the IVC is calculated to generate the IVC proof. Then, the proof compressor Decider compresses the IVC proof into a concise zero-knowledge proof. IVC includes: , respectively, represent the IVC public parameter generation algorithm, the proof key and verification key generation algorithm, the proof generation algorithm, and the proof verification algorithm; Decider includes: , respectively, represent the algorithm for generating the Decider's public parameters, the algorithm for generating the proof key and the verification key, the proof generation algorithm, and the proof verification algorithm; First, the DP calling algorithm and Generate common parameters for IVC and Decider. and , Indicate the safety parameters; then, call the algorithm. and Generate key pairs for IVC and Decider. and , Indicates the proof key. This indicates the verification key; simultaneously, DP invokes the algorithm. Generate challenge data Merkel's existence proof ; Step 4.4: IVC proof generation; DP calling algorithm IVC proof for generating the first i challenge data , This represents the initial state for IVC calculation. Indicates the first calculation of IVC step, Indicates that IVC is calculated at the 1st The value of the step, Statement No. Merkel's existence proof for each data point Indicates the first A challenging set of data, Indicates the first The proof is generated step by step; until the final proof is generated. ; Step 4.5: IVC verification; DP calls the algorithm IVC proof for the validation challenge dataset Legality; Algorithm The result is 0 or 1, with 1 indicating IVC proof. Legal and All IVC calculations are correct; otherwise, terminate the current data transfer process. Step 4.6: Generate concise zero-knowledge proofs; DP calling algorithm IVC proof Compressed into concise zero-knowledge proofs ; Step 4.7: On-chain contract generation; The blockchain automatically generates smart contracts using the Sonobe library to verify concise zero-knowledge proofs. ; Step 4.8: On-chain proof verification; Blockchain (BC) runs smart contracts, and smart contracts call algorithms. The verification result is obtained. If the verification result is 1, it means that the proof is valid.

7. The efficient instrumentation and control data transfer method based on blockchain according to claim 1, characterized in that, In step 5, the process by which the data requester calculates the Merkle root of the received dataset is as follows: Call The algorithm recalculates the dataset Merkelgen, represented as , This represents the Merkle tree generation algorithm.

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