Energy transaction supervision method and system

Abstract

The application belongs to the technical field of block chain, and particularly relates to an energy transaction supervision method and system, which comprises the following steps: S1. initialization and supervision power distribution; S2. terminal registration and transient signature based on PUF; S3. privacy cleaning and aggregation of an edge gateway; S4. block consensus chaining based on chameleon hash; S5. compliance correction execution under multi-party consensus; the application has the advantages that a trusted supervision architecture of 'end-edge-cloud' three-layer cooperation is provided. The most key technical concept is to build a full-process trust closed loop from the physical world to the digital world and to the compliance supervision level.

Description

Technical Field

[0001] This application pertains to blockchain technology, specifically relating to an energy trading supervision method and system. Background Technology

[0002] With the explosive growth of distributed energy resources (DERs), building decentralized peer-to-peer (P2P) energy trading platforms using blockchain technology has become a mainstream trend in the Industrial Internet of Things (IIoT) field. Blockchain, with its transparent and immutable characteristics, solves the problem of trust among multiple parties. However, in actual industrial applications, the existing technological system is caught in an irreconcilable "trust-regulation-privacy" triangle dilemma.

[0003] Despite existing technologies exploring blockchain data correction and privacy protection algorithms, two fundamental architectural flaws remain in practical applications for large-scale industrial Internet of Things (IIoT) energy trading.

[0004] First, existing technologies generally lack source-based trusted anchoring based on physical hardware, leading to a severe "oracle" trust crisis for regulatory systems. Whether it's a reputation-based correction scheme or a state machine-based negotiation scheme, their security logic rests on the software-layer assumption that "private key equals identity," ignoring the risk of easily physical extraction of private keys statically stored in general-purpose memory (Flash / EEPROM) in industrial terminals. Due to the lack of underlying anchoring based on hardware physical characteristics (such as PUF), existing technologies cannot distinguish between "real device data" and "fake data simulated by hackers using stolen private keys." This deficiency of "only correcting data logic, without verifying the source's authenticity" means that the entire regulatory correction mechanism may be based on false facts, failing to defend against source-based forgery attacks.

[0005] Secondly, the existing algorithm architecture is severely mismatched with the "weak terminals, strong regulation" reality of industrial scenarios. On the one hand, existing solutions tend to use heavy privacy algorithms such as group signatures, whose high computational complexity far exceeds the carrying capacity of massive low-cost industrial microcontrollers (MCUs). Forced deployment would lead to network congestion or even paralysis, making it impractical in engineering. On the other hand, existing correction mechanisms mostly rely on soft constraints such as "multi-party consultation" or "reputation accumulation," lacking the enforceability and timeliness required for administrative supervision. In highly adversarial scenarios such as malicious electricity theft, attackers' refusal to cooperate leads to correction failure. Existing technologies lack an efficient mechanism that can represent public authority and execute "mandatory in-situ error correction" under multi-party consensus, failing to meet the rigid requirements of "legal regulation" in the energy industry.

[0006] In summary, existing technologies lack a systematic solution that can simultaneously address trusted anchoring of source hardware, lightweight privacy protection, and support for compliance and regulatory corrections. Summary of the Invention

[0007] This invention addresses the challenges of source fraud, privacy breaches, and regulatory corrections in industrial IoT energy trading by proposing a three-layer collaborative trusted regulatory architecture encompassing the "device-edge-cloud." Its key technical concept lies in constructing a closed-loop trust system that spans the entire process from the physical world to the digital world and then to compliance and regulation. The technical solution is as follows:

[0008] An energy trading regulatory approach includes the following steps: S1. Initialization and Distribution of Regulatory Power; S2. PUF-based terminal registration and transient signature; S3. Privacy scrubbing and aggregation at the edge gateway; S4. Block consensus based on chameleon hashing on-chain; S5. Compliance amendments implemented based on multi-party consensus.

[0009] Preferably, S1. Initialization and distribution of regulatory powers, as follows: S11. Establish the cryptographic parameter system for Chameleon Hash and generate the master public key for Chameleon Hash. and the initial trapdoor private key ; S12. Initiate the trapdoor crushing process: using Shamir Threshold secret sharing algorithm, Divided into A separate private key fragment The trapdoor was then distributed via a secure channel to members of a regulatory committee comprised of various stakeholders. Once distributed, the original, intact trapdoor was immediately destroyed. This ensures that no single entity has the ability to modify the blockchain while the system is running.

[0010] Preferably, in step S2, during the device network access phase, the registration center sends an excitation signal to the PUF module, extracts its physical response and calculates auxiliary error correction data, and stores the "device ID-auxiliary data" mapping relationship in the edge gateway. During the transaction phase, when the smart meter collects energy data... At that time, the PUF module powers on and reads the current SRAM physical noise value. Combined with locally cached auxiliary data, it uses a fuzz extractor to recover the unique physical fingerprint in real time and derive the transient private key. The device uses this private key to access data. Digital signature generation After signing, Immediately erase from volatile memory to ensure the device cannot be physically cloned or the private key extracted.

[0011] Preferably, in step S3, the edge gateway receives signed data packets sent by multiple smart meters within its jurisdiction. The gateway uses the PUF public key stored on the blockchain to verify the legitimacy of all signatures, eliminating fake device requests that cannot pass physical fingerprint verification; the gateway initiates a privacy cleaning process: using the BLS non-interactive aggregate signature algorithm, it aggregates signatures within the same time window. A single valid signature is compressed into a very short aggregate signature. and the corresponding The plaintext transactions are homomorphically aggregated or obfuscated to generate de-identified "regional aggregate blocks". .

[0012] Preferably, in step S4, when the edge gateway aggregates blocks... When broadcasting to the blockchain network, the ledger node randomly selects an initial random number. Using the node's public key Calculate the chameleon hash digest: ; After successful verification, the tuple will be... Write a new block and link it to the main chain.

[0013] Preferably, in step S5, when the regulatory agency detects a logical anomaly in a certain aggregated block, it initiates a "correction proposal" to the on-chain smart contract, the content of which includes the original block hash. Corrected data The oversight committee members vote on the proposal on-chain, and once the number of votes in favor reaches a threshold... Each node does not leak its own fragments. Under the premise of ensuring security, initiate secure multi-party computation to jointly compute a new random number. , so that: ; New trading pairs broadcast online After all nodes in the network verify the hash match, the local ledger content is updated without forking or rolling back, thus completing the compliance correction.

[0014] Preferably, step S5 includes: Anomaly Detection and Proposal Initiation: When the regulatory initiator detects a logical anomaly in the aggregated block, it sends a correction proposal to the on-chain smart contract. This proposal includes the chameleon hash value of the original block. and the corrected aggregated data content ; Threshold voting and authorization verification: Step 1: After receiving the proposal, the smart contract sends a voting request instruction to other regulatory nodes of the regulatory committee. Each regulatory node verifies the proposal and then casts a vote of approval or disapproval to the smart contract. Step 2: The smart contract summarizes the voting results and strictly executes the threshold judgment logic: verifying whether the number of affirmative votes is greater than or equal to the preset threshold. If the conditions are met, the subsequent joint computation process will be triggered. Secure multi-party computation and hash collisions: Step 1: The smart contract sends a command to the regulatory node that voted in favor to initiate joint computation; Step 2: In a secure multi-party computation environment, the participating regulatory nodes utilize their respective trapdoor fragments. Joint computation is performed, during which each node does not reveal the true fragment information to the others, and together they calculate a new random number. ; Step 3: Each node returns the calculated sharding result to the smart contract; Ledger Update: Step 1: The smart contract combines and shards to obtain a complete new random number. After confirming the new trading pair Its hash value is still Then, the system returns a status indicating successful correction to the regulatory initiator. Step 2: The smart contract broadcasts the new trading pair to the entire network. The block.

[0015] An energy trading regulatory system, comprising a terminal side, an edge side, and a cloud side; On the terminal side: Based on the source anchoring logic of transient physical fingerprints, a PUF module is introduced into the terminal. It utilizes the randomness of the microscopic physical features at the moment the chip is powered on to build an authentication mechanism of "hardware as identity". The physical fingerprint is recovered in real time and a transient private key is derived for signing only within the millisecond window when the transaction occurs. The fingerprint is erased immediately after signing is completed. Edge side: An edge computing gateway is introduced between the terminal and the blockchain as a "privacy cleaning pool". Using BLS aggregate signature technology, the gateway compresses the independent signatures of hundreds or thousands of users in the area into a unique aggregate signature, and homomorphically summarizes or obfuscates the specific transaction plaintext to generate regional aggregate blocks. On the cloud side: a correctable consensus ledger is constructed based on the compliance correction logic of threshold chameleon hash.

[0016] Preferably, the "trapdoor" property of the chameleon hash function is utilized to allow the replacement of block content without changing the hash value: the trapdoor power is "crushed" by using Shamir threshold secret sharing technology and distributed to a committee composed of multiple regulatory agencies. Only with the consensus of multiple parties can the hash collision parameters be calculated and illegal transactions or erroneous data on the chain be corrected in place without leaving a trace.

[0017] Compared with the prior art, the beneficial effects of this application are as follows:

[0018] 1. This invention achieves "physical-level" source anti-counterfeiting, fundamentally solving the trust problem of blockchain "oracles." Existing technologies mostly use static private key authentication, which cannot defend against private key leaks or device cloning attacks. This invention introduces SRAM PUF technology, directly anchoring digital identity to the microscopic physical characteristics generated during chip manufacturing. Because the private key only exists transiently within a millisecond window of the signature and is destroyed after use (RAM cleared), any attacker, even with physical intrusion into the device, cannot extract the private key, nor can they forge transaction data verified by physical fingerprints using a software simulator. This ensures that every energy transaction on the blockchain has a strong binding relationship between the "hardware entity" and the "digital behavior," eliminating the risk of "fake data on the chain" common in the Industrial Internet of Things.

[0019] 2. A compliance correction mechanism that is "non-forking and non-breakable" has been constructed, breaking through the bottleneck of blockchain implementation in highly regulated scenarios. Addressing the regulatory rigidity caused by the "absolute immutability" of traditional blockchains, this invention utilizes threshold chameleon hash technology to empower regulatory agencies to perform "in-situ correction" of illegal or erroneous data while preserving the integrity of the blockchain hash chain. Unlike existing technologies that rely on soft corrections based on "negotiation" or "reputation," this solution disperses "trapdoor" power through threshold secret sharing. This prevents the abuse of single power while ensuring that, with multi-party consensus, administratively enforceable corrections (such as reversals and marking) can be executed against malicious transactions, perfectly meeting the energy industry's rigid requirements for audit compliance and penetrating supervision.

[0020] 3. This invention decouples privacy protection from terminal computing power, significantly reducing hardware costs for large-scale industrial deployment. Addressing the pain points of existing privacy protection schemes (such as group signatures and zero-knowledge proofs) being computationally intensive and difficult to run on low-cost electricity meters, this invention innovatively adopts an "edge-end" collaborative architecture. By utilizing edge gateways to perform BLS aggregated signatures and data cleansing, the complex privacy computing load is removed from resource-constrained terminals. This not only achieves collective protection of user electricity privacy and severs the explicit association between data and identity, but also enables the system to be compatible with inexpensive, low-power IoT terminals, significantly improving the system's transaction throughput (TPS) and engineering feasibility. Attached Figure Description

[0021] Figure 1 This is the overall framework diagram; Figure 2 Here is the overall method flowchart; Figure 3 Logic diagram for PUF key generation and signature; Figure 4 Corrected timing diagram for threshold chameleon hash. Detailed Implementation

[0022] The technical solutions of the embodiments 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, and not all embodiments.

[0023] This invention addresses the challenges of source fraud, privacy breaches, and regulatory corrections in industrial IoT energy trading by proposing a three-layer collaborative trusted regulatory architecture encompassing the "device-edge-cloud." Its key technical concept lies in constructing a closed-loop trust system spanning the entire process from the physical world to the digital world and then to compliance and regulation, primarily composed of the following three core logical modules:

[0024] An energy trading regulatory system, comprising a terminal side, an edge side, and a cloud side; On the terminal side: Unlike existing technologies that statically store private keys in Flash memory, this solution introduces PUF (Physically Unclonable Function) technology at the terminal. Utilizing the randomness of the microscopic physical characteristics at the moment of chip power-on, a "hardware as identity" authentication mechanism is constructed. The system only needs to recover the physical fingerprint in real time within a millisecond window after a transaction occurs and derive a transient private key for signing; after signing, it is immediately erased. This concept fundamentally removes the physical carrier from which the private key can be stolen, ensuring that every piece of on-chain data originates from a real physical device, thus solving the trust root problem of "separation of virtual and physical" (i.e., the root of trust is not directly related to the previous sentence).

[0025] Edge Side: Privacy Cleansing Logic Based on Non-Interactive Aggregation To achieve efficient privacy protection in resource-constrained IIoT environments, this solution introduces an edge computing gateway as a "privacy cleansing pool" between the terminal and the blockchain. Utilizing BLS aggregated signature technology, the gateway compresses the independent signatures of hundreds or thousands of users within its jurisdiction into a unique aggregated signature, and homomorphically summarizes or obfuscates the specific plaintext transactions to generate regional-level aggregated blocks. This concept removes the complex privacy computing load from the weak terminal while physically severing the explicit correlation between on-chain public data and individual users' daily routines.

[0026] On the cloud side: Addressing the conflict between the "immutability" and "regulatory compliance" of blockchain, this solution constructs a correctable consensus ledger. Utilizing the "trapdoor" property of the chameleon hash function, it allows for the replacement of block content without altering the hash value. Crucially, this solution uses Shamir threshold secret sharing technology to "crush" the trapdoor power, distributing it to a committee composed of multiple regulatory bodies. Only with multi-party consensus can the system calculate hash collision parameters and perform in-situ, seamless correction of illegal transactions or erroneous data on the chain. This concept retains the blockchain's anti-unilateral tampering characteristics while endowing the system with "error correction capabilities under multi-party authorization," achieving a unification of technological trust and administrative supervision.

[0027] An energy trading regulatory approach includes the following steps: Step 1: System Initialization and Distribution of Regulatory Authority Upon system startup, the cryptographic parameter system for the Chameleon Hash is first established. The system then generates the master public key for the Chameleon Hash. (Publicly available online) and the initial trapdoor private key To eliminate the risk of isolated political manipulation, the trap-breaking process was immediately initiated: utilizing Shamir... Threshold secret sharing algorithm, Divided into A separate private key fragment The information was then distributed via a secure channel to members of the regulatory committee, comprised of representatives from various stakeholders including the market supervision bureau, the power grid company, and the consumer association. Upon completion of distribution, the original, intact trapdoor was immediately destroyed. This ensures that no single entity has the ability to modify the blockchain while the system is running.

[0028] Step 2: PUF-based terminal registration and transient signature: During the device registration phase, the registration center sends an excitation signal to the PUF module of the smart meter, extracts its physical response, calculates helper data, and stores the "device ID-helper data" mapping relationship in the edge gateway. During daily transactions, when the smart meter collects energy data... At that time, the PUF module powers on and reads the current SRAM physical noise value. Combined with auxiliary data cached locally, it uses a fuzzy extractor to recover the unique physical fingerprint in real time and derive the transient private key. The device uses this private key to access data. Digital signature generation After signing, Immediately erase from volatile memory to ensure the device cannot be physically cloned or the private key extracted.

[0029] Step 3: Privacy scrubbing and aggregation at the edge gateway: The edge gateway receives signed data packets sent by multiple smart meters within its jurisdiction. First, the gateway uses the PUF public key stored on the blockchain to verify the legitimacy of all signatures, eliminating fake device requests that cannot pass physical fingerprint verification. Then, the gateway initiates a privacy cleansing process: using the BLS non-interactive aggregate signature algorithm, it aggregates signatures within the same time window... A single valid signature is compressed into a very short aggregate signature. and the corresponding The plaintext transactions are homomorphically aggregated (e.g., to calculate the total electricity sales of a distribution area) or obfuscated to generate de-identified "regional aggregate blocks". This step ensures that the data uploaded to the blockchain is mathematically verifiable, but it cannot semantically infer individual user privacy.

[0030] Step 4: On-chain consensus based on chameleon hashing: When the edge gateway aggregates blocks When broadcasting to the blockchain network, the ledger node (miner) randomly selects an initial random number. The nodes no longer use the traditional SHA-256 algorithm, but instead utilize the system's public key. Calculate the chameleon hash digest: After successful verification, the tuple will be... Write a new block and link it to the main chain. At this point, for ordinary nodes that do not possess the trapdoor fragment, this hash value... It has the same collision resistance as traditional hashing, ensuring the immutability of the ledger.

[0031] Step 5: Implementation of Compliance Amendments Based on Multi-Party Consensus: When a regulatory body detects a logical anomaly in a certain aggregated block (such as an abnormal extreme value caused by a physical spoofing of the source sensor), it initiates a "correction proposal" to the on-chain smart contract, which includes the original block hash. Corrected data (e.g., "reverse flag"). Oversight committee members vote on proposals on-chain; once the number of votes in favor reaches a threshold... Each node does not leak its own fragments. Under the premise of ensuring security, initiate a secure multi-party computation (MPC) process to jointly compute a new random number. , making New trading pairs broadcast online. After all nodes in the network verify the hash match, the local ledger content is updated without forking or rolling back, thus completing the compliance correction.

[0032] 1. Anomaly Detection and Proposal Initiation: When a regulatory initiator (such as a market supervision bureau) detects a logical anomaly in an aggregated block, such as extreme data values ​​caused by physical spoofing of the source sensor, it sends a correction proposal to the on-chain smart contract. This proposal includes the chameleon hash value of the original block. and the corrected aggregated data content .

[0033] 2. Threshold voting and authorization verification: Step 1: After receiving the proposal, the smart contract sends a voting request to other regulatory nodes of the regulatory committee (such as Chameleon Trapdoor Fragment holders like Node A, Node B, and Node C). Each regulatory node verifies the proposal and then casts a vote of approval or disapproval to the smart contract.

[0034] Step 2: The smart contract summarizes the voting results and strictly executes the threshold judgment logic: verifying whether the number of affirmative votes is greater than or equal to the preset threshold. (i.e., the number of verification votes) If the conditions are met, the subsequent joint computation process will be triggered.

[0035] 3. Secure multi-party computation and hash collision: Step 1: The smart contract sends a command to the regulatory node that voted in favor to start joint computation.

[0036] Step 2: In a secure multi-party computation (MPC) environment, the participating regulatory nodes utilize their respective trapdoor fragments. Joint computation is performed. During this process, each node retains its actual fragment information and jointly calculates a new random number. , so that: .

[0037] Step 3: Each node returns the calculated sharding results to the smart contract.

[0038] 4. Ledger Updates: Step 1: The smart contract combines and shards to obtain a complete new random number. After confirming the new trading pair Its hash value is still Afterwards, the system returns a status indicating successful correction to the regulatory initiator.

[0039] Step 2: The smart contract broadcasts the new trading pair to the entire network. The block. After all the ledger nodes in the network verify that the hash match is correct, they directly update the local ledger content without forking or rolling back, thus completing the compliance correction.

[0040] Specific application scenarios: This invention is applicable to the industrial IoT field, where there are high requirements for data source authenticity, privacy protection, and compliance with regulations. Typical application scenarios include:

[0041] 1. Prevention and Automated Settlement of Subsidy Fraud in Distributed Photovoltaic Systems: This solution addresses the issue of residential photovoltaic systems using simulators to falsify power generation data and fraudulently obtain subsidies. At the inverter end, a PUF (Power Activated Function) ensures that data originates from real physical hardware, preventing software-driven data manipulation. Simultaneously, the power grid, as the regulator, can use threshold chameleon hashing to correct erroneous entries on-chain if metering faults are detected, ensuring secure settlement of subsidy funds without the need for a hard fork.

[0042] 2. Industrial Carbon Emission Monitoring and Green Certificate Auditing addresses the issue of enterprises falsifying pollution discharge data to evade regulation. The system utilizes edge aggregation technology to process high-frequency energy consumption data from factories into regional totals and upload them to the blockchain, preventing the leakage of trade secrets (such as inferring order volume from electricity consumption curves). When environmental audits uncover historical violations, the system can, through consensus among multiple parties within the regulatory committee, forcibly mark or cancel the "green certificates" already issued on the blockchain, achieving penetrating enforcement.

[0043] 3. Electric Vehicle (V2G) Privacy Protection and Dispute Arbitration: Addressing the issue of privacy leaks related to vehicle location and travel patterns during vehicle-to-grid interactions. Charging stations, acting as edge gateways, utilize BLS aggregated signatures to obfuscate and package charging and discharging requests from vehicles within their area onto the blockchain, severing identity associations. In the event of electricity metering disputes, consumer associations and operators jointly utilize trapdoor fragments to compliantly correct disputed bills, protecting group privacy while preserving the ability to correct individual cases.

[0044] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a program for an energy trading supervision method, which, when executed by a processor, implements the steps of the method of the present application.

[0045] Of course, those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware (such as a processor, controller, etc.). The program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The computer-readable storage medium can be a memory, magnetic disk, optical disk, etc.

[0046] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for regulating energy trading, characterized in that, Includes the following steps: S1. Initialization and Distribution of Regulatory Power; S2. PUF-based terminal registration and transient signature; S3. Privacy scrubbing and aggregation at the edge gateway; S4. Block consensus based on chameleon hashing on-chain; S5. Compliance amendments implemented based on multi-party consensus.

2. The energy trading supervision method according to claim 1, characterized in that, S1. Initialization and distribution of regulatory powers, as detailed below: S11. Establish the cryptographic parameter system for Chameleon Hash and generate the master public key for Chameleon Hash. and the initial trapdoor private key ; S12. Initiate the trapdoor crushing process: using Shamir Threshold secret sharing algorithm, Divided into A separate private key fragment The trapdoor was then distributed via a secure channel to members of a regulatory committee comprised of various stakeholders. Once distributed, the original, intact trapdoor was immediately destroyed. This ensures that no single entity has the ability to modify the blockchain while the system is running.

3. The energy trading supervision method according to claim 1, characterized in that, In step S2, during the device network access phase, the registration center sends an excitation signal to the PUF module, extracts its physical response and calculates auxiliary error correction data, and stores the "device ID-auxiliary data" mapping relationship in the edge gateway. During the transaction phase, when the smart meter collects energy data... At that time, the PUF module powers on and reads the current SRAM physical noise value. Combined with locally cached auxiliary data, it uses a fuzz extractor to recover the unique physical fingerprint in real time and derive the transient private key. The device uses this private key to access data. Digital signature generation After signing, Immediately erase from volatile memory to ensure the device cannot be physically cloned or the private key extracted.

4. The energy trading supervision method according to claim 1, characterized in that, Step S3: The edge gateway receives signed data packets sent by multiple smart meters within its jurisdiction. The gateway uses the PUF public key stored on the blockchain to verify the legitimacy of all signatures, eliminating fake device requests that cannot pass physical fingerprint verification; the gateway initiates a privacy cleansing process: using the BLS non-interactive aggregate signature algorithm, it merges signatures within the same time window. A single valid signature is compressed into a very short aggregate signature. and the corresponding The plaintext transactions are homomorphically aggregated or obfuscated to generate de-identified "regional aggregate blocks". .

5. The energy trading supervision method according to claim 1, characterized in that, Step S4: When the edge gateway aggregates blocks When broadcasting to the blockchain network, the ledger node randomly selects an initial random number. Using the node's public key Calculate the chameleon hash digest: ； After successful verification, the tuple will be... Write a new block and link it to the main chain.

6. The energy trading supervision method according to claim 1, characterized in that, Step S5: When the regulatory agency detects a logical anomaly in a certain aggregated block, it initiates a "correction proposal" to the on-chain smart contract, which includes the original block hash. Corrected data The oversight committee members vote on the proposal on-chain, and once the number of votes in favor reaches a threshold... Each node does not leak its own fragments. Under the premise of ensuring security, initiate secure multi-party computation to jointly compute a new random number. , so that: ； New trading pairs broadcast online After all nodes in the network verify the hash match, the local ledger content is updated without forking or rolling back, thus completing the compliance correction.

7. The energy trading supervision method according to claim 6, characterized in that, Step S5 includes: Anomaly Detection and Proposal Initiation: When the regulatory initiator detects a logical anomaly in the aggregated block, it sends a correction proposal to the on-chain smart contract. This proposal includes the chameleon hash value of the original block. and the corrected aggregated data content ; Threshold voting and authorization verification: Step 1: After receiving the proposal, the smart contract sends a voting request instruction to other regulatory nodes of the regulatory committee. Each regulatory node verifies the proposal and then casts a vote of approval or disapproval to the smart contract. Step 2: The smart contract summarizes the voting results and strictly executes the threshold judgment logic: verifying whether the number of affirmative votes is greater than or equal to the preset threshold. If the conditions are met, the subsequent joint computation process will be triggered. Secure multi-party computation and hash collisions: Step 1: The smart contract sends a command to the regulatory node that voted in favor to initiate joint computation; Step 2: In a secure multi-party computation environment, the participating regulatory nodes utilize their respective trapdoor fragments. Joint computation is performed, during which each node does not reveal the true fragment information to the others, and together they calculate a new random number. ; Step 3: Each node returns the calculated sharding result to the smart contract; Ledger Update: Step 1: The smart contract combines and shards to obtain a complete new random number. After confirming the new trading pair Its hash value is still Then, the system returns a status indicating successful correction to the regulatory initiator. Step 2: The smart contract broadcasts the new trading pair to the entire network. The block.

8. An energy trading supervision system, characterized in that, Including the terminal side, edge side, and cloud side; On the terminal side: Based on the source anchoring logic of transient physical fingerprints, a PUF module is introduced into the terminal. It utilizes the randomness of the microscopic physical features at the moment the chip is powered on to build an authentication mechanism of "hardware as identity". The physical fingerprint is recovered in real time and a transient private key is derived for signing only within the millisecond window when the transaction occurs. The fingerprint is erased immediately after signing is completed. Edge side: An edge computing gateway is introduced between the terminal and the blockchain as a "privacy cleaning pool". Using BLS aggregate signature technology, the gateway compresses the independent signatures of hundreds or thousands of users in the jurisdiction into a unique aggregate signature, and homomorphically summarizes or obfuscates the specific transaction plaintext to generate regional aggregate blocks. On the cloud side: a correctable consensus ledger is constructed based on the compliance correction logic of threshold chameleon hash.

9. The energy trading supervision system according to claim 8, characterized in that, By leveraging the "trapdoor" property of the Chameleon hash function, block content can be replaced without changing the hash value. The Shamir threshold secret sharing technology "crushes" the trapdoor power and distributes it to a committee composed of multiple regulatory bodies. Only with consensus among the parties can the hash collision parameters be calculated, allowing for in-situ, seamless correction of illegal transactions or erroneous data on the chain.

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