Industrial Internet of Things anonymous responsibility-traceable data editing method and system based on block chain

Abstract

The invention belongs to the technical field of blockchain security, and discloses an industrial Internet of Things anonymous responsibility-traceable data editing method and system based on a blockchain. The method comprises the following steps: generating a chameleon Hash trap door by a trusted mechanism, splitting the chameleon Hash trap door into shares by using threshold secret sharing, distributing the shares to verifier nodes, and initializing a dynamic accumulator; the owner encrypts the production data and formulates a modification strategy, and generates a hash value and an initial voucher by using chameleon hash and uploads the hash value and the initial voucher to a chain; the modifier initiates a request containing zero-knowledge proof, after verification is passed, the verifier node generates partial vouchers by using the trap door share, and the modifier aggregates the partial vouchers into a one-time voucher to complete editing; and the trusted mechanism decrypts the identity of the malicious modifier, moves the malicious modifier out of the dynamic accumulator and updates the revocation list. According to the method, trap door leakage is prevented through a threshold sharing mechanism, zero knowledge proof and a dynamic accumulator are combined, and effective tracking and permission revocation of malicious behaviors are realized while identity privacy of a modifier is guaranteed.

Description

A Blockchain-Based Method and System for Anonymous and Traceable Data Editing in the Industrial Internet of Things Technical Field

[0001] This invention belongs to the field of blockchain security technology, specifically relating to a blockchain-based method and system for anonymous and traceable data editing in the industrial Internet of Things. Background Technology

[0002] With the continuous development of the Industrial Internet of Things (IIoT) and the deep integration of information technology and industrial processes, data flow is evolving from local optimization at single points to global optimization. This transformation has driven the demand for cross-enterprise and cross-industry data sharing and collaboration, making it an inevitable trend. Due to its transparency and the immutability of append-only writes, blockchain has become a powerful technology for fostering trust among enterprises and ensuring data security, bringing significant advantages to cross-enterprise data sharing. However, this also harbors potential risks. For example, if incorrect data is stored on the blockchain, it can not only damage the reputation of the relevant enterprises but also cause economic losses to other enterprises that rely on this data. Therefore, industrial enterprises must have mechanisms to correct erroneous data on the blockchain. Chameleon hash functions allow modification of inputs without changing the hash output and are therefore widely used to study the editability of blockchains. Thus, introducing editable blockchains in cross-enterprise data sharing within IIoT scenarios has the potential to solve such problems.

[0003] Applying existing editable blockchain solutions to cross-enterprise data sharing in the IIoT can lead to trapdoor vulnerabilities because modifiers in editable blockchains are typically internal employees whose honesty cannot be guaranteed. In most existing technologies, modifiers have direct access to the trapdoor plaintext. Therefore, dishonest modifiers might exchange trapdoors to expand their privileges or sell them to users without editing rights or even external adversaries. This poses a serious security risk. Some solutions distribute trapdoor credentials to modifiers in a distributed manner, allowing them to modify blocks without direct access to the trapdoor plaintext. However, these solutions often lack fine-grained management of modifier identities, potentially allowing correctly uploaded data from one factory to be maliciously tampered with by modifiers from other factories. Therefore, these technologies are not suitable for the IIoT environment.

[0004] Applying existing editable blockchain solutions to cross-enterprise data sharing in the IIoT can present a difficult challenge in balancing anonymity and accountability for modifiers. Editable blockchains contain modifiers, often company employees in IIoT scenarios, whose absolute honesty cannot be guaranteed. A few modifiers may abuse their privileges to maliciously modify on-chain data. Therefore, it is essential to be able to hold malicious modifiers accountable. Simultaneously, the anonymity of honest modifiers needs to be protected to prevent attacks from adversaries. However, most existing editable blockchain solutions fail to achieve a proper balance between modifier anonymity and accountability. In most existing solutions, the modifier's identity is exposed, significantly increasing the risk of targeted attacks. Some solutions achieve modifier anonymity but fail to hold malicious modifiers accountable. Summary of the Invention

[0005] Purpose of the invention: The purpose of this invention is to address the shortcomings of existing technologies by providing a blockchain-based method and system for anonymous and traceable data editing in the industrial Internet of Things (IoT), thereby solving the problems of easy leakage of chameleon hash trapdoors, difficulty in balancing anonymity and traceability of modifiers, and low efficiency of permission revocation in existing technologies.

[0006] Technical Solution: The present invention provides a blockchain-based method for anonymous and traceable data editing in the industrial Internet of Things, comprising the following steps:

[0007] System initialization steps: The trusted institution initializes system parameters, generates a trapdoor using a chameleon hash function, splits the trapdoor into multiple shares using a threshold secret sharing mechanism and distributes them to each validator node in the validator node set, and initializes a dynamic accumulator containing the public key information of all legitimate modifiers and maintains a revocation list in the blockchain.

[0008] Certificate issuance steps: A trusted authority issues an attribute-based anonymous certificate, proof of identity, and a corresponding secret value to the legitimate modifier;

[0009] Data upload steps: The data owner encrypts the production data, formulates an attribute-based data modification strategy, uses the Chameleon hash function to generate the hash value and initial voucher of the production data, and uploads the encrypted data, hash value, initial voucher and data modification strategy to the blockchain;

[0010] On-chain error data editing steps: The modifier sends a data modification request to the set of validator nodes. The request contains a zero-knowledge proof that the modifier's attributes satisfy the data modification policy and that its identity is in the dynamic accumulator. If the verification is successful, each validator node generates a partial certificate using its trapdoor share and sends it to the modifier. The modifier aggregates the received partial certificates to generate a one-time certificate for this modification and calculates a new random factor to complete the on-chain data modification.

[0011] Data verification steps: After receiving the modified data, the new random factor, and the one-time certificate, the blockchain network node verifies whether the chameleon hash collision formula is valid. If it is valid, the on-chain record is updated.

[0012] Malicious Modifier Accountability and Revocation Steps: When malicious modification occurs, the trusted institution uses its private key to decrypt the modifier's identity information to track the real identity, removes the malicious modifier from the dynamic accumulator, and updates the revocation list; the remaining legitimate modifiers in the system that have not been revoked update their own identity verification according to the updated revocation list.

[0013] Furthermore, the present invention also provides a blockchain-based anonymous and traceable data editing system for the Industrial Internet of Things, comprising a trusted institution server, a set of validator nodes, a data owner terminal, a modifier terminal, and blockchain network nodes, for executing the above method, wherein:

[0014] Trusted authority servers are configured to issue attribute-based anonymous certificates and credentials to modifiers, track malicious modifiers, and revoke their permissions.

[0015] The data owner terminal is configured to encrypt production information and upload it to the blockchain, while also establishing corresponding editing strategies for the encrypted data;

[0016] The modifier terminal is configured to store and hold an attribute-based anonymous certificate. When the attributes possessed by the modifier satisfy the editing policy of the relevant data in the block and have not been revoked, the modifier initiates and executes the editing operation of the block data. When executing the editing operation of the block data, the editing policy includes an attribute-based access control policy.

[0017] The verifier node set is configured to accept data editing requests from modifiers and verify the legality of the modifier's request. If the verification request is legal, a one-time credential for the modifier to use is calculated collaboratively. When calculating the one-time credential collaboratively, a threshold secret sharing mechanism is adopted. Only when the number of nodes that have passed verification reaches a preset threshold value can a valid one-time credential be aggregated and generated. The one-time credential does not expose the system's trapdoor.

[0018] A blockchain network is configured to store the encrypted production information and editing strategies, and to record the editing results of the data.

[0019] Beneficial Effects: Compared with existing technologies, the advantages of this invention are as follows: This invention employs a threshold-based secret sharing mechanism to prevent trapdoor leakage. The trapdoor of the Chameleon Hash is split and stored in distributed validator nodes after initialization. When editing data, the modifier can only generate a "one-time credential" for a specific editing operation by aggregating the partial credentials returned by the validator nodes. The modifier cannot deduce the trapdoor from this one-time credential. Even if the modifier's device is compromised or the modifier is malicious, they cannot obtain the system-level master trapdoor, thus preventing illegal trapdoor exchange and privilege abuse.

[0020] This invention combines zero-knowledge proofs and dynamic accumulator techniques. During normal modification, the modifier uses zero-knowledge proofs to demonstrate to the verifier node that their properties are legitimate and have not been revoked, without revealing their identity, thus achieving strong anonymity. Simultaneously, the trusted authority retains tracking permissions and can decrypt the malicious modifier's encrypted identity, fulfilling the regulatory requirement of "anonymity at the front end and real-name verification at the back end."

[0021] By introducing attribute-based access control policies, data owners can formulate specific modification policies for each piece of data, enabling the present invention to adapt to the complex organizational structures and access control requirements in the Industrial Internet of Things.

[0022] A dynamic accumulator is used to maintain the list of legitimate members. When a malicious user needs to be revoked, only the user's public key needs to be removed from the accumulator and the public parameter updated, without needing to update the private keys of all users. Other honest users in the system only need to listen to the revocation list and update their identity credentials locally to remain valid, greatly reducing the system's communication and computational overhead.

[0023] This invention employs an optimized bilinear pairing mapping and aggregation algorithm. It avoids cumbersome repetitive calculations during the generation of partial credentials by the validator node and the aggregation of one-time credentials by the modifier. Experimental results show that, under the same security strength, the computational efficiency of this invention is superior to existing similar solutions, making it more suitable for resource-constrained IIoT environments. Attached Figure Description

[0024] Figure 1 is a system model diagram of the blockchain-based anonymous and traceable data editing method for industrial IoT provided in an embodiment of the present invention, illustrating the interaction between trusted institutions, data owners, modifiers, a set of verifier nodes, and the blockchain network.

[0025] Figure 2 is a schematic diagram comparing the overhead of the data upload stage in the embodiment of the present invention with that of the prior art;

[0026] Figure 3 is a schematic diagram comparing the overhead of the on-chain error data editing stage in the embodiment of the present invention with that of the prior art;

[0027] Figure 4 is a schematic diagram comparing the overhead of the data verification stage in the embodiment of the present invention with that of the prior art;

[0028] Figure 5 is a schematic diagram comparing the overhead of generating a one-time trapdoor (credential) in an embodiment of the present invention with that of the prior art, with the set of validator nodes set as the independent variable;

[0029] Figure 6 is a schematic diagram comparing the overhead of generating a one-time trapdoor (credential) in an embodiment of the present invention with that of the prior art, with the independent variable set as a threshold value. Detailed Implementation

[0030] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings, but the scope of protection of the present invention is not limited to the embodiments described.

[0031] Example 1: To address the security issues inherent in existing editable blockchain solutions applied to industrial IoT data sharing scenarios, this invention proposes a blockchain-based anonymous and traceable data editing method for industrial IoT. Specifically, to solve the chameleon hash trapdoor leakage problem, this invention first combines editable signatures and threshold secret sharing. A trusted institution generates a trapdoor share by sharing the threshold secret with a set of validator nodes. The modifier sends a modification request to the set of validator nodes. If the request is valid (i.e., the modifier meets the on-chain data modification policy and the modifier has not been revoked), each node in the validator node set generates a partial certificate for the modifier using the trapdoor share. The modifier aggregates these partial certificates into a one-time certificate to complete the on-chain data modification. Throughout this process, the trapdoor plaintext is not exposed and cannot be derived from the one-time certificate. Simultaneously, to achieve both anonymity for the modifier and traceability for malicious modifiers, this invention combines zero-knowledge proofs and a dynamic accumulator. In the entire process, only a trusted institution can decipher the modifier's identity information and remove them from the dynamic accumulator, thus revoking the malicious modifier's claim.

[0032] To facilitate understanding of the technical solution in this embodiment, the meanings of the relevant variables are explained first, as detailed in Table 1.

[0033] Table 1

[0034]

[0035] As shown in Figure 1, this embodiment provides a blockchain-based method for anonymous and traceable data editing in the Industrial Internet of Things (IIoT), involving five main entities: Trusted Authority (TA), Data Owner, Modifier, Verifier Nodes (VNs), and the blockchain network.

[0036] In this system, a trusted institution issues attribute-based anonymous certificates and identity verification to modifiers, tracks malicious modifiers, and revokes their permissions; modifiers hold attribute-based anonymous certificates. When the attributes possessed by a modifier satisfy the editing policy of the relevant data in the block, and the certificate has not been revoked, the modifier can execute the block data editing operation; in the proposed scheme, the modifier refers to factory management personnel, including department managers and general managers, who are responsible for encrypting production information and uploading it to the blockchain, while also formulating corresponding editing policies for the encrypted data; the verifier node set is responsible for accepting the data editing requests from modifiers, verifying the legality of the modifier's request, and if legal, collaboratively calculating a one-time credential for the modifier to use.

[0037] This method specifically includes the following steps:

[0038] Step (1): System Initialization

[0039] Step (1.1): The Trusted Authority (TA) first selects a security parameter. The bilinear mapping algorithm was selected. Randomly generate generators .

[0040] Step (1.2): The trusted organization selects random elements. ,calculate:

[0041]

[0042] ,

[0043] in, It will serve as the system's master private key. , This represents the maximum number of attributes a modifier can possess. It will serve as the system's master public key. The trusted institution will subsequently select two random oracle functions. .

[0044] Step (1.3): The trusted mechanism calculates the dynamic accumulator. ,in It is the set of indices of all modifiers in the system, where any modifier in the set is set to... , A trusted organization generates a random secret value for it. The trusted organization needs to maintain a record of the secret value corresponding to each modifier. And guarantee that any two modifiers They are different.

[0045] Step (1.4): The trusted institution maintains a revocation list RL in the blockchain. The RL stores the identity information of the malicious modifiers whose revocations are made. It is initially empty.

[0046] Step (1.5): Assume the initial set of validator nodes contains... Let the nodes inside the set be . Trusted institutions select random numbers And generate a trapdoor for the chameleon hash. The corresponding public key is To prevent trapdoor leaks, trusted institutions utilize threshold secret sharing mechanisms (Shamir's Secret Sharing) to handle... :

[0047] Construct a polynomial function ,in For constant terms, This is the threshold value.

[0048] Trusted institutions calculate share and through a secure channel The first one sent to the set of validator nodes One validator node ,public .

[0049] After distribution is complete, the trusted organization removes the entire trapdoor locally. .

[0050] Step 2: Certificate Issuance

[0051] Trusted organizations issue attribute certificates to legitimate modifiers within the system. Identity verification and secret value The modifier uses these credentials to prove their legitimacy in subsequent steps.

[0052] Step (2.1), let the modifier be... The corresponding public and private keys are The modifier's public and private keys The modifier applied to a trusted organization in advance.

[0053] The modifier selects a random number. Calculate zero-knowledge proofs about one's own private key. ,in Make the random challenge value Calculate the response value corresponding to the random challenge value. .

[0054] Step (2.2): The modifier sends a certificate request to a trusted authority.

[0055] ,in These are the attributes that the modifier needs to apply for;

[0056] Step (2.3): The trusted organization calculates the random challenge value. ,verify If true, select a random number. Computational property certificate ,in , Return attribute certificate To the person who made the changes;

[0057] Step (2.4): The trusted institution sends the corresponding identity verification to the modifier. and secret value ;

[0058] Step (2.5): The modifier successfully obtains the certificate. .

[0059] Step (3): Data Upload

[0060] Factory data owners encrypt production data And upload it to the blockchain to generate a corresponding modification strategy. Generate using the Chameleon hash function The corresponding parameters include the hash value. random factor and initial credentials Perform the following operations:

[0061] Step (3.1): The data owner encrypts the production data to obtain ciphertext. .

[0062] Step (3.2): Develop a plan for this data. Modification strategy (For example, attribute-based access control policies) use a chameleon hash function to generate parameters. Specifically, a random number is selected. Calculate auxiliary values .

[0063] Calculate the chameleon hash value: .

[0064] Calculate the random factor: .

[0065] Calculate the initial voucher: .

[0066] Step (3.3), will The hash value is then uploaded to the blockchain network.

[0067] Step 4: Editing On-Chain Error Data

[0068] When an on-chain data error is detected, the modifier... The corresponding public and private keys are The modifier sends the corresponding parameters to the set of validator nodes, including the error data that needs to be modified. The corresponding correct data Encrypted identity information ( Derivative Attribute Certificate With identity documents If the request is valid, each validator node in the validator node set will generate a corresponding partial credential for it. The modifier will then aggregate the received partial credentials into a one-time credential. and calculate data and Corresponding Chameleon Hash Random Factor This is to complete the on-chain data modification operation; the details are as follows:

[0069] Step (4.1): The modifier needs to derive different partial attribute certificates according to different access policies. Here, the attributes that the modifier needs to display are: ,in This is the set of indices corresponding to the selected portion of the modifier's attribute sequence that needs to be displayed, and it is set... ;

[0070] Step (4.2): The modifier selects a random number. Calculate partial attribute certificates Encrypt identity information Updated random factor and identity documents Corresponding commitment The calculation process is as follows:

[0071] , , , ;

[0072] , , ;

[0073] , ,

[0074] in, , It is the encrypted, correct production data;

[0075] Step (4.3): The modifier selects a random number. Calculate variables Corresponding zero-knowledge proof information , , , , Random challenge value The corresponding value is , , , ;

[0076] Step (4.1.4), the modifier will Send to the set of validator nodes ;

[0077] Step (4.2), each node in the validator node set The request from the modifier needs to be verified. The verification process is as follows:

[0078] Step (4.2.1) Calculate random challenge value , ;

[0079] Step (4.2.2): Verify whether the following equation holds true, and determine... Does it meet the modification strategy? :

[0080] ,

[0081] ,

[0082] ,

[0083] ,

[0084] ;

[0085] Step (4.2.3): If all the above conditions are met, calculate the new random factor of the Chameleon Hash. and to the validator node set Initiate a request,

[0086] ,

[0087] in It is the data originally stored in the blockchain. It is data that has been edited;

[0088] Each node in the validator node set Using its holdings of trapdoor shares and parameters provided by the modifier Calculate part of the voucher Returned to the modifier, the validator node set is stored. .

[0089] Step (4.3), the modifier collects at least A correct partial voucher Then, these partial vouchers are aggregated using Lagrange interpolation to generate a one-time voucher. The aggregation formula satisfies:

[0090]

[0091] in, For Lagrange coefficients, This is the set of indexes for the participating nodes. These are parameters related to this modification request.

[0092] At the same time, the modifier calculates the new chameleon hash random factor. and broadcast To the blockchain network.

[0093] In this process, the modifier only obtains the calculation result. Due to the difficulty of the discrete logarithm problem, it is impossible to solve it from... Separate from .

[0094] Step 5: Data Validation

[0095] The modifier will Broadcast to the blockchain. Blockchain nodes verify whether the following conditions are met:

[0096] Bilinear pairing verification: verification This ensures the legality of the one-time voucher;

[0097] Hash Collision Verification: Verification and Whether it is valid, among which ;

[0098] If the verification passes, the blockchain node will record the data locally. Replace with .

[0099] Step 6: Holding Malicious Modifiers Accountable

[0100] If a modification is found to be malicious, a trusted organization will intervene to hold the responsible party accountable.

[0101] Step (6.1): The trusted institution bases its decisions on the error data on the chain. Obtain the encrypted identity information of the malicious modifier from the set of validator nodes. and .

[0102] Step (6.2): ​​The trusted institution uses the system's master private key to calculate the malicious modifier's public key. .

[0103] Step 7: Malicious modifier revoks

[0104] Step (7.1): The trusted institution will transfer the malicious modifier's public key. From dynamic accumulator Remove from the middle and calculate the new accumulator value. .

[0105] Step (7.2), the trusted institution will revoke the information ( Add to the public Revocation List (RL), where It is a trusted institution The generated random secret value will be deleted by the trusted organization after the above steps are completed. corresponding and .

[0106] Step (7.3): Monitor other legitimate modifiers in the system that have not been revoked. And the update of RL. When RL is updated, the legitimate modifier uses the old identity credentials stored locally. Based on the system parameters and the revocation value in the RL, the update algorithm is executed to calculate the new identity verification. To ensure that it can continue to pass the verification of the dynamic accumulator, where and It is the public key of a non-malicious modifier and the random secret value generated for it by a trusted institution.

[0107] To address the trapdoor leakage problem, a threshold secret sharing-based anti-trapdoor leakage algorithm is employed, and editable signatures are introduced to achieve fine-grained management of the modifier's identity. Legitimate modifiers receive a one-time credential to exercise editing privileges, and the plaintext of the trapdoor cannot be deduced from the credential.

[0108] To address the issues of anonymity and accountability, an anonymous and accountable protocol combining zero-knowledge proofs, editable signatures, and dynamic accumulators was designed. This protocol guarantees the anonymity of the modifier's identity and the non-linkability of editing operations, while also supporting efficient tracking and reversal of malicious modifiers.

[0109] Example 2: System Example

[0110] This embodiment provides a blockchain-based anonymous and traceable data editing system for the Industrial Internet of Things (IIoT). The system's hardware architecture includes:

[0111] Trusted authority servers are configured to issue attribute-based anonymous certificates and credentials to modifiers, track malicious modifiers, and revoke their permissions.

[0112] The data owner terminal is configured to encrypt production information and upload it to the blockchain, while also establishing corresponding editing strategies for the encrypted data;

[0113] The modifier terminal is configured to store and hold an attribute-based anonymous certificate. When the attributes possessed by the modifier meet the editing policy of the relevant data in the block and have not been revoked, the modifier initiates and executes the editing operation of the block data. When executing the editing operation of the block data, the editing policy includes an attribute-based access control policy. The modifier corresponding to the modifier terminal includes factory management personnel, and the attributes include department manager attributes or general manager attributes.

[0114] The verifier node set is configured to accept data editing requests from modifiers and verify the legality of the modifier's request. If the verification request is legal, a one-time credential for the modifier to use is calculated collaboratively. When calculating the one-time credential collaboratively, a threshold secret sharing mechanism is adopted. Only when the number of nodes that have passed verification reaches a preset threshold value can a valid one-time credential be aggregated and generated. The one-time credential does not expose the system's trapdoors.

[0115] The blockchain network is configured to store encrypted production information and editing strategies, and record the results of data editing.

[0116] Example 3: This example uses the Miracl Core cryptographic library to obtain the execution time of various cryptographic operations on a PC (Intel Core i7-10700 CPU @ 2.9GHz, 16GB RAM, Ubuntu 20.04.6 operating system). Simultaneously, the proposed scheme employs a BLS-12-381 curve, which provides 128-bit security, to implement the asymmetric bilinear mapping function.

[0117] Figures 2 to 4 show the computational overhead of the proposed invention in steps (3), (4), and (5), and compare it with the papers by Dealer et al. ("Fine-grained and controlled rewriting in blockchains: Chameleon-hashing gone attribute-based."), Xu et al. ("Accountable and fine-grained controlled rewriting in blockchains."), and Xu et al. ("Redactable blockchain-based secure and accountable data management."). In the experiments, the length of the access policy / attribute was set to 5 to 30, with a step size of 5, and only AND gates were used. Furthermore, to ensure fairness in the comparison of computational costs, a threshold value was set. Set to the number of attributes or the length of the access strategy, and set the total number of nodes in the validator node set to... The comparative results show that the computational cost of the method of the present invention is better than that of existing methods, because existing methods require executing more group operations. Add operations to the points on the top.

[0118] Figures 5 and 6 show the computational cost of generating a one-time trapdoor using the proposed invention and compare it with existing solutions, with the independent variable set as the total number of nodes in the validator node set. With threshold value .

[0119] The results clearly demonstrate that the computational overhead of the method of the present invention has a significant advantage over existing methods.

[0120] As described above, although the invention has been shown and described with reference to specific preferred embodiments, it should not be construed as limiting the invention itself. Various changes in form and detail may be made without departing from the spirit and scope of the invention as defined in the appended claims.

Claims

1. A blockchain-based method for anonymous and traceable data editing in the Industrial Internet of Things (IIoT), characterized in that, Includes the following steps: System initialization steps: The trusted institution initializes system parameters, generates a trapdoor using a chameleon hash function, splits the trapdoor into multiple shares using a threshold secret sharing mechanism and distributes them to each validator node in the validator node set, and initializes a dynamic accumulator containing the public key information of all legitimate modifiers and maintains a revocation list in the blockchain. Certificate issuance steps: A trusted authority issues an attribute-based anonymous certificate, proof of identity, and a corresponding secret value to the legitimate modifier; Data Upload Steps: The data owner encrypts the production data, formulates an attribute-based data modification strategy, generates a hash value and initial certificate for the production data using the Chameleon Hash Function, and uploads the encrypted data, hash value, initial certificate, and data modification strategy to the blockchain. On-Chain Error Data Editing Steps: The modifier sends a data modification request to the set of validator nodes. This request includes a zero-knowledge proof that the modifier's attributes satisfy the data modification strategy and that their identity is in the dynamic accumulator. If the verification passes, each validator node uses its trapdoor share to generate a partial certificate and sends it to the modifier. The modifier aggregates the received partial certificates to generate a one-time certificate for this modification and calculates a new random factor to complete the on-chain data modification. Data Verification Steps: After receiving the modified data, the new random factor, and the one-time certificate, the blockchain network nodes verify whether the Chameleon Hash Collision Formula holds. If it does, the on-chain record is updated. Malicious Modifier Accountability and Revocation Steps: When malicious modification occurs, a trusted institution uses its private key to decrypt the modifier's identity information to track their true identity, removes the malicious modifier from the dynamic accumulator, and updates the revocation list. The remaining legitimate modifiers in the system who have not had their modifications revoked will update their identity verification based on the updated revocation list.

2. The blockchain-based anonymous and traceable data editing method for the Industrial Internet of Things as described in claim 1, characterized in that, The system initialization steps include: trusted institutions selecting security parameters. and bilinear mapping algorithm Randomly select groups Generators in ,group Generators in Master public key of trusted organization computing system Parameters: ,in For random elements, The maximum number of attributes, and Stored as the master private key, and two random oracle hash functions are selected simultaneously. and Trusted mechanism initializes dynamic accumulator ,in This is the set of indices for all modifiers in the system. For the modifier's public key, A random secret value generated by a trusted institution for the modifier, while an empty revocation list is initialized in the blockchain. A trapdoor where a trusted institution randomly generates chameleon hashes. Calculate the corresponding public key The trapdoor is handled using a threshold secret sharing mechanism: a polynomial function is constructed. ,Will As a constant term, the share is calculated. And send it to the corresponding node in the verifier node set via a secure channel. Then delete the entire trapdoor. 。 3. The blockchain-based anonymous and traceable data editing method for the Industrial Internet of Things as described in claim 2, characterized in that, The certificate issuance steps include: the modifier selecting a random number. Calculate information about one's own private key Zero-knowledge proof and send a set of attributes and Certificate application request; trusted authority calculates local challenge value And verify zero-knowledge proofs If the verification is successful, the trusted authority will generate an attribute certificate for the modifier. and identity documents and attribute certificate Identity verification and secret value Send to the modifier, including proof of identity. Based on dynamic accumulator Generated with the modifier's private key, it is used to prove that the modifier is a legitimate member of the system and has not been revoked.

4. The blockchain-based anonymous and traceable data editing method for the Industrial Internet of Things as described in claim 2, characterized in that, The data upload step includes: the data owner defining an attribute-based access control structure as a data modification strategy. Data owners in the group Select generator And select a random number. Combined with production data Calculate auxiliary values Calculate the chameleon hash value ; Calculate random factors ; Calculate the initial voucher encrypt the data Random factors Initial voucher Modify strategy and hash value Uploaded to the blockchain network.

5. The blockchain-based anonymous and traceable data editing method for the Industrial Internet of Things as described in claim 1, characterized in that, In the on-chain error data editing step, when the modifier initiates a request, it performs an attribute privacy protection operation: the modifier follows the access policy. Derive a partial attribute certificate from its complete attribute certificate and select a random number. Regarding the aforementioned attribute certificates and identity verification The encrypted identity information is randomized and obfuscated to generate a zero-knowledge proof commitment value, enabling verifier nodes to verify the permissions of the modifier without knowing the modifier's specific attributes and plaintext identity.

6. The blockchain-based anonymous and traceable data editing method for the Industrial Internet of Things according to claim 5, characterized in that, In the on-chain error data editing step, the one-time credential generation process includes: the modifier derives a partial attribute certificate based on the access policy and combines it with identity verification. Generating zero-knowledge proofs Calculate the new random factor of the chameleon hash. and to the set of validator nodes Initiate a request, ,in It is the data originally stored in the blockchain. It is data that has been edited; each node in the validator node set. Using its holdings of trapdoor shares and parameters provided by the modifier Calculate part of the voucher The modifier collected at least A correct partial voucher is aggregated using the Lagrange interpolation formula to generate a one-time voucher. ： ,in, For the validator index set, is the Lagrange multiplier.

7. The blockchain-based anonymous and traceable data editing method for the Industrial Internet of Things according to claim 6, characterized in that, The data verification step includes: after receiving the modified data, the new random factor, and the one-time certificate, the blockchain network node performs the following verification: verifying the bilinear equivalence. Whether it is valid, among which As a new random factor, This is a one-time credential; verify the hash collision formula. Whether it is true or not, among which, The hash value of the original data stored on the chain. ， The modified data is used; if the verification is successful, the modification is confirmed as legitimate and the modified data is updated in the blockchain record, replacing the original erroneous data.

8. The blockchain-based anonymous and traceable data editing method for the Industrial Internet of Things according to claim 1, characterized in that, Accountability for malicious modifiers includes: trusted institutions based on erroneous data on the blockchain. Obtain the encrypted identity information of the malicious modifier from the set of validator nodes. and ; Utilizing encrypted identity information Calculate the public key of the malicious modifier ,in, This is the system private key parameter.

9. The blockchain-based anonymous and traceable data editing method for the Industrial Internet of Things according to claim 1, characterized in that, In the revocation process for malicious modifiers, the update process for identity verification includes: the trusted institution removes the malicious modifier's public key information from the dynamic accumulator and adds the revocation value generated based on that public key to the public revocation list (RL); the remaining legitimate modifiers in the system that have not been revoked monitor the updates to the revocation list; when an update to the revocation list is detected, the legitimate modifier uses their currently held identity verification, the system's public parameters, and the newly added revocation value in the revocation list to calculate a new identity verification by executing an update algorithm, so that the updated identity verification can continue to pass the membership verification of the dynamic accumulator.

10. A blockchain-based anonymous and traceable data editing system for the Industrial Internet of Things, characterized in that, include: The trusted authority server is configured to initialize system parameters, distribute chameleon hash trapdoor shares using a threshold mechanism, issue certificates to modifiers, maintain a dynamic accumulator and revocation list, and perform tracking and revocation of malicious modifiers. The data owner terminal is configured to encrypt production information and upload it to the blockchain, while also establishing corresponding editing strategies for the encrypted data; The modifier terminal is configured to store and hold an attribute-based anonymous certificate. When the attributes possessed by the modifier satisfy the editing policy of the relevant data in the block and have not been revoked, the modifier initiates and executes the editing operation of the block data. When executing the editing operation of the block data, the editing policy includes an attribute-based access control policy. A set of validator nodes is configured to accept data editing requests from modifiers, verify the legality of the requests, and if the requests are valid, collaboratively calculate a one-time credential for the modifier to use. A threshold secret sharing mechanism is used in the collaborative calculation of the one-time credential; a valid one-time credential is only generated when the number of nodes that have passed verification reaches a preset threshold, and the one-time credential does not expose any trapdoors in the system. A blockchain network is configured to store the encrypted production information and editing strategies, and record the data editing results.

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