Privacy-protection-based physical resource authentication method and apparatus

Abstract

Provided are a privacy-protection-based physical resource authentication method and apparatus. A target circuit logic is deployed in a first device involved in the method, and same comprises a calculation circuit portion and a generation algorithm portion. The method comprises: a first device generating, by using a first private key thereof, a first commitment for original resource data of a physical resource held by the first device; then at least inputting the original resource data and the first commitment into target circuit logic, verifying the first commitment by means of a calculation circuit portion, calculating conclusion data corresponding to the original resource data, and generating, by means of a generation algorithm portion, a zero-knowledge proof regarding the calculation correctness of the calculation circuit portion, so as to obtain first proof data, wherein the conclusion data indicates the health state of the physical resource and is used for resource value evaluation; and the first device then correspondingly storing the first commitment and the first proof data in a second device for the second device to verify the zero-knowledge proof.

Description

Privacy-Preserving Physical Resource Authentication Method and Device

[0001] This application claims priority to Chinese Patent Application No. 2024113981998, filed on October 8, 2024, entitled "Personal Information Protection-Based Physical Resource Authentication Method and Apparatus", the entire contents of which are incorporated herein by reference. Technical Field

[0002] The embodiments in this specification belong to the field of computer technology, and in particular relate to a method and apparatus for authenticating physical resources based on privacy protection. Background Technology

[0003] The valuation of physical resources (such as power battery resources) requires the completion of the assessment based on the original resource data of the physical resources. This original resource data is the private data of the resource holder. Providing this original resource data to the assessor for resource valuation could lead to privacy data leakage, cross-institutional data compliance issues, and business risks.

[0004] A reasonable and reliable solution is needed to achieve effective resource valuation without disclosing the original resource data of physical resources. Summary of the Invention

[0005] The purpose of this invention is to provide a privacy-preserving physical resource authentication scheme that can achieve effective resource value assessment without disclosing the original resource data of the physical resource.

[0006] This specification provides a privacy-preserving physical resource authentication method, executed by a first device. The first device deploys target circuit logic, including a computational circuit section and a generation algorithm section. The method includes: generating a first commitment for original resource data of a physical resource held by the first device using a first private key; inputting at least the original resource data and the first commitment into the target circuit logic; verifying the first commitment through the computational circuit section and calculating conclusion data corresponding to the original resource data; and generating a zero-knowledge proof regarding the correctness of the computation by the computational circuit section through the generation algorithm section to obtain first proof data, wherein the conclusion data indicates the health status of the physical resource and is used for resource value assessment; and storing the first commitment and the first proof data in a corresponding manner in a second device for the second device to verify the zero-knowledge proof.

[0007] A second aspect of this specification provides a privacy-preserving physical resource authentication method, comprising: a first device using its own first private key to generate a first commitment for original resource data of a physical resource held by the first device; the first device deploying target circuit logic, including a computational circuit part and a generation algorithm part; the first device inputting at least the original resource data and the first commitment into the target circuit logic, verifying the first commitment through the computational circuit part, calculating conclusion data corresponding to the original resource data, and generating a zero-knowledge proof regarding the correctness of the computation by the computational circuit part through the generation algorithm part to obtain first proof data, wherein the conclusion data indicates the health status of the physical resource for resource value assessment; the first device storing the first commitment and the first proof data in a corresponding manner in a second device; and the second device verifying the zero-knowledge proof indicated by the first proof data.

[0008] A third aspect of this specification provides a privacy-preserving physical resource authentication device applied to a first device. The first device deploys target circuit logic, including a computational circuit section and a generation algorithm section. The device includes: a generation unit configured to generate a first commitment for original resource data of physical resources held by the first device using a first private key; a proof unit configured to input at least the original resource data and the first commitment into the target circuit logic, verify the first commitment through the computational circuit section, calculate conclusion data corresponding to the original resource data, and generate a zero-knowledge proof regarding the correctness of the computational circuit section's calculation through the generation algorithm section to obtain first proof data, wherein the conclusion data indicates the health status of the physical resource for resource value assessment; and a storage unit configured to store the first commitment and the first proof data in a corresponding manner in a second device for the second device to verify the zero-knowledge proof.

[0009] A fourth aspect of this specification provides a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to perform the method described in the first aspect.

[0010] A fifth aspect of this specification provides a computing device including a memory and a processor, wherein the memory stores executable code, and the processor, when executing the executable code, implements the method described in the first aspect.

[0011] A sixth aspect of this specification provides a computer program product including a computer program / instructions that, when executed by a processor, implement the steps of the method as described in the first aspect.

[0012] The above embodiments of this specification provide a customized target circuit logic, including a computational circuit section and a generation algorithm section, which is deployed in a first device. In this scheme, the first device can use its own first private key to generate a first commitment for the original resource data of the physical resources held by the first device. Then, at least the original resource data and the first commitment are input into the target circuit logic. The computational circuit section verifies the first commitment and calculates the conclusion data corresponding to the original resource data, and the generation algorithm section generates a zero-knowledge proof regarding the correctness of the computation by the computational circuit section, obtaining first proof data. This conclusion data indicates the health status of the physical resource and is used for resource value assessment. Next, the first device stores the first commitment and the first proof data in a corresponding manner in a second device for the second device to verify the zero-knowledge proof indicated by the first proof data.

[0013] By customizing the target circuit logic and introducing a commitment generated for the original resource data, the association between the original resource data and the device identity can be ensured. This verifies the authenticity of the original resource data while simultaneously verifying the device identity, providing multiple guarantees for the authenticity and anonymity of the original resource data. Through ZKP (Zero-Knowledge Proof) technology, the original resource data remains within the device and is not leaked throughout the entire process. What is transmitted over the network is the proof data, not the original resource data itself, ensuring the "invisibility" of the original resource data during the verification process. Even if the proof data is intercepted by a third party, the interceptor cannot reconstruct it from the original resource data, thus effectively protecting user privacy. Furthermore, if the zero-knowledge proof verification shown by the proof data passes, the verification result of the zero-knowledge proof indicates that the conclusion data shown by the proof data is authentic and reliable, allowing for resource value assessment based on this conclusion data. Therefore, effective resource value assessment can be achieved without disclosing the original resource data of physical resources, avoiding cross-institutional data compliance issues and business risks. Attached Figure Description

[0014] To more clearly illustrate the technical solutions of the embodiments in this specification, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 is a schematic diagram of one application scenario in which the embodiments of this specification can be applied;

[0016] Figure 2 is a blockchain architecture diagram in one embodiment;

[0017] Figure 3 is a timing diagram of a privacy-preserving physical resource authentication method in an embodiment of this specification;

[0018] Figure 4 is a timing diagram of the resource assessment process in an embodiment of this specification;

[0019] Figure 5 is another timing diagram of the privacy-preserving physical resource authentication method in the embodiments of this specification;

[0020] Figure 6 is another timing diagram of the resource assessment process in the embodiments of this specification;

[0021] Figure 7 is an exemplary schematic diagram of the power battery resource evaluation process in an embodiment of this specification;

[0022] Figure 8 is a schematic diagram of the physical resource authentication device based on privacy protection in the embodiments of this specification. Detailed Implementation

[0023] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this specification.

[0024] As mentioned earlier, the raw resource data of physical resources is the private data of the resource holder. Providing this raw resource data to an assessor for resource value assessment could lead to privacy data leakage, cross-agency data compliance issues, and business risks.

[0025] This specification provides a privacy-preserving physical resource authentication scheme that enables effective resource value assessment without disclosing the original resource data of the physical resource.

[0026] Figure 1 is a schematic diagram of an application scenario in which the embodiments of this specification can be applied. As shown in Figure 1, the application scenario involves physical resources 100, device 101, and device 102.

[0027] Physical resource 100 is a resource with economic value that can be assessed for its value. For example, physical resource 100 can be any of the following: artwork, jewelry, agricultural products, buildings, new energy equipment, and power battery resource 100 as shown in Figure 1. Power battery resource 100 can include, but is not limited to, any of the following: charging piles, new energy batteries, solar cells, batteries in electric vehicles, and batteries in electric vehicles. The following description primarily uses power battery resource 100 as an example.

[0028] Device 101 includes power battery resource 100, or device 101 is an edge device on the side of power battery resource 100. In practical applications, when the internal hardware and software resources of power battery resource 100 / target device (the device where power battery resource 100 is located) meet the resource requirements of ZKP technology, power battery resource 100 / target device can be used as device 101. When the internal hardware and software resources of power battery resource 100 and target device do not meet the resource requirements of ZKP technology, one or more edge devices on the side of power battery resource 100 can be used as device 101.

[0029] Additionally, device 101 deploys target circuit logic (ZKP circuit logic as shown in Figure 1). The ZKP circuit logic includes a computational circuit section and a generation algorithm section. The inputs to the ZKP circuit logic include, but are not limited to, raw resource data of the physical resources and commitments generated for that raw resource data. The computational circuit section verifies the input commitments and calculates conclusion data corresponding to the input raw resource data. This conclusion data indicates the health status of the physical resources and is used for resource value assessment. The generation algorithm section generates zero-knowledge proofs regarding the correctness of the computations performed by the computational circuit section, obtaining proof data.

[0030] Furthermore, the device 101 contains an embedded target chip. The target chip has ZKP and network transmission functions, and can collect raw resource data of the power battery resource 100 through sensors, including battery power.

[0031] Device 102 is used to store the commitment and proof data as described above, and to verify the zero-knowledge proofs shown by the proof data. Furthermore, device 102 may also have resource valuation capabilities. Device 102 can be an institutional device of an authoritative certification body, or a blockchain network.

[0032] Blockchain is a novel application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and cryptographic algorithms. In a blockchain, data blocks are sequentially linked together in a chain-like data structure, and cryptographic methods are used to ensure the immutability and forgery resistance of these data blocks. Due to its decentralized, immutable, and autonomous characteristics, blockchain is receiving increasing attention and application.

[0033] Figure 2 illustrates a blockchain architecture diagram in one embodiment. In the blockchain architecture diagram shown in Figure 2, blockchain 200 includes N nodes, with nodes 1 through 8 schematically shown in Figure 1. The connections between nodes schematically represent P2P (Peer-to-Peer) connections, such as TCP connections, used for data transmission between nodes. These nodes can store the full ledger, that is, the state of all blocks and all accounts. Each node in the blockchain can generate the same state in the blockchain by executing the same transaction, and each node in the blockchain can store the same state database.

[0034] In the blockchain field, a transaction refers to a unit of task executed and recorded within the blockchain. A transaction typically includes a From field, a To field, and a Data field. Specifically, in the case of a transfer transaction, the From field represents the account address initiating the transaction (i.e., initiating a transfer task to another account), the To field represents the account address receiving the transaction (i.e., receiving the transfer), and the Data field includes the transfer amount.

[0035] Blockchain provides the functionality of smart contracts. A smart contract on the blockchain is a contract that can be triggered and executed through transactions within the blockchain system. Smart contracts can be defined in the form of code. Calling a smart contract on the blockchain involves initiating a transaction that points to the smart contract's address, causing each node in the blockchain to run the smart contract code in a distributed manner.

[0036] In a contract deployment scenario, for example, Bob sends a transaction containing information about creating a smart contract (i.e., deploying the contract) to the blockchain shown in Figure 1. The transaction's `data` field includes the code of the contract to be created (such as bytecode or machine code), and the `to` field is empty to indicate that the transaction is used to deploy the contract. After the nodes reach a consensus through the consensus mechanism, they determine the contract address "0x6f8ae93…". Each node adds a contract account corresponding to the smart contract's contract address to its state database, allocates state storage corresponding to that contract account, stores the contract code, and saves the hash value of the contract code in the contract's state storage, thus successfully creating the contract.

[0037] In a scenario where a contract is invoked, for example, Bob sends a transaction to the blockchain shown in Figure 1 to invoke a smart contract. The "from" field of this transaction is the address of the account of the transaction initiator (i.e., Bob), the "to" field is "0x6f8ae93…", which is the address of the smart contract being invoked, and the "data" field of the transaction includes the method and parameters for invoking the smart contract. After consensus is reached on this transaction in the blockchain, each node in the blockchain can execute the transaction, thereby executing the contract separately, and updating the state database based on the execution of the contract.

[0038] When device 102 is an institution device belonging to an authoritative certification body, the institution device deploys verification algorithm logic, and verifies the zero-knowledge proof shown by the proof data by executing the verification algorithm logic. When device 102 is a blockchain network, the blockchain network deploys a smart contract C1 for executing the verification algorithm logic, and the blockchain network can verify the zero-knowledge proof shown by the proof data by executing the verification algorithm logic corresponding to the verification interface of smart contract C1.

[0039] When there is a need to assess the resource value of power battery resource 100, as shown in Figure 1, device 101 can collect the original resource data (soc) of power battery resource 100, such as the original resource data (soc) of power battery resource 100 within a target time period, including battery capacity. The target time period can be, for example, the past month, two months, six months, or one year, etc., and can be set according to actual needs, without specific limitations here. Then, device 101 can use its private key key1 to generate a commitment h for the original resource data (soc). Next, device 101 can input at least the original resource data (soc) and commitment h into the ZKP circuit logic, verify commitment h through the calculation circuit part, calculate the conclusion data (i.e., cumulative charge / discharge times) corresponding to the original resource data (soc), and generate a zero-knowledge proof regarding the correctness of the calculation by the calculation circuit part through the generation algorithm part, obtaining proof data P1. Then, device 101 can store commitment h and proof data P1 correspondingly in device 102. Then, device 102 can verify the zero-knowledge proof shown by proof data P1.

[0040] If the zero-knowledge proof verification shown in proof data P1 passes, the verification result of this zero-knowledge proof confirms that the cumulative charge-discharge count shown in proof data P1 is authentic and reliable data. Therefore, resource value assessment can be performed based on this cumulative charge-discharge count. Specifically, this cumulative charge-discharge count is negatively correlated with the resource value of power battery resource 100. It should be understood that the fewer the cumulative charge-discharge counts of the power battery resource, the higher its value. Thus, effective resource value assessment can be achieved without disclosing the original resource data (SOC) of power battery resource 100, avoiding cross-institutional data compliance issues and commercial risks.

[0041] In one implementation, the application scenario shown in Figure 1 may further include device 103 of a local data service provider. Device 103 can be a node in a trusted oracle network. Device 101 can store the commitment h and the original resource data soc in device 103 for regulatory verification of the original resource data soc. By introducing an oracle and storing the data in a local data service provider, the verification and evidence collection requirements of regulators can be met. Regulators can use the transaction log of each resource verification to query the data storage service, and can trace back the resource details and ZKP verification process throughout the entire process, ensuring that the commitment generated for the original resource data and the logic contained in the zero-knowledge proof shown by the proof data are both true and reliable.

[0042] The physical resource authentication process will now be described with reference to Figure 3. Figure 3 is a timing diagram of a privacy-preserving physical resource authentication method in an embodiment of this specification. The method involves physical resources 100, device 101, and device 102 as described above, and includes steps S301-S307 as shown below.

[0043] As shown in Figure 3, in step S301, device 101 uses its private key key1 to generate a commitment h for the original resource data soc of the physical resource 100 held by device 101.

[0044] In this process, commitment h participates in the generation of zero-knowledge proofs to verify the authenticity of the proofs and the device's identity during the verification phase. When generating commitment h, device 101 can utilize the preset Pedersen commitment algorithm, using key1 to generate commitment h for the original resource data soc. The Pedersen commitment algorithm is a cryptographic technique that allows the prover to commit to a value without revealing or being able to change it. The core of this algorithm lies in its ability to provide a commitment value generated based on the original information and some random numbers. However, the verifier can only verify the correctness of the original information through the provided commitment value, without knowing the specific content of the original information. Since the Pedersen commitment algorithm is a well-known technique, its calculation process will not be elaborated upon here.

[0045] Next, in step S303, device 101 inputs at least the original resource data soc and commitment h into the locally deployed ZKP circuit logic, verifies commitment h through the computation circuit part, calculates the conclusion data corresponding to the original resource data soc, and generates a zero-knowledge proof on the correctness of the computation circuit part through the generation algorithm part to obtain proof data P1, wherein the conclusion data indicates the health status of physical resource 100 and is used for resource value assessment.

[0046] It should be noted that the computational circuit section includes the public key key2 corresponding to key1, or the input of the ZKP circuit logic also includes key2. When the input of the ZKP circuit logic also includes key2, key2 and the commitment h are the public inputs of the ZKP circuit logic, and the original resource data soc is the private input of the ZKP circuit logic.

[0047] When verifying commitment h, the computational circuit can use key2 and the original resource data soc to reconstruct the commitment h generated by device 101 for the original resource data soc, thereby obtaining the calculated value h1, and then determine whether the calculated value h1 is equal to the commitment h. If the calculated value h1 is determined to be equal to the commitment h, the commitment h verification passes; otherwise, the commitment h verification fails.

[0048] In addition, the computing circuit section includes computing logic for calculating the conclusion data corresponding to the original resource data. This computing logic can be used to calculate the conclusion data corresponding to the original resource data (soc).

[0049] Taking physical resource 100 as power battery resource 100 as an example, the original resource data soc includes the battery capacity of power battery resource 100 within the target time period, and the conclusion data corresponding to the original resource data soc is the cumulative charge and discharge times cnt of power battery resource 100 within the target time period. When the original resource data soc is the battery capacity of power battery resource 100 within the target time period, the calculation process of the cumulative charge and discharge times cnt can include: for any two battery capacities of power battery resource 100 collected at adjacent times within the target time period, if the difference v1 between the latter and former battery capacities is greater than 0, then the cumulative charge amount total of power battery resource 100 within the target time period is increased by v1; based on the calculated total and the preset capacity threshold (e.g., 100), the cumulative charge and discharge times cnt are determined. The initial value of total is 0. Taking a capacity threshold of 100 as an example, cycles = total / 100 can be calculated. If cycles is an integer, then cnt = cycles; if cycles is a decimal, then cnt is equal to the integer part of cycles.

[0050] In practice, the trends of battery voltage and battery capacity are generally consistent. To improve the accuracy of the calculation of the cumulative charge-discharge count in the calculation circuit, the battery voltage can also be used as the input of the ZKP circuit logic. Based on this, in one embodiment, the original resource data soc includes the battery voltage and battery capacity of the power battery resource 100 within the target time period. The calculation process of the cumulative charge-discharge count cnt of the power battery resource 100 within the target time period may include: for any two battery capacities of the power battery resource 100 collected at adjacent times within the target time period, if the difference v1 between the latter battery capacity and the former battery capacity is greater than 0, and the difference v2 between the battery voltages corresponding to the latter battery capacity and the former battery capacity is greater than 0, then the cumulative charge amount total of the power battery resource within the target time period is increased by v1; based on the calculated cumulative charge amount total and the preset capacity threshold, the cumulative charge-discharge count cnt is determined.

[0051] In one implementation, the compilation result of the computational circuit section includes an executable bytecode file (such as a wasm file) obtained by compiling the computational logic of the computational circuit section, and a description file (such as an R1CS file) used to describe the constraint information of the computational circuit section. In practice, the wasm file is used to handle complex computational tasks and generate witness data, while the R1CS (Rank-1 Constraint System) file defines the mathematical constraints that ensure the validity of the proof. The combination of these two allows ZKP technology to verify the authenticity of information without disclosing specific information, thus providing a powerful means of privacy protection.

[0052] The aforementioned description file can be used to generate a proof key pk and a verification key vk. The proof key pk is stored by device 101 for generating zero-knowledge proofs. The verification key vk is stored by device 102 for verifying zero-knowledge proofs. The compilation of the computational circuitry, and the generation of the proof key pk and verification key vk, can be performed by device 101 or other devices, and must be performed before device 101 generates the zero-knowledge proof for the first time.

[0053] In the process of verifying the commitment h through the computational circuit and calculating the conclusion data corresponding to the original resource data soc, the bytecode file can be run based on the input of the ZKP circuit logic (including the original resource data soc and the commitment h) to generate several intermediate variables. Then, the witness data can be generated based on the values ​​of these intermediate variables through the generation algorithm, and a zero-knowledge proof can be generated based on this witness data and the proof key pk, resulting in proof data P1. The witness data can include the original resource data soc and the values ​​of the intermediate variables.

[0054] Next, in step S305, device 101 stores the commitment h and proof data P1 in device 102.

[0055] Next, in step S307, device 102 verifies the zero-knowledge proof shown by proof data P1.

[0056] Specifically, device 101 can send a data storage request containing commitment h and proof data P1 to device 102, so that device 102 can store the commitment h and proof data P1 accordingly. Afterwards, device 102 can verify the zero-knowledge proof shown by the proof data P1.

[0057] As an example, device 102 is equipped with verification algorithm logic. Device 102 can verify the zero-knowledge proof shown by the proof data P1 by executing this verification algorithm logic. Furthermore, device 102 pre-stores the public key key2 and verification key vk as described above. Device 102 can verify the zero-knowledge proof shown by the proof data P1 based on the commitment h, the public key key2, and the verification key vk by executing this verification algorithm logic.

[0058] The solution provided in the embodiment corresponding to Figure 3, by customizing ZKP circuit logic and introducing a commitment generated for the original resource data, ensures that the original resource data is associated with the device identity. This verifies the authenticity of the original resource data while simultaneously verifying the device identity, providing multiple guarantees for the authenticity and anonymity of the original resource data. Through ZKP technology, the original resource data never leaves the device and is never leaked throughout the entire process. What is transmitted over the network is proof data, not the original resource data itself, ensuring the "invisibility" of the original resource data during the verification process. Even if the proof data is intercepted by a third party, the interceptor cannot reconstruct it from the original resource data, thus effectively protecting user privacy. Furthermore, if the zero-knowledge proof verification shown by the proof data passes, the verification result of the zero-knowledge proof indicates that the conclusion data shown by the proof data is authentic and reliable, allowing for resource value assessment based on this conclusion data. Therefore, effective resource value assessment can be achieved without leaking the original resource data of physical resources, avoiding cross-institutional data compliance issues and business risks.

[0059] In practice, the verification of the zero-knowledge proof shown by proof data P1 can be performed automatically by device 102 after receiving proof data P1 and commitment h, or in response to a resource evaluation request sent by device 104. This resource evaluation request includes data identifiers for several proof data corresponding to several physical resources, including proof data P1. In one example, these physical resources belong to the same resource holder, and device 104 is a device belonging to a partner of that resource holder. Taking a lending scenario in RWA (Real Word Assets) as an example, in this scenario, the resource holder is the borrower, and the partner is the lender. RWA can convert valuable real-world resources (real estate, art, power battery resources, etc.) into digital tokens, which can then be traded and circulated on the blockchain.

[0060] The resource assessment process involving devices 102 and 104 will now be described with reference to Figure 4. Figure 4 is a timing diagram of the resource assessment process in an embodiment of this specification. The resource assessment process includes steps S401-S405 as shown below.

[0061] As shown in Figure 4, in step S401, device 104 sends a resource assessment request to device 102, which includes data identifiers of several proof data corresponding to several physical resources.

[0062] The aforementioned physical resources refer to one or more physical resources; correspondingly, the aforementioned proof data refer to one or more proof data. Furthermore, the aforementioned proof data may include proof data P1 as described above, and the aforementioned proof data is stored in device 102.

[0063] Next, in step S403, device 102 verifies the zero-knowledge proofs shown by the aforementioned proof data.

[0064] Specifically, for each of the aforementioned proof data, device 102 can verify the zero-knowledge proof shown by the proof data by executing a locally deployed verification algorithm logic. Furthermore, device 102 also stores a commitment associated with the proof data, a public key for verifying the commitment, and a verification key vk. Device 102 can verify the zero-knowledge proof shown by the proof data based on the commitment, the public key, and the verification key vk by executing the verification algorithm logic.

[0065] When the zero-knowledge proof verification shown by one or more of the aforementioned proof data fails, device 102 can return feedback information to device 104 indicating that the verification of the one or more proof data has failed. When the zero-knowledge proofs shown by the aforementioned proof data all pass verification, step S505 can then be executed.

[0066] In step S405, in response to the fact that all the zero-knowledge proofs shown by the aforementioned proof data have been verified, the device 102 determines the resource value of the aforementioned physical resources based on the conclusion data shown by the aforementioned proof data.

[0067] In one example, for each of the aforementioned physical resources, the resource value can be determined based on the conclusion data shown by the supporting evidence data for that physical resource. In another example, when the aforementioned physical resources belong to the same resource holder and are of the same resource category, in order to improve the efficiency of resource assessment, the sum of the conclusion data shown by the aforementioned supporting evidence data can be used as assessment reference data, and the total resource value of the aforementioned physical resources can be determined based on this assessment reference data.

[0068] Furthermore, when the aforementioned physical resources are several power battery resources, and the original resource data as mentioned above includes the battery capacity of the power battery resources within the target time period, and the conclusion data is the cumulative number of charge and discharge cycles of the power battery resources within the target time period, the sum of the cumulative number of charge and discharge cycles shown by the aforementioned evidence data can be used as evaluation reference data, and the overall health of the battery can be determined based on the evaluation reference data, and then the total resource value of the several power battery resources can be determined based on the overall health of the battery.

[0069] It should be noted that device 102 has a preset resource assessment strategy, which it can use to assess the resource value of the aforementioned physical resources. Taking power battery resources as an example, in one instance, the resource assessment strategy may include a mapping relationship from assessment reference data to the overall health of the battery, and a mapping relationship from the overall health of the battery to the total resource value. It should be understood that the content of this resource value assessment strategy can be configured according to actual needs and is not specifically limited here.

[0070] In the embodiment corresponding to Figure 4, by supporting the inclusion of data identifiers for several proof data corresponding to several physical resources in a resource assessment request, batch verification of the proof data can be achieved. Then, resource value assessment can be performed after the batch verification is passed. This can greatly improve the throughput of resource assessment requests and reduce user costs.

[0071] As described above, device 102 can be a blockchain network or an institutional device of an authoritative certification body.

[0072] When device 102 is a blockchain network, a smart contract C1 is deployed in the blockchain network 102 to execute the verification algorithm logic. As mentioned earlier, the data storage request is a transaction Tx1 that calls the storage interface of smart contract C1. Based on transaction Tx1, blockchain network 102 can store the commitment h and proof data P1 into the contract state of smart contract C1. It should be noted that the private key key1 of device 101 participates not only in commitment generation but also in the interaction between device 101 and blockchain network 102. For example, transaction Tx1 can include a signature generated based on key1, and blockchain network 102 can store the public key key2 corresponding to key1. After verifying the signature using key2, blockchain network 102 stores the commitment h and proof data P1 into the contract state of smart contract C1. Then, blockchain network 102 can execute the verification algorithm logic corresponding to the verification interface of smart contract C1 to verify the zero-knowledge proof shown by proof data P1. Specifically, the contract state may pre-store the public key key2 and the verification key vk as described above. The blockchain network 102 can execute the verification algorithm logic to verify the zero-knowledge proof shown by the proof data P1 based on the commitment h, the public key key2 and the verification key vk.

[0073] Furthermore, as mentioned above, the resource assessment request is a transaction Tx2 that invokes the verification interface of smart contract C1. Blockchain network 102 can respond to transaction Tx2 sent by device 104, and according to transaction Tx2, execute the verification algorithm logic corresponding to the verification interface of smart contract C1 to verify the zero-knowledge proof shown by proof data P1. Specifically, transaction Tx2 includes data identifiers corresponding to several proof data for several physical resources. These several proof data include proof data P1. Blockchain network 102 can execute the verification algorithm logic according to transaction Tx2 to verify the zero-knowledge proofs shown by these several proof data respectively. Afterwards, in response to the successful verification of all the zero-knowledge proofs shown by these several proof data, blockchain network 102 can determine the resource value of the aforementioned physical resources based on the conclusion data shown by these several proof data respectively.

[0074] As is well known, the execution of transactions in a blockchain network requires gas. Gas is a unit used to measure and pay for the computational resources required to perform operations on a blockchain network. To reduce gas consumption and thus reduce the investment costs for resource holders (such as physical enterprises) of physical resource 100, blockchain scaling solutions (such as zkSync Era) can be introduced, enabling the blockchain network 102 to include a Layer 2 network, and allowing the smart contract C1, as described above, to be deployed within the Layer 2 network. Thus, the commitment h and proof data P1 can be stored in the contract state of smart contract C1, and the Layer 2 network can verify the zero-knowledge proof shown by proof data P1 by executing the verification algorithm logic corresponding to the verification interface of smart contract C1.

[0075] The physical resource authentication process involving a Layer 2 network is described below with reference to Figure 5. Figure 5 is another timing diagram of the privacy-preserving physical resource authentication method in an embodiment of this specification. The method includes steps S501-S509 as shown below.

[0076] As shown in Figure 5, in step S501, device 101 uses its private key key1 to generate a commitment h for the original resource data soc of the physical resource 100 held by device 101.

[0077] In step S503, device 101 inputs at least the original resource data soc and commitment h into the locally deployed ZKP circuit logic, verifies commitment h through the computation circuit part, calculates the conclusion data corresponding to the original resource data soc, and generates a zero-knowledge proof on the correctness of the computation circuit part through the generation algorithm part to obtain proof data P1, wherein the conclusion data indicates the health status of physical resource 100 and is used for resource value assessment.

[0078] In step S505, device 101 sends transaction Tx1 to the second-layer network in blockchain network 102, which calls the storage interface of smart contract C1 and includes commitment h and proof data P1.

[0079] In step S507, the Layer 2 network stores the commitment h and proof data P1 into the contract state of smart contract C1 according to transaction Tx1.

[0080] In step S509, the second-layer network executes the verification algorithm logic corresponding to the verification interface of smart contract C1 to verify the zero-knowledge proof shown by the proof data P1.

[0081] For an explanation of the implementation details of steps S501-S509, please refer to the relevant explanations above, which will not be repeated here.

[0082] The solution provided by the embodiment corresponding to Figure 5 can not only achieve the technical effects of the embodiment corresponding to Figure 3, but also reduce the investment cost of the resource holder by introducing a two-layer network for zero-knowledge proof verification.

[0083] In one embodiment, the blockchain network 102 includes a main chain and a layer-two network. As previously described, smart contract C1 is deployed in the layer-two network, while smart contract C2 for resource valuation is deployed in the main chain. Thus, high-frequency zero-knowledge proof verification can be performed on the lower-cost layer-two network, while only a small number of critical resource updates are performed on the main chain.

[0084] The following describes the resource evaluation process, using blockchain network 102, which includes a main chain and a layer 2 network, with smart contract C2 deployed in the main chain and smart contract C1 deployed in the layer 2 network, in conjunction with Figure 6. Figure 6 is another timing diagram of the resource evaluation process in this embodiment of the specification. This resource evaluation process includes the following steps S601-S609.

[0085] As shown in Figure 6, in step S601, device 104 sends transaction Tx2 to the second-layer network in blockchain network 102, which calls the verification interface of smart contract C1 and includes data identifiers of several proof data corresponding to several physical resources.

[0086] The evidence data is stored in the contract state of smart contract C1.

[0087] Next, in step S603, the second-layer network executes the verification algorithm logic corresponding to the verification interface of smart contract C1 based on transaction Tx2, and verifies the zero-knowledge proofs shown by the aforementioned proof data respectively.

[0088] Next, in step S605, the second-layer network responds to the fact that all the zero-knowledge proofs shown by the aforementioned proof data have been verified, and uses the sum of the conclusion data shown by the aforementioned proof data as the evaluation reference data R.

[0089] Next, in step S607, the second-layer network sends the transaction certificate Tv of transaction Tx2 to the main chain in the blockchain network 102, which includes the evaluation reference data R.

[0090] Specifically, the Layer 2 network can send transaction credentials (Tv) to the main chain via a rollup mechanism. The transaction credentials (Tv) can also include information such as the device identifier of device 104. In practice, the rollup mechanism is a scaling solution that processes transactions off-chain and then "packages" the transaction data into the main chain. It solves the scalability problem of blockchain networks such as Ethereum, allowing more transactions to be processed while maintaining the security and decentralization of the main chain.

[0091] After receiving the transaction certificate Tv, the main chain can verify the authenticity of transaction Tx2 based on the transaction certificate Tv. Specifically, the main chain has an internal mechanism for verifying the authenticity of transactions executed by the Layer 2 network, and the main chain uses this mechanism to verify the authenticity of transaction Tx2 based on the transaction certificate Tv.

[0092] Next, in step S609, after the main chain verifies the authenticity of transaction Tx2 based on transaction certificate Tv, it calls smart contract C2 to determine the total resource value of the aforementioned physical resources based on the evaluation reference data R.

[0093] In practice, the main chain's determination of the total resource value of the aforementioned physical resources can be executed automatically after the authenticity verification of transaction Tx2 is passed, or triggered by device 104. When this determination operation is triggered by device 104, after the main chain verifies the authenticity of transaction Tx2, it can store the transaction voucher Tv and return the verification result of the authenticity of transaction Tx2 to the Layer 2 network. In one example, the transaction voucher Tv can be stored in the contract state of smart contract C2. Then, in response to receiving the verification result, the Layer 2 network can return the transaction voucher Tv to device 104. Next, device 104 can send transaction Tx3 to the main chain, which calls smart contract C2 and includes the transaction voucher Tv. Then, after the main chain verifies the transaction voucher Tv in transaction Tx3, it calls smart contract C2 to determine the total resource value of the aforementioned physical resources based on the evaluation reference data R.

[0094] When the main chain verifies the transaction voucher (Tv) in transaction Tx3, it can search for the transaction voucher (Tv) in the locally stored transaction vouchers. If it is found, the transaction voucher (Tv) is considered to have passed verification. If it is not found, the transaction voucher (Tv) is considered to have failed verification.

[0095] Below, using a lending scenario in RWA as an example, and referring to Figure 7, we will illustrate the resource assessment process described in Figure 6. Figure 7 is an exemplary schematic diagram of the power battery resource assessment process. In this lending scenario, entity A, possessing multiple power battery resources, acts as the borrower and hopes to obtain a loan from lending institution B (such as a bank) through on-chain digital resources. In this case, entity A can, as shown in Figure 7, complete an agency authorization agreement with lending institution B, the lender. After authorization, lending institution B can verify the zero-knowledge proofs shown by the multiple proof data corresponding to the multiple power battery resources and assess the resource value of the multiple power battery resources.

[0096] Specifically, as shown in Figure 7, lending institution B can select proof data from enterprise A and then submit resource assessment to the Layer 2 network. For example, lending institution B can select multiple proof data corresponding to multiple power battery resources of enterprise A through device 104, generate transaction Tx2 based on the data identifier of these multiple proof data, and then send transaction Tx2 to the Layer 2 network. Transaction Tx2 calls the verification interface of smart contract C1 deployed in the Layer 2 network and includes the data identifier. Afterwards, the Layer 2 network can obtain verification parameters based on transaction Tx2 and execute the verification algorithm logic corresponding to the verification interface, performing ZKP proof verification based on the verification parameters. The verification parameters include the verification key vk, the commitment associated with each of the multiple proof data, and the public key used to verify the commitment. After the zero-knowledge proofs shown by the multiple proof data are all verified, the Layer 2 network can perform resource calculation and resource accumulation for the multiple power battery resources. For example, it can calculate the sum of the cumulative charge and discharge times shown by the multiple proof data and use this sum as the total cumulative charge and discharge times of the multiple power battery resources. Next, the Layer 2 network can use the total cumulative charge-discharge count as evaluation reference data and send a transaction certificate containing this evaluation reference data for transaction Tx2 to the main chain via the rollup mechanism. Then, after the main chain verifies the authenticity of transaction Tx2 based on the transaction certificate, it can call smart contract C2 to determine the overall health of the battery based on the evaluation reference data, and determine the total resource value of the multiple power battery resources based on the overall battery health.

[0097] It should be noted that the total resource value can be converted into digital tokens on the blockchain. Enterprise A can convert the aforementioned multiple power battery resources into digital tokens based on the total resource value and publish them on the blockchain. Enterprise A can then obtain a loan from lending institution B based on the digital resources on the chain (such as the digital tokens).

[0098] The solution provided in the embodiment corresponding to Figure 6 completes high-frequency zero-knowledge proof verification based on a two-layer network and supports batch verification of proofs by the two-layer network. This can greatly improve transaction throughput while reducing user costs, such as reducing transaction costs between users and the main chain, and improving transaction processing speed with the main chain.

[0099] Figure 8 is a schematic diagram of the physical resource authentication device based on privacy protection in an embodiment of this specification. This device can be applied to a first device, which deploys target circuit logic, including a computational circuit section and a generation algorithm section. The device can perform the steps executed by device 101 as shown in Figures 3 and 5. The device includes: a generation unit 801, configured to generate a first commitment using its own first private key for the original resource data of the physical resources held by the first device; a proof unit 802, configured to input at least the original resource data and the first commitment into the target circuit logic, verify the first commitment through the computational circuit section, calculate the conclusion data corresponding to the original resource data, and generate a zero-knowledge proof regarding the correctness of the computation by the computational circuit section through the generation algorithm section, obtaining first proof data, wherein the conclusion data indicates the health status of the physical resource and is used for resource value assessment; and a storage unit 803, configured to store the first commitment and the first proof data corresponding to a second device for the second device to verify the zero-knowledge proof.

[0100] This specification also provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed in a computer, it causes the computer to perform the methods described in Figures 3 to 6.

[0101] This specification also provides a computing device, including a memory and a processor, wherein the memory stores executable code, and when the processor executes the executable code, it implements the method described in Figures 3 to 6.

[0102] This specification also provides a computer program product, including a computer program / instruction that, when executed by a processor, implements the steps of the method described in Figures 3 to 6.

[0103] In the 1990s, improvements to a technology could be clearly distinguished as either hardware improvements (e.g., improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the methodology). However, with technological advancements, many methodological improvements today can be considered direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved methodology into the hardware circuit. Therefore, it cannot be said that a methodological improvement cannot be implemented using hardware physical modules. For example, a Programmable Logic Device (PLD) (such as a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logic function is determined by the user programming the device. Designers can program and "integrate" a digital system onto a PLD themselves, without needing chip manufacturers to design and manufacture dedicated integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing integrated circuit chips, this programming is mostly implemented using "logic compiler" software. Similar to the software compiler used in program development, the original code before compilation must also be written in a specific programming language, called a Hardware Description Language (HDL). There are many HDLs, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, and RHDL (Ruby Hardware Description Language). Currently, the most commonly used are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also understand that by simply performing some logic programming on the method flow using one of these hardware description languages ​​and programming it into an integrated circuit, the hardware circuit implementing the logical method flow can be easily obtained.

[0104] The controller can be implemented in any suitable manner. For example, it can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicon Labs C8051F320. A memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art will also recognize that, in addition to implementing the controller in purely computer-readable program code form, the same functionality can be achieved by logically programming the method steps to make the controller take the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the means included therein for implementing various functions can also be considered as structures within the hardware component. Alternatively, the means for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0105] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or physical entities, or by products with certain functions. A typical implementation device is a server system. Of course, this application does not exclude the possibility that, with the future development of computer technology, the computer implementing the functions of the above embodiments can be, for example, a personal computer, a laptop computer, an in-vehicle human-machine interaction device, a cellular phone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or any combination of these devices.

[0106] While one or more embodiments of this specification provide the operational steps of the methods described in the embodiments or flowcharts, more or fewer operational steps may be included based on conventional or non-inventive means. The order of steps listed in the embodiments is merely one possible order of execution among many steps and does not represent the only possible order. In actual device or end product execution, the methods shown in the embodiments or drawings may be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment, or even a distributed data processing environment). The terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, product, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, product, or apparatus. Without further limitations, the presence of other identical or equivalent elements in the process, method, product, or apparatus that includes the elements is not excluded. For example, the use of terms such as "first," "second," etc., is to denote names and does not indicate any particular order.

[0107] For ease of description, the above devices are described in terms of function, divided into various modules. Of course, when implementing one or more of these specifications, the functions of each module can be implemented in one or more software and / or hardware components, or a module that performs the same function can be implemented by a combination of multiple sub-modules or sub-units. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, indirect coupling or communication connection between devices or units, and may be electrical, mechanical, or other forms.

[0108] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in one or more blocks of the flowchart illustrations and / or one or more blocks of the block diagrams.

[0109] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means that implement the functions specified in one or more flowcharts and / or one or more block diagrams.

[0110] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, such that the instructions, which execute on the computer or other programmable apparatus, provide steps for implementing the functions specified in one or more flowcharts and / or one or more block diagrams.

[0111] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0112] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0113] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage, graphene storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0114] Those skilled in the art will understand that one or more embodiments of this specification can be provided as a method, system, or computer program product. Therefore, one or more embodiments of this specification may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, one or more embodiments of this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0115] One or more embodiments of this specification can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a particular task or implement a particular abstract data type. One or more embodiments of this specification can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0116] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, system embodiments are basically similar to method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. In the description of this specification, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this specification. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described can be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0117] The above description is merely an embodiment of one or more embodiments of this specification and is not intended to limit the scope of these embodiments. Various modifications and variations can be made to these embodiments by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this specification should be included within the scope of the claims.

Claims

1. A privacy-preserving physical resource authentication method, executed by a first device, wherein the first device deploys target circuit logic, including a computational circuit section and a generation algorithm section, the method comprising: Using the first private key of this party, a first commitment is generated for the original resource data of the physical resources held by the first device; The original resource data and the first commitment are input into the target circuit logic. The first commitment is verified by the computing circuit part, and the conclusion data corresponding to the original resource data is calculated. The zero-knowledge proof on the correctness of the calculation by the computing circuit part is generated by the generation algorithm part to obtain the first proof data. The conclusion data indicates the health status of the physical resource and is used for resource value assessment. The first commitment and the first proof data are stored in the second device for the second device to verify the zero-knowledge proof.

2. The method according to claim 1, wherein, The input to the target circuit logic also includes the first public key corresponding to the first private key; The verification of the first commitment includes: Using the first public key and the original resource data, a first calculated value is obtained; Determine whether the first calculated value and the first commitment are equal.

3. The method according to claim 1, wherein, The compilation result of the computing circuit part includes an executable bytecode file obtained by compiling the computing logic of the computing circuit part, and a description file for describing the constraint information of the computing circuit part. The step of verifying the first commitment through the computing circuit and calculating the conclusion data corresponding to the original resource data includes: Based on the original resource data and the first commitment, the bytecode file is run to generate several intermediate variables; The generation of zero-knowledge proofs regarding the correctness of calculations in the computational circuit section includes: Witness data is generated based on the values ​​of the aforementioned intermediate variables; The zero-knowledge proof is generated based on the witness data and the proof key; wherein the proof key is generated based on the description file.

4. The method according to claim 1, wherein, The first device includes the physical resource, or the first device is an edge device on the side of the physical resource; Before generating the first commitment, the following is also included: Collect the raw resource data of the physical resources within the target time period.

5. The method according to claim 1, wherein, The step of generating a first commitment for the original resource data of the physical resources held by the first device using the first private key includes: A first commitment is generated for the original resource data using the first private key through a preset Pedersen commitment algorithm.

6. The method according to claim 1, wherein, The second device is a blockchain network, in which a first smart contract is deployed for executing verification algorithm logic; The step of storing the first commitment and the first proof data in the second device includes: A first transaction is sent to the blockchain network, which invokes the storage interface of the first smart contract and includes the first commitment and the first proof data; so that the blockchain network stores the first commitment and the first proof data into the contract state of the first smart contract according to the first transaction.

7. The method according to claim 6, wherein, The blockchain network includes a main chain and a second-layer network, and the first smart contract is deployed in the second-layer network; Sending the first transaction to the blockchain network includes: Send the first transaction to the Layer 2 network.

8. The method according to claim 1, wherein, The second device is equipment from an authoritative certification body; The step of storing the first commitment and the first proof data in the second device includes: Send a data storage request containing the first commitment and the first proof data to the institution, so that the institution stores the first commitment and the first proof data accordingly.

9. The method according to claim 1, further comprising: The first commitment and the original resource data are stored on a third device of the local data service provider for the regulatory authority to verify the original resource data.

10. The method according to claim 9, wherein, The third device is a node in a trusted oracle network.

11. The method according to any one of claims 1-10, wherein, The physical resource is a power battery resource, the original resource data includes the battery capacity of the power battery resource within the target time period, and the conclusion data is the cumulative number of charge and discharge cycles of the power battery resource within the target time period.

12. The method according to claim 11, wherein, The original resource data also includes the battery voltage of the power battery resources within the target time period; The calculation of the conclusion data corresponding to the original resource data includes: For any two battery charges that are adjacent in time during the target time period, if the first difference between the charge of the latter battery and the charge of the former battery is greater than 0, and the second difference between the battery voltages corresponding to the charge of the latter battery and the charge of the former battery is greater than 0, then the cumulative charging amount of the power battery during the target time period is increased by the first difference. The cumulative number of charge / discharge cycles is determined based on the calculated cumulative charge amount and the preset power threshold.

13. A privacy-preserving physical resource authentication method, comprising: The first device uses its own first private key to generate a first commitment for the original resource data of the physical resources held by the first device; The first device is equipped with target circuit logic, including a computational circuit section and a generation algorithm section; The first device inputs at least the original resource data and the first commitment into the target circuit logic, verifies the first commitment through the computing circuit part, calculates the conclusion data corresponding to the original resource data, and generates a zero-knowledge proof on the correctness of the calculation by the computing circuit part through the generation algorithm part to obtain first proof data, wherein the conclusion data indicates the health status of the physical resource and is used for resource value assessment. The first device stores the first commitment and the first proof data in the second device accordingly; The second device verifies the zero-knowledge proof shown by the first proof data.

14. The method according to claim 13, wherein, The second device verifies the zero-knowledge proof shown by the first proof data, including: The second device responds to a resource assessment request sent by the fourth device by verifying the zero-knowledge proof shown by the first proof data; wherein, the resource assessment request includes data identifiers of a plurality of proof data corresponding to a plurality of physical resources; the plurality of proof data includes the first proof data; The method further includes: The second device, in response to the fact that all zero-knowledge proofs shown by the plurality of proof data have been verified, determines the resource value of the plurality of physical resources based on the conclusion data shown by the plurality of proof data.

15. The method according to claim 14, wherein, The determination of the resource value of the physical resources based on the conclusion data shown by the aforementioned evidence data includes: The sum of the conclusions shown by the aforementioned proof data is used as the evaluation reference data; Based on the assessment reference data, the total resource value of the aforementioned physical resources is determined.

16. The method according to claim 15, wherein, The physical resources are several power battery resources, the original resource data includes the battery capacity of the power battery resources within the target time period, and the conclusion data is the cumulative number of charge and discharge cycles of the power battery resources within the target time period. The determination of the total resource value of the plurality of physical resources based on the assessment reference data includes: The overall health of the battery is determined based on the aforementioned assessment reference data; The total resource value is determined based on the overall health of the battery.

17. The method of claim 14, wherein, The second device is a blockchain network, in which a first smart contract for executing verification algorithm logic is deployed; the resource evaluation request is a second transaction that calls the verification interface of the first smart contract, and the plurality of proof data are stored in the contract state of the first smart contract; The verification of the zero-knowledge proof shown by the first proof data includes: Based on the second transaction, the verification algorithm logic corresponding to the verification interface of the first smart contract is executed to verify the zero-knowledge proof shown by the first proof data.

18. The method according to claim 17, wherein, The blockchain network includes a main chain and a second-layer network. The first smart contract is deployed in the second-layer network, and a second smart contract is deployed in the main chain. Determining the resource value of the plurality of physical resources includes: The second-layer network sends the transaction certificate of the second transaction to the main chain, which includes evaluation reference data, the evaluation reference data being the sum of the conclusion data shown by the various proof data respectively; After the main chain verifies the authenticity of the second transaction based on the transaction certificate, it calls the second smart contract to determine the total resource value of the several physical resources based on the evaluation reference data.

19. The method according to claim 18, wherein, The step of calling the second smart contract to determine the total resource value of the plurality of physical resources based on the evaluation reference data includes: The main chain stores the transaction certificate and returns the verification result of the authenticity of the second transaction to the second-layer network; Upon receiving the verification result, the Layer 2 network returns the transaction certificate to the fourth device. The fourth device sends a third transaction to the main chain, which invokes the second smart contract and includes the transaction certificate; After the main chain verifies the transaction certificate in the third transaction, it calls the second smart contract to determine the total resource value of the several physical resources based on the evaluation reference data.

20. The method according to any one of claims 13-16, wherein, The second device is equipment from an authoritative certification body.

21. A privacy-preserving physical resource authentication device, applied to a first device, the first device having deployed target circuit logic, including a computational circuit section and a generation algorithm section, the device comprising: The generation unit is configured to use its own first private key to generate a first commitment for the original resource data of the physical resources held by the first device; The proof unit is configured to input at least the original resource data and the first commitment into the target circuit logic, verify the first commitment through the computing circuit part, calculate the conclusion data corresponding to the original resource data, and generate a zero-knowledge proof on the correctness of the calculation of the computing circuit part through the generation algorithm part to obtain first proof data, wherein the conclusion data indicates the health status of the physical resource for resource value assessment. The storage unit is configured to store the first commitment and the first proof data in a second device for the second device to verify the zero-knowledge proof.

22. A computer program product comprising a computer program / instructions that, when executed by a processor, implement the steps of the method according to any one of claims 1-12.

23. A computing device comprising a memory and a processor, wherein the memory stores executable code, and the processor, when executing the executable code, implements the method of any one of claims 1-12.

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