Air quality data management method, equipment and medium

Abstract

The invention belongs to the technical field of block chains, and particularly relates to an air quality data management method and device and a medium, and the method comprises the steps: combining a block chain technology with a linkable group signature mechanism, taking an ecological environment department node as a group administrator, and taking an air quality data collection node as a group member; and safety management and credible uplink of the air quality data in the whole process of acquisition, transmission and storage are realized. The data acquisition node performs group signature on the air quality data and uploads the air quality data on the premise of not exposing the real identity, so that the privacy of the data source node is protected, and a single-point device is prevented from being maliciously targeted; meanwhile, a link detection algorithm is introduced on the basis that group signature verification is passed and is used for identifying whether multiple signatures are from the same data acquisition node or not, so that Sybil attacks and malicious quantity swiping behaviors are effectively prevented, and extra calculation overhead caused by frequent opening of the group signatures is avoided.

Description

Technical Field

[0001] This application belongs to the field of blockchain technology, specifically relating to an air quality data management method, device, and medium. Background Technology

[0002] Ambient air safety has become an increasingly important social concern. For example, the concentrations of ozone, sulfides, nitrogen oxides, and inhalable particulate matter in the environment are crucial. If the ambient air quality index is detrimental to the health of residents or environmental workers, they should have the right to know and access ambient air data. Blockchain is a new application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms. Current technologies mainly use ring signatures to protect the privacy of submitters, but this leads to a lack of traceability: once data is incorrect or abnormal, the system cannot effectively locate the true submitter through the ring signature. There is also the risk of a signer falsely accusing a non-true signer, thus weakening the "traceability" advantage of blockchain and introducing security risks. At the same time, traditional group signatures cannot resist Sybil attacks in many application scenarios. External verifiers find it difficult to distinguish whether multiple signatures come from multiple identities of the same node, making it difficult to prevent duplicate reporting and data manipulation, affecting data authenticity and governance efficiency. Summary of the Invention

[0003] To address the aforementioned technical problems, this invention provides an air quality data management method, device, and medium. By using ecological and environmental department nodes as group administrators and air quality data collection nodes as group members, it achieves secure management and reliable on-chain storage of air quality data throughout the entire process of collection, transmission, and storage, thereby significantly improving the security, reliability, and regulatory feasibility of air quality data management. The technical solution is as follows: An air quality data management method includes the following steps: S1. Air Quality Monitoring Node Deployment and Key Initialization: In the air quality monitoring network, the ecological and environmental protection department node is used as the group administrator, and the blockchain trusted sensor and monitoring station node are used as data acquisition nodes; the public key of the ecological and environmental protection department node and the public key of the monitoring station node generated by the key distribution agency are used as their identity identifiers in the blockchain network. S2. Initialization of the Blockchain Network and Group Signature System: S3. Generation of group signatures for air quality data: The data acquisition nodes perform group signature on the collected air quality data to obtain the group signature result, and then send the group signature result and air quality data to the ecological and environmental protection department node. S4. Air Quality Data Cluster Signature Verification: The results of the group signature are verified by the nodes of the ecological and environmental protection department. Once the verification is successful, the air quality data is packaged into a block and broadcast to the blockchain network. S5. Air Quality Block Verification and Consensus: Monitoring station nodes in the blockchain network verify the blocks, and after successful verification, the blocks are stored in the blockchain ledger.

[0004] Preferably, the key distribution organization generates a unique public-private key pair for each node using the national cryptographic standard SM2, based on the device information of each blockchain trusted sensor node and monitoring station node; at the same time, it generates a unique public-private key pair for the ecological and environmental department node; the monitoring station node participates in the consensus process of the blockchain network, verifies new blocks, and acts as a group member.

[0005] Preferably, the initialization steps for the S2 blockchain network and group signature system are as follows: S2.1 Initialize the blockchain network: Write the public keys of each blockchain trusted sensor node, the public keys of the ecological and environmental protection department node, and the public keys of the monitoring station node into the genesis block and upload them to the chain; S2.2 Constructing the bilinear group and system parameters: Let G1 and G2 be prime numbers of order. p The generators of the two cyclic groups G1 are: The generators of G2 are , mapping For a mapping to be bilinear, it must satisfy the following conditions: However, isomorphic mappings exist. ,in ; S2.3 System Parameters and Group Public Key Generation: The ecological and environmental department node acts as the group administrator, generating group signature system parameters; the ecological and environmental department node generates a bilinear group. ; Choose the first hash function , Indicates less than The set of non-negative integers, the second hash function Determine the group public key And the group administrator's private key ; Among them, system parameters η1 and η2 are used to recover the true identity of the group member corresponding to the signature. , Indicates less than p The set of positive integers; system parameters 、 Used to generate signed commitments, system parameters Used to generate zero-knowledge proofs, the system parameter γ is used to publish the private keys of group members. ; , making G1* represents the set of non-negative numbers in the cyclic group G1; S2.4 Air Quality Data Acquisition Node Group Private Key Generation: For any air quality data acquisition node ID b The group administrator randomly selects and determines the G2 private key parameters for the circular group. And calculate the first group of private key parameters. Therefore, group member ID b The group private key can be represented as ; The group administrator will set up a triplet. Member list stored by the group administrator This is used to trace the true identity of nodes during the subsequent group signature opening phase.

[0006] Preferably, the group signature generation of air quality data in step S3 includes signature commitment generation, linkable parameter generation, zero-knowledge proof parameter generation, and response value calculation and group signature generation; Signature commitment generation: The air quality data collected by the air quality data acquisition node is m. A first random number is randomly selected using the data acquisition node. α Second random number β Calculate the first signature parameter, the second signature parameter, and the third signature parameter, specifically: ; ; ; In the formula, T 1 Indicates the first signature parameter. T 2 This represents the second signature parameter. T 3 This represents the third signature parameter. A b This represents the private key parameter of the cyclic group G1; Linkable parameter generation: The fourth signature parameter is calculated using the group private key of the data acquisition node, thus linking the parameters. Specifically: ; In the formula, t This represents the fourth signature parameter. H 2( ) represents the second hash function. m Indicates air quality data, Represents the private key parameters of the cyclic group G2; zero-knowledge proof parameter generation: the third random number is determined by randomly selecting air quality data acquisition nodes. Fourth random number Fifth random number The sixth random number and the seventh random number , Based on the system parameters, R1~R6 are calculated, and then the challenge value is calculated. c Specifically: ; ; ; ; ; ; ; Response value calculation and group signature generation: ; ; ; ; ; ; ; In the formula, This represents the sixth signature parameter. This represents the seventh signature parameter. This represents the eighth signature parameter. This represents the ninth signature parameter. This represents the tenth signature parameter. This represents the seventh calculated value. This represents the eighth calculated value; The final group signature result for generating air quality data: Air quality data and group signature results are sent to the ecological and environmental protection department node.

[0007] Preferably, step S4, the air quality data group signature verification step, is as follows: S4.1. Use the ecological and environmental department node to determine whether multiple group signature results for the same air quality data have been received. If not, verify the individual group signature result. If the verification is successful, proceed directly to S4.2.2. If so, verify the multiple group signature results and execute S4.2; The verification process is as follows: For each group of signature results, calculate the first verification value. Second verification value Third verification value , Fourth verification value Fifth verification value and the sixth verification value ,like If the result is true, the verification is considered successful; otherwise, the verification fails. S4.2 If the verification result is passed, then execute S4.2.1; S4.2.1. Use a link detection algorithm to determine whether multiple group signature results come from the same data collection node. If not, proceed to S4.2.2; if yes, proceed to S4.2.3, which specifically includes: S4.2.1.1 Obtain the fourth signature parameter from each group signature result. ; S4.2.1.2 Determine whether all of the fourth signature parameters are the same. If so, determine that the multiple group signature results come from the same data acquisition node. If not, determine that the multiple group signature results come from different data acquisition nodes.

[0008] Suppose there are two group signature results, one of which is... Another group signature result is If the fourth signature parameter t = t′ of the two group signature results, then the two group signature results are determined to come from the same data collection node; if they are not equal, then the two group signature results are determined to come from different data collection nodes. S4.2.2 Pack the air quality data into blocks and broadcast the blocks to the blockchain network; S4.2.3 Open the group signature result and restore the data acquisition node information corresponding to the group signature result.

[0009] Preferably, the air quality data is stored in a cache pool in chronological order, and it is determined whether the data in the cache pool has reached a preset value. If so, the air quality data in the cache pool is packaged into a block and the block is broadcast to the blockchain network.

[0010] Preferably, calculate the parameters to be searched. And using the ecological and environmental department node to search the list based on the parameter A to be searched. Search tuples ; Specifically, if A = A b Then return A. b Corresponding ID b This confirms the identity of the data collection node corresponding to the group signature result.

[0011] Preferably, the S5 air quality block verification, consensus and ledger storage: the monitoring station nodes in the blockchain network are used to verify the block, and if the verification result is successful, the block is stored in the blockchain ledger; The monitoring station nodes in the blockchain network verify the block. If the verification result is successful, the corresponding confirmation information is returned to the ecological and environmental department node, and the block is stored in the blockchain ledger. The ecological and environmental department node determines whether the number of monitoring station nodes returning the confirmation information exceeds two-thirds. If so, the consensus is considered to have ended. By introducing a multi-node verification and consensus mechanism in the blockchain network, air quality data protected by group signatures must be jointly verified by multiple air quality monitoring station nodes before being written into the blockchain ledger. At the same time, combined with the aforementioned linkable group signature and group signature opening mechanism, the traceability, auditability, and supervision of air quality data are achieved while ensuring the privacy of the identity of air quality data collection nodes.

[0012] A computing device includes: a memory and a processor; Memory, used to store program instructions; A processor is configured to invoke program instructions stored in the memory and execute the method described in this application according to the obtained program.

[0013] A computer storage medium storing computer-executable instructions for performing the methods described in this application.

[0014] Compared with the prior art, the beneficial effects of this application are as follows: By combining blockchain technology with a linkable group signature mechanism, this invention uses nodes from the environmental protection department as group administrators and air quality data collection nodes as group members, achieving secure management and trusted on-chain uploading of air quality data throughout the entire process of collection, transmission, and storage. Data collection nodes sign and upload air quality data without revealing their true identities, protecting the privacy of data source nodes and preventing malicious targeting of individual devices. When air quality data is abnormal or suspected of being falsified, the environmental protection department node can restore the identity of the true data upload node by opening the group signature, thus ensuring data traceability and regulatory oversight. Furthermore, this invention introduces a link detection algorithm based on successful group signature verification to identify whether multiple signatures originate from the same data collection node, effectively preventing Sybil attacks and malicious data manipulation, and avoiding the additional computational overhead of frequently opening the group signature. Building upon this, leveraging the blockchain's "once uploaded, it cannot be tampered with" characteristic, this invention achieves long-term trusted storage and auditing of air quality data, balancing anonymity, traceability, and system efficiency, thereby significantly improving the security, reliability, and regulatory feasibility of air quality data management. Attached Figure Description

[0015] Figure 1 This is a flowchart. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0017] S1. Air quality monitoring node deployment and key initialization: Based on the work plan and importance of urban grid-based air quality monitoring, authorized and certified blockchain-based trusted sensor devices are installed in urban roads, residential areas, industrial parks, areas around schools and hospitals, and transportation hubs. Monitoring station nodes are also deployed at several fixed monitoring stations (such as national control points, provincial control points, municipal control points, and park fixed monitoring stations).

[0018] The key distribution organization generates a unique public-private key pair for each blockchain trusted sensor node and monitoring station node using the national cryptographic standard SM2, based on the device information (including manufacturer name, device model, device serial number SN, device MAC address, etc.). Simultaneously, a unique public-private key pair is generated for the ecological and environmental department nodes. The public keys generated by the key distribution organization for the ecological and environmental department nodes and the monitoring station nodes serve as their respective identity identifiers within the blockchain network.

[0019] S2 Blockchain Network and Group Signature System Initialization: S2.1 Initialize the Blockchain Network Write the public keys of each blockchain trusted sensor node, the public keys of the ecological and environmental protection department node, and the public keys of the monitoring station node into the genesis block and upload them to the chain for subsequent identity verification and traceability.

[0020] S2.2 Constructing the bilinear group and system parameters Let G1 and G2 be cyclic groups of order p, and let the generator of G1 be... The generators of G2 are , mapping It is a bilinear mapping that satisfies bilinearity, non-degeneracy, and computability. In this invention, the bilinear mapping must satisfy the following conditions: However, isomorphic mappings exist. ,in ; S2.3 System Parameters and Group Public Key Generation (Ecological and Environmental Department Node as Group Administrator Generates Group Signature System Parameters) The ecological and environmental department node acts as the group administrator, generating group signature system parameters; the ecological and environmental department node generates a bilinear group. ; Choose the first hash function , Indicates less than The set of non-negative integers, the second hash function Determine the group public key And the group administrator's private key ; Among them, system parameters η1 and η2 are used to recover the true identity of the group member corresponding to the signature. , Indicates less than p The set of positive integers; system parameters 、 Used to generate signed commitments, system parameters Used to generate zero-knowledge proofs, the system parameter γ is used to publish the private keys of group members. ; ; , making G1* represents the set of nonnegative numbers in the cyclic group G1.

[0021] S2.4 Air Quality Data Acquisition Node Group Private Key Generation: For any air quality data acquisition node ID b The group administrator randomly selects and determines the G2 private key parameters for the circular group. And calculate the first group of private key parameters. Therefore, group member ID b The group private key can be represented as The group administrator will set up the triplet. Member list stored by the group administrator In this context, it is used to trace the true identity of nodes during the subsequent group signature opening phase (when opening the group signature later, it is only necessary to compare the calculated A with the A in the list). b By comparing the data, the true identity of the node can be determined.

[0022] Group signature generation for S3 air quality data: After system initialization is completed, the collected air quality data is group-signed using the data acquisition nodes to obtain the group signature result.

[0023] S3.1 Signature Commitment Generation: The air quality data collected by the air quality data acquisition node is m. A first random number is randomly selected using the data acquisition node. α Second random number β Based on system parameters, the first random number, the second random number, and the group private key of the data acquisition node, the first signature parameter, the second signature parameter, and the third signature parameter are calculated, specifically: ; ; ; In the formula, T 1 Indicates the first signature parameter. T 2 This represents the second signature parameter. T 3 This represents the third signature parameter. A b This represents the private key parameter of the cyclic group G1; S3.2 Linkable Parameter Generation: The fourth signature parameter (a linkable parameter) is calculated using the group private key of the data acquisition node. Specifically: ; In the formula, t represents the fourth signature parameter. H 2 ( ) represents the second hash function, and m represents the air quality data. This represents the second group of private key parameters. S3.3 Zero-knowledge proof parameter generation: The air quality data acquisition node randomly selects and determines the third random number. Fourth random number Fifth random number The sixth random number and the seventh random number , Based on the system parameters, intermediate values ​​R1 to R6 are calculated, and then the challenge value is calculated. c Specifically: ; ; ; ; ; ; ; In the formula, H 1 ( ) represents the first hash function, R1 represents the first calculated value, R2 represents the second calculated value, R3 represents the third calculated value, R4 represents the fourth calculated value, R5 represents the fifth calculated value, and R6 represents the sixth calculated value.

[0024] S3.4 Response Value Calculation and Group Signature Generation: The response parameters are calculated as follows: ; ; ; ; ; ; ; In the formula, s α This represents the sixth signature parameter, s. β This represents the seventh signature parameter, s x This represents the eighth signature parameter, s δ1 This represents the ninth signature parameter, s δ2 δ1 represents the tenth signature parameter, δ2 represents the seventh calculated value, and δ2 represents the eighth calculated value. The final group signature result for generating air quality data: The air quality data and group signature results will be sent to the ecological and environmental protection department node.

[0025] S4. Air quality data group signature verification, link detection, and accountability methods: S4.1 Group Signature Verification (Data acquisition nodes include blockchain trusted sensor nodes and monitoring station nodes. After collecting air quality data, group members can all group-sign the water system data and then send the signed group signature results to the ecological and environmental department node. Therefore, the ecological and environmental department node may receive multiple group signature results for the same water system data. To avoid Sybil attacks, even if the group signature result verification is successful, a link detection algorithm is needed to determine whether multiple group signature results come from the same data acquisition node. If they are from the same signer, it means that the current signer may be a malicious node impersonating someone else, hence sending multiple signatures to simulate multiple virtual identities. At this time, it is necessary to restore the signer's information and check the signer's real identity. This avoids Sybil attacks and also avoids the waste of computing power caused by opening the group signature every time, thereby further improving the security of water system data.) After receiving the air quality data and the corresponding group signature, the ecological and environmental department node verifies each group signature result. If the verification is successful, the air quality data is packaged into a block and broadcast to the blockchain network. Specifically, this includes: S4.1. Use the ecological and environmental department node to determine whether multiple group signature results for the same air quality data have been received. If not, verify the individual group signature result. If the verification is successful, proceed directly to S4.2.2. If so, verify the multiple group signature results and execute S4.2; Specifically, the verification includes: For each group of signature results, calculate the first verification value. Second verification value Third verification value , Fourth verification value Fifth verification value and the sixth verification value ,like If the result is true, the verification is successful; otherwise, the verification fails.

[0026] S4.2 If the verification result is passed, then execute S4.2.1; S4.2.1 Use a link detection algorithm to determine whether multiple group signature results come from the same data collection node (if they all come from the same node, it indicates that they may be under a Sybil attack). If not, proceed to S4.2.2; if yes, proceed to S4.2.3, which specifically includes: S4.2.1.1 Obtain the fourth signature parameter t in each of the group signature results; S4.2.1.2 Determine whether all of the fourth signature parameters are the same. If so, determine that the multiple group signature results come from the same data acquisition node. If not, determine that the multiple group signature results come from different data acquisition nodes.

[0027] Suppose there are two group signature results, one of which is... Another group signature result is If the fourth signature parameter of the two group signature results t=t′ If the two group signature results are equal, it is determined that they come from the same data collection node; if they are not equal, it is determined that they come from different data collection nodes.

[0028] S4.2.2 Pack the air quality data into blocks and broadcast the blocks to the blockchain network; In one optional implementation, the air quality data is stored in a cache pool in chronological order, and it is determined whether the data in the cache pool has reached a preset value. If so, the air quality data in the cache pool is packaged into a block and the block is broadcast to the blockchain network.

[0029] S4.2.3 Open the group signature result and restore the data acquisition node information corresponding to the group signature result; In one alternative implementation, the parameters to be searched are calculated. And using the ecological and environmental department node to search the list based on the parameter A to be searched. Search tuples ; Specifically, if A = A b Then return A. b Corresponding ID b This confirms the identity of the data collection node corresponding to the group signature result.

[0030] S5. Air quality block verification, consensus and ledger storage: The monitoring station nodes in the blockchain network are used to verify the block. If the verification result is successful, the block is stored in the blockchain ledger.

[0031] Specifically, the monitoring station nodes in the blockchain network verify the block. If the verification result is successful, the corresponding confirmation information is returned to the ecological and environmental department node, and the block is stored in the blockchain ledger. The ecological and environmental department node determines whether the number of monitoring station nodes returning the confirmation information exceeds two-thirds. If so, the consensus is considered to have ended.

[0032] By introducing a multi-node verification and consensus mechanism in the blockchain network, air quality data protected by group signatures must be jointly verified by multiple air quality monitoring station nodes before being written into the blockchain ledger. This prevents the risk of malicious behavior or misjudgment by a single node at the system level. At the same time, combined with the aforementioned linkable group signature and group signature opening mechanism, the traceability, auditability, and supervision of air quality data are achieved while ensuring the privacy of the identities of air quality data collection nodes.

[0033] In some possible implementations, the computing device according to this application may include at least one processor and at least one memory. The memory stores a computer program that, when executed by the processor, causes the processor to perform the steps of the air quality data management method according to the various exemplary embodiments of this application described above.

[0034] In some possible implementations, various aspects of the terminal location information processing method provided in this application can also be implemented in the form of a program product, which includes a computer program. When the program product is run on a computer device, the computer program is used to cause the computer device to perform the steps in the air quality data management method according to the various exemplary embodiments of this application described above.

[0035] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0036] The program product for parameter processing according to the embodiments of this application can be a portable compact disc read-only memory (CD-ROM) and include a computer program, and can run on a computing device. However, the program product of this application is not limited thereto. In this document, the readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0037] A readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying a readable computer program. Such propagated data signals may take various forms, including—but not limited to—electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of sending, propagating, or transmitting a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0038] The computer program contained on the readable medium can be transmitted using any suitable medium, including—but not limited to—wireless, wired, optical fiber, RF, etc., or any suitable combination thereof. The computer program for performing the operations of this application can be written in any combination of one or more programming languages, including object-oriented programming languages—such as Java, C++, etc.—and conventional procedural programming languages—such as the "C" language or similar programming languages. The computer program can be executed entirely on the target computing device, partially on the target device, as a standalone software package, partially on the target computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device can be connected to the target computing device via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0039] It should be noted that although several units or sub-units of the device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of this application, the features and functions of two or more units described above can be embodied in one unit. Conversely, the features and functions of one unit described above can be further divided and embodied by multiple units.

[0040] Furthermore, although the operations of the method of this application are described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0041] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can 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-ROMs, optical storage, etc.) containing computer-usable computer programs.

[0042] The computer program instructions used may also be loaded onto a computer or other programmable data processing equipment, causing a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0043] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0044] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. An air quality data management method, characterized in that, Includes the following steps: S1. Air Quality Monitoring Node Deployment and Key Initialization: In the air quality monitoring network, the ecological and environmental protection department node is used as the group administrator, and the blockchain trusted sensor and monitoring station node are used as data acquisition nodes; the public key of the ecological and environmental protection department node and the public key of the monitoring station node generated by the key distribution agency are used as their identity identifiers in the blockchain network. S2. Initialization of the Blockchain Network and Group Signature System: S3. Generation of group signatures for air quality data: The data acquisition nodes perform group signature on the collected air quality data to obtain the group signature result, and then send the group signature result and air quality data to the ecological and environmental protection department node. S4. Air Quality Data Cluster Signature Verification: The results of the group signature are verified by the nodes of the ecological and environmental protection department. Once the verification is successful, the air quality data is packaged into a block and broadcast to the blockchain network. S5. Air Quality Block Verification and Consensus: Monitoring station nodes in the blockchain network verify the blocks, and after successful verification, the blocks are stored in the blockchain ledger.

2. The air quality data management method according to claim 1, characterized in that, The key distribution organization generates a unique public-private key pair for each node based on the device information of each blockchain trusted sensor node and monitoring station node, using the national cryptographic standard SM2; at the same time, it generates a unique public-private key pair for the ecological and environmental protection department node; the monitoring station node participates in the consensus process of the blockchain network, verifies new blocks, and acts as a group member.

3. The air quality data management method according to claim 1, characterized in that, The initialization steps for the S2 blockchain network and group signature system are as follows: S2.1 Initialize the blockchain network: Write the public keys of each blockchain trusted sensor node, the public keys of the ecological and environmental protection department node, and the public keys of the monitoring station node into the genesis block and upload them to the chain; S2.2 Constructing the bilinear group and system parameters: Let G1 and G2 be prime numbers of order. p The generators of the two cyclic groups G1 are: The generators of G2 are , mapping For a mapping to be bilinear, it must satisfy the following conditions: However, isomorphic mappings exist. ,in ; S2.3 System Parameters and Group Public Key Generation: The ecological and environmental department node acts as the group administrator, generating group signature system parameters; the ecological and environmental department node generates a bilinear group. ; Choose the first hash function , Indicates less than The set of non-negative integers, the second hash function Determine the group public key And the group administrator's private key ; Among them, system parameters System parameters η1 and η2 are used to recover the true identity of the group member corresponding to the signature. , Indicates less than p The set of positive integers; system parameters 、 Used to generate signed commitments, system parameters Used to generate zero-knowledge proofs, the system parameter γ is used to publish the private keys of group members. ; , making G1* represents the set of non-negative numbers in the cyclic group G1; S2.4 Air Quality Data Acquisition Node Group Private Key Generation: For any air quality data acquisition node ID b The group administrator randomly selects and determines the G2 private key parameters for the circular group. And calculate the first group of private key parameters. Therefore, group member ID b The group private key can be represented as ; The group administrator will set up triplet Member list stored by the group administrator This is used to trace the true identity of nodes during the subsequent group signature opening phase.

4. The air quality data management method according to claim 1, characterized in that, Step S3, the generation of group signatures for air quality data, includes signature commitment generation, linkable parameter generation, zero-knowledge proof parameter generation, and response value calculation and group signature generation. Signature commitment generation: The air quality data collected by the air quality data acquisition node is m. A first random number is randomly selected using the data acquisition node. α Second random number β Calculate the first signature parameter, the second signature parameter, and the third signature parameter, specifically: ； ； ； In the formula, T 1 Indicates the first signature parameter. T 2 This represents the second signature parameter. T 3 This represents the third signature parameter. A b This represents the private key parameter of the cyclic group G1; Linkable parameter generation: The fourth signature parameter is calculated using the group private key of the data acquisition node, thus linking the parameters. Specifically: ; In the formula, t This represents the fourth signature parameter. H 2 ( ) represents the second hash function. m Indicates air quality data, This represents the private key parameter of the cyclic group G2; Zero-knowledge proof parameter generation: The third random number is determined by randomly selecting air quality data acquisition nodes. Fourth random number Fifth random number The sixth random number and the seventh random number , Based on the system parameters, R1~R6 are calculated, and then the challenge value is calculated. c Specifically: ； ； ； ； ； ； ； Response value calculation and group signature generation: ; ； ； ； ； ； ； In the formula, This represents the sixth signature parameter. This represents the seventh signature parameter. This represents the eighth signature parameter. This represents the ninth signature parameter. This represents the tenth signature parameter. This represents the seventh calculated value. This represents the eighth calculated value; The final group signature result for generating air quality data: ； Air quality data and group signature results are sent to the ecological and environmental protection department node.

5. The air quality data management method according to claim 4, characterized in that, Step S4, the air quality data group signature verification steps, are as follows: S4.

1. Use the ecological and environmental department node to determine whether multiple group signature results for the same air quality data have been received. If not, verify the individual group signature result. If the verification is successful, proceed directly to S4.2.

2. If so, verify the multiple group signature results and execute S4.2; The verification process is as follows: For each group of signature results, calculate the first verification value. Second verification value Third verification value , Fourth verification value Fifth verification value and the sixth verification value ,like If the result is true, the verification is considered successful; otherwise, the verification fails. S4.2 If the verification result is passed, then execute S4.2.1; S4.2.

1. Use a link detection algorithm to determine whether multiple group signature results come from the same data collection node. If not, proceed to S4.2.2; if yes, proceed to S4.2.3, which specifically includes: S4.2.1.1 Obtain the fourth signature parameter from each group signature result. ; S4.2.1.2 Determine whether all of the fourth signature parameters are the same. If so, determine that the multiple group signature results come from the same data acquisition node; otherwise, determine that the multiple group signature results come from different data acquisition nodes. Suppose there are two group signature results, one of which is... Another group signature result is If the fourth signature parameter t = t′ of the two group signature results, then the two group signature results are determined to come from the same data collection node; if they are not equal, then the two group signature results are determined to come from different data collection nodes. S4.2.2 Pack the air quality data into blocks and broadcast the blocks to the blockchain network; S4.2.3 Open the group signature result and restore the data acquisition node information corresponding to the group signature result.

6. The air quality data management method according to claim 4, characterized in that, The air quality data is stored in a cache pool in chronological order. It is then determined whether the data in the cache pool has reached a preset value. If so, the air quality data in the cache pool is packaged into a block and broadcast to the blockchain network.

7. The air quality data management method according to claim 4, characterized in that, Calculate the parameters to be searched And using the ecological and environmental department node to search the list based on the parameter A to be searched. Search tuples ; Specifically, if A = A b Then return A. b Corresponding ID b This confirms the identity of the data collection node corresponding to the group signature result.

8. The air quality data management method according to claim 1, characterized in that, S5 Air Quality Block Verification, Consensus and Ledger Storage: The monitoring station nodes in the blockchain network are used to verify the block. If the verification result is successful, the block is stored in the blockchain ledger. The monitoring station nodes in the blockchain network verify the block. If the verification result is successful, the corresponding confirmation information is returned to the ecological and environmental department node, and the block is stored in the blockchain ledger. The ecological and environmental department node determines whether the number of monitoring station nodes returning the confirmation information exceeds two-thirds. If so, the consensus is considered to have ended. By introducing a multi-node verification and consensus mechanism in the blockchain network, air quality data protected by group signatures must be jointly verified by multiple air quality monitoring station nodes before being written into the blockchain ledger. At the same time, combined with the aforementioned linkable group signature and group signature opening mechanism, the traceability, auditability, and supervision of air quality data are achieved while ensuring the privacy of the identity of air quality data collection nodes.

9. A computing device, characterized in that, include: Memory and processor; Memory, used to store program instructions; A processor is configured to invoke program instructions stored in the memory and execute the method according to any one of claims 1-8.

10. A computer storage medium storing computer-executable instructions, characterized in that, The computer-executable instructions are used to perform the method as described in any one of claims 1-8.

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