Cross-chain transaction-based smart contract collaboration method, system, device and medium

Abstract

The present application relates to the technical field of cross-chain transaction, in particular to a smart contract cooperation method, system, device and medium based on cross-chain transaction. It comprises the following steps: S1, initiating cross-chain transaction on the source chain, triggering the qualification review contract, node management contract and verification cooperation contract set on the source chain; S2, the qualification review contract extracts the qualification data of the initiator and the receiver according to the initiated cross-chain transaction, and the transaction value of the cross-chain transaction, carries out risk quantitative analysis on the cross-chain transaction according to the qualification data and the transaction value, and determines the risk value according to the analysis result; by constructing a multi-dimensional risk quantitative evaluation system, the problem of insufficient risk assessment accuracy is effectively solved, the qualification data of the transaction initiator and the receiver and the transaction value are deeply integrated, a multi-dimensional quantitative model with dynamic weight distribution is used to calculate the comprehensive risk value, and the cross-chain transaction risk is finely described.

Description

Technical Field

[0001] This invention relates to the field of cross-chain transaction technology, and more specifically, to a method, system, device, and medium for smart contract collaboration based on cross-chain transactions. Background Technology

[0002] With its decentralized and immutable characteristics, blockchain technology has been widely used in finance, digital assets and other fields. As the core means to realize the exchange of value between different blockchain networks, the security and efficiency of cross-chain transactions directly determine the interoperability of the blockchain ecosystem.

[0003] Existing smart contract collaboration technologies for cross-chain transactions still have significant shortcomings, making it difficult to balance transaction security and execution efficiency. Current technologies mostly focus only on the legality of the transaction assets or the technical security of the cross-chain bridge, ignoring the differences in qualifications between the transaction initiator and receiver and the inherent risk characteristics of the transaction value itself. This results in insufficient accuracy in risk assessment and fails to provide a scientific basis for subsequent verification processes. Secondly, existing technologies mostly use a fixed number of verification nodes to perform verification tasks, without dynamically adjusting the number and professional capabilities of nodes according to the transaction risk level. This leads to insufficient verification resources for high-risk transactions and redundant verification resources for low-risk transactions. Furthermore, the lack of an effective validity judgment mechanism for node screening, and the existence of some zombie nodes or malicious nodes, further reduces the credibility of the verification results.

[0004] In view of this, the present invention provides a method, system, device and medium for smart contract collaboration based on cross-chain transactions. Summary of the Invention

[0005] The purpose of this invention is to provide a smart contract collaboration method, system, device, and medium based on cross-chain transactions to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention aims to provide a smart contract collaboration method based on cross-chain transactions, comprising the following steps:

[0007] S1. Initiate a cross-chain transaction on the source chain, triggering the qualification review contract, node management contract, and verification collaboration contract set on the source chain;

[0008] S2, Qualification Review Contract: Extracts qualification data of the initiator and receiver, as well as the transaction value of the cross-chain transaction, based on the initiated cross-chain transaction. Performs risk quantification analysis on the cross-chain transaction based on the qualification data and transaction value, and determines the risk value based on the analysis results.

[0009] S3, Node Management Contract: Establish a node resource pool, randomly select verification nodes from the node resource pool based on risk values ​​to form a verification node group, and conduct simulation verification effect analysis and verification characteristic determination based on the historical verification results and verification objects of the verification node group.

[0010] S4. Based on the verification effect and verification characteristics, set the verification weight and reorganize the nodes in the verification node group. Then, input the transaction value and qualification data according to the verification characteristics of the nodes to obtain the security score output by each node.

[0011] S5. Verify the collaborative contract and determine the verification result of the cross-chain transaction by comprehensively verifying the security score output by the node group. If the verification result is passed, the cross-chain transaction is executed.

[0012] As a further improvement to this technical solution, in S1, a smart contract is set in the blockchain and the smart contract is used to monitor the transaction dynamics. When a user initiates a cross-chain transaction in the blockchain, the smart contract is triggered to manage the transaction initiator and receiver.

[0013] Smart contracts include qualification review contracts, node management contracts, verification and collaboration contracts, and transaction monitoring functions.

[0014] As a further improvement to this technical solution, in step S2, the qualification review contract response S1 is triggered, and the steps are as follows:

[0015] S2.1 Extract the initiator's address and the recipient's address from the initiated cross-chain transaction, and determine the transaction value corresponding to this cross-chain transaction.

[0016] S2.2 Obtain the initiator's qualification data based on the initiator's address;

[0017] Based on the recipient's address, obtain the recipient's qualification data;

[0018] Qualification data includes historical transaction records, asset pledge status, and address risk information;

[0019] S2.3. Combine the acquired qualification data with the transaction value, use multi-dimensional quantitative methods to conduct a risk assessment of the cross-chain transaction, and output the risk value of this cross-chain transaction based on the assessment results.

[0020] S2.3.1 Normalize the qualification data and transaction value simultaneously to obtain a standardized evaluation value. Then, perform hierarchical analysis on the historical transaction records and the transaction security information contained in the transaction records, and dynamically determine the weight coefficient of the standardized evaluation value based on the analysis results.

[0021] S2.3.2 Calculate the comprehensive risk value by weighting and summing the standardized assessment values ​​with weighting coefficients.

[0022] As a further improvement to this technical solution, in step S3, the node management contract responds to the triggering of S1, and the steps are as follows:

[0023] S3.1. Pre-register multiple verification nodes to form a node resource pool, then receive the risk value determined by the qualification review contract, and randomly select verification nodes from the resource nodes according to the risk value to form a verification node group;

[0024] The higher the risk value, the more nodes the verification node group contains;

[0025] The lower the risk value, the fewer nodes the verification node group contains;

[0026] S3.2. Combine risk values ​​to generate a simulated verification dataset similar to the current cross-chain transactions, and set a benchmark standard answer for the verification data of the simulated verification dataset;

[0027] S3.3 Input the simulated verification dataset into the nodes of the verification node group, and obtain the simulated verification results output by each node for the simulated verification data. Combine the simulated verification results of the nodes with the benchmark standard answer for evaluation, and determine the effect score of each node based on the evaluation results.

[0028] S3.4. Set an effect threshold based on the risk value, and compare the effect score of the node with the effect threshold. If the effect score of the node is lower than the effect threshold, the node is deleted from the verification node group and re-selected from the node resource pool. Conversely, if the effect score of the node is higher than the effect threshold, it is retained.

[0029] S3.5 Obtain the node's registration information and historical verification records, and determine the node's verification characteristics based on the registration information and historical verification records.

[0030] As a further improvement to this technical solution, step S4 is as follows:

[0031] S4.1 Based on the effect score obtained in S3.3, set the verification weight for the nodes in the verification node group; the higher the effect score, the higher the verification weight set.

[0032] S4.2 Analyze the verification data contained in this cross-chain exchange and determine the verification characteristics corresponding to the verification data. Then, combine the verification characteristics corresponding to the verification data with the verification characteristics obtained in S3.5 to perform verification characteristic coverage analysis. If the analysis results show that the verification characteristics obtained in S3.5 are not covered, then extract nodes from the node resource pool according to the missing verification characteristics, thereby reorganizing and updating the verification node group.

[0033] Among them, the reorganization and update of the verification node group involves extracting nodes from the node resource pool and adding nodes to the verification node group;

[0034] S4.3 Based on the verification characteristics of the nodes in the verification node group, relevant data related to the node verification characteristics are extracted from the transaction value and qualification data as input. Each node independently conducts risk assessment based on the relevant data, and then each node outputs a corresponding security score.

[0035] As a further improvement to this technical solution, in step S5, the steps for verifying the triggering of the collaborative contract response S1 are as follows:

[0036] S5.1 Summarize the security scores output by each node in S4.3, and then use the consensus algorithm to combine the security scores of all nodes to determine the verification result of this cross-chain transaction;

[0037] S5.2 If the verification result is successful, the cross-chain bridging mechanism set in the blockchain will be triggered to execute the cross-chain transaction. Conversely, if the verification result is unsuccessful, the cross-chain transaction will be terminated and the relevant funds will be returned to the initiator.

[0038] The second objective of this invention is to provide a smart contract collaboration system based on cross-chain transactions, including any one of the smart contract collaboration methods based on cross-chain transactions described above, comprising a transaction monitoring module, a qualification review module, a node management module, and a verification collaboration module.

[0039] The transaction monitoring module initiates cross-chain transactions on the source chain, triggering the qualification review contract, node management contract, and verification collaboration contract set on the source chain;

[0040] The qualification review module extracts the qualification data of the initiator and the recipient, as well as the transaction value of the cross-chain transaction, based on the initiated cross-chain transaction. It then performs a risk quantification analysis of the cross-chain transaction based on the qualification data and transaction value, and determines the risk value based on the analysis results.

[0041] The node management module establishes a node resource pool, randomly selects verification nodes from the node resource pool based on risk values ​​to form a verification node group, and performs simulated verification effect analysis and verification characteristic determination based on the historical verification results and verification objects of the verification node group. Based on the verification effect and verification characteristics, the verification weight is set and the nodes are reorganized for the verification node group. Then, the transaction value and qualification data are input according to the verification characteristics of the nodes to obtain the security score output by each node.

[0042] The verification collaboration module is used to determine the verification result of cross-chain transactions by comprehensively verifying the security scores output by the node group. If the verification result is passed, the cross-chain transaction is executed.

[0043] The third objective of this invention is to provide a smart contract collaboration device based on cross-chain transactions, including any one of the smart contract collaboration methods based on cross-chain transactions described above, including a first smart contract interface, a second smart contract, a third smart contract, and a fourth smart contract.

[0044] The first smart contract interface is used to receive cross-chain transaction requests triggered by the transaction initiator;

[0045] The second smart contract is used to assess the risk of cross-chain transaction requests;

[0046] The third smart contract is used to dynamically configure verification nodes based on the risk value;

[0047] The fourth smart contract is used to process and make decisions based on the feedback from the verification nodes.

[0048] The fourth objective of this invention is to disclose a readable storage medium, including a memory storing execution instructions, wherein when a processor executes the execution instructions stored in the memory, the processor hardware executes the smart contract collaboration method based on cross-chain transactions as described in the first aspect.

[0049] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0050] By constructing a multi-dimensional risk quantification assessment system, the problem of insufficient accuracy in risk assessment is effectively solved. The system deeply integrates the qualification data of the transaction initiator and receiver with the transaction value, and uses a multi-dimensional quantification model with dynamic weight allocation to calculate the comprehensive risk value. This achieves a refined characterization of cross-chain transaction risks and provides a scientific basis for the dynamic configuration of subsequent verification nodes. It avoids risk misjudgment or omission caused by single-dimensional assessment. Through innovative node screening, validity verification, and feature adaptation mechanisms, the quality and efficiency of cross-chain transaction verification are significantly improved. Furthermore, through full-process smart contract collaboration and weighted consensus mechanisms, the system achieves dual protection of cross-chain transaction security and fairness. Attached Figure Description

[0051] Figure 1 This is a flowchart illustrating the overall process of the smart contract collaboration method based on cross-chain transactions according to the present invention.

[0052] Figure 2 This is a flowchart illustrating the process of extracting the initiator's address and the recipient's address in a cross-chain transaction according to the present invention.

[0053] Figure 3 This is a flowchart illustrating the process of pre-registering multiple verification nodes according to the present invention.

[0054] Figure 4 This is a flowchart illustrating the process of analyzing the verification data included in this cross-chain transaction.

[0055] Figure 5 This is a flowchart illustrating the process by which the present invention determines the verification result of this cross-chain transaction.

[0056] Figure 6 This is a schematic diagram of the structural principle of the present invention. Detailed Implementation

[0057] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0058] Please see Figure 1 - Figure 6 As shown, one of the objectives of this invention is to provide a smart contract collaboration method based on cross-chain transactions, comprising the following steps:

[0059] S1. Initiate a cross-chain transaction on the source chain, triggering the qualification review contract, node management contract, and verification collaboration contract set on the source chain;

[0060] In S1, smart contracts are set up in the blockchain and used to monitor transaction dynamics. When a user initiates a cross-chain transaction in the blockchain, the smart contract is triggered to manage the transaction initiator and receiver.

[0061] Smart contracts include qualification review contracts, node management contracts, verification and collaboration contracts, and transaction monitoring functions (continuously monitoring all transaction events on the source chain).

[0062] When a transaction is detected, it is first filtered to determine whether it is a legitimate cross-chain transaction request. This includes verifying the validity of the transaction signature, checking whether the transaction calls the preset cross-chain entry contract, and verifying the integrity of the transaction format and parameters.

[0063] Once a legitimate cross-chain transaction request is confirmed, a pre-defined collaborative process is immediately triggered, activating the qualification review contract, node management contract, and verification collaboration contract simultaneously or sequentially, and passing key cross-chain transaction information (such as initiator address, recipient address, transaction value, target chain information, etc.) as parameters to these contracts.

[0064] S2, Qualification Review Contract: Extracts qualification data of the initiator and receiver, as well as the transaction value of the cross-chain transaction, based on the initiated cross-chain transaction. Performs risk quantification analysis on the cross-chain transaction based on the qualification data and transaction value, and determines the risk value based on the analysis results.

[0065] In S2, the qualification review contract response S1 is triggered, and the steps are as follows:

[0066] S2.1 Extract the initiator address (the blockchain account address of the user initiating the transaction) and the receiver address (the blockchain account address of the user receiving the transaction or the contract) from the initiated cross-chain transaction, and determine the transaction value corresponding to this cross-chain transaction.

[0067] S2.2 Obtain the initiator's qualification data based on the initiator's address;

[0068] The smart contract obtains the qualification data of the extracted initiator address through a preset data interface (such as on-chain ledger query or decentralized oracle).

[0069] Based on the recipient's address, obtain the recipient's qualification data;

[0070] Similarly, the smart contract obtains the qualification data of the recipient's address.

[0071] Qualification data includes historical transaction records (including transaction frequency and compliance rate), asset pledge status (pledge amount and pledge duration), and address risk status (blacklist association and number of malicious transactions).

[0072] S2.3. Combine the acquired qualification data with the transaction value, use multi-dimensional quantitative methods to conduct a risk assessment of the cross-chain transaction, and output the risk value of this cross-chain transaction based on the assessment results.

[0073] S2.3.1 Normalize the qualification data and transaction value (cross-chain transaction amount, asset volatility) simultaneously to obtain a standardized evaluation value;

[0074] For indicators where "the larger the value, the higher the risk" (such as location risk and asset volatility), positive normalization is used;

[0075] Inverse normalization is used for indicators where "the larger the value, the lower the risk" (such as the amount of asset pledge and the transaction compliance rate).

[0076] Ensure that all standardized assessment values ​​reflect the risk in the same direction (i.e., the higher the value, the higher the risk);

[0077] Then, a hierarchical analysis is performed on historical transaction records and the transaction security information contained within those records. Based on the analysis results, the weighting coefficients of the standardized evaluation values ​​are dynamically determined. The steps are as follows:

[0078] First, a hierarchical structure is constructed, consisting of a target layer (cross-chain transaction risk assessment) → a criteria layer (historical transaction records, asset staking status, address risk status, and transaction value) → a solution layer (specific indicators). Then, the administrator compares the relative importance of each indicator in the criteria layer pairwise, using a 1-9 scale (1 = equally important, 9 = extremely important) to generate a judgment matrix. Simultaneously, the consistency index CI and random consistency ratio CR of the judgment matrix are calculated. If CR < 0.1, the matrix meets the consistency requirements; otherwise, the administrator's score is adjusted. Finally, the eigenvector corresponding to the largest eigenvalue of the judgment matrix is ​​solved using the eigenvalue method. After normalization, the dynamic weight coefficients of each standardized evaluation value are obtained (the sum of the weights is 1).

[0079] S2.3.2. The comprehensive risk value is calculated by combining the standardized evaluation value with the weight coefficient and summing them. The comprehensive risk value of cross-chain transactions is obtained by multiplying the standardized evaluation value of each indicator with the corresponding weight coefficient and summing them. The value range is [0,1] (the closer to 1, the higher the risk).

[0080] S3, Node Management Contract: Establish a node resource pool, randomly select verification nodes from the node resource pool based on risk values ​​to form a verification node group, and conduct simulation verification effect analysis and verification characteristic determination based on the historical verification results and verification objects of the verification node group.

[0081] In S3, the node management contract responds to the S1 trigger, following these steps:

[0082] S3.1 Pre-register multiple verification nodes. The registration steps are as follows:

[0083] Nodes are required to submit identity and qualification certificates, pledge a preset amount of platform tokens (for default penalties), and deploy compliant verification algorithms (such as security audit tools and risk assessment models). At the same time, smart contracts automatically verify the locked status of pledged assets and the compliance of the verification algorithms. Nodes that pass the review are entered into the node resource pool, thus forming the node resource pool.

[0084] Then, it receives the risk value determined by the qualification review contract, and randomly selects verification nodes from the resource nodes based on the risk value to form a verification node group; among them, a blockchain native secure random number generator is used, such as a random algorithm based on block hash combined with nonce, to randomly select a target number of nodes from the effective node subset to form a verification node group.

[0085] The higher the risk value, the more nodes the verification node group contains, and more nodes are needed to participate in the verification to improve the credibility of the results.

[0086] The lower the risk value, the fewer nodes the verification node group contains, which can reduce the number of nodes to optimize efficiency;

[0087] S3.2. Combine risk values ​​to generate a simulated verification dataset similar to the current cross-chain transactions, and set a benchmark standard answer for the verification data of the simulated verification dataset;

[0088] Based on risk values ​​and transaction characteristics, three types of simulated data are generated (covering normal, abnormal, and edge scenarios), as follows:

[0089] In normal scenarios, simulated transactions that comply with security rules (such as transfers to legitimate addresses, sufficient balance, and no vulnerabilities in the contract);

[0090] Abnormal scenarios, including simulated transactions with risk points (such as receiving from blacklisted addresses, contract reentrancy vulnerabilities, invalid signatures).

[0091] In edge scenarios, simulated transactions at critical security thresholds (such as large-amount, low-frequency transfers and high-frequency interactions between associated addresses).

[0092] For each piece of simulated data, based on a preset security rule base (such as address blacklists and whitelists, contract vulnerability databases, and transaction compliance rules), the baseline standard answer for passing or rejecting is automatically marked;

[0093] Ensure that the sample distribution of the simulated dataset matches the current transaction risk; the higher the risk value, the higher the proportion of samples from abnormal and edge scenarios.

[0094] S3.3 Input the simulated verification dataset into the nodes of the verification node group, and obtain the simulated verification result output by each node for the simulated verification data. Evaluate the simulated verification results of the nodes in conjunction with the benchmark standard answer, and determine the effect score of each node based on the evaluation results. The steps are as follows:

[0095] The node management contract sends the simulated verification dataset in batches to each node in the verification node group through an encrypted channel. Then, each node runs its own verification algorithm independently and outputs a pass or rejection result for each simulated data, ensuring that there is no data interaction between nodes (to avoid collusion). At the same time, the node is required to return the result within a preset time window (5 seconds). If the result is not returned within the time limit, it is considered an "invalid result" and is directly included in the evaluation deduction item.

[0096] The simulation verification results of each node are compared with the benchmark standard answer one by one, and the core evaluation indicators (accuracy, precision, recall) are statistically analyzed. The harmonic mean of precision and recall is used as the final performance score of the node.

[0097] S3.4. Set an effect threshold based on the risk value (the higher the risk, the stricter the threshold). Compare the effect score of the node with the effect threshold. If the effect score of the node is lower than the effect threshold, the node will be removed from the verification node group and re-selected from the node resource pool. Conversely, if the effect score of the node is higher than the effect threshold, it will be retained.

[0098] S3.5 Obtain the node's registration information and historical verification records. Determine the node's verification characteristics based on the registration information and historical verification records. The specific steps are as follows:

[0099] Predefine the core verification feature dimensions for cross-chain blockchain transaction scenarios (covering mainstream verification needs) to ensure unified judgment standards. The dimensions include identity compliance verification, contract security verification, behavior pattern analysis, and asset security verification.

[0100] Then, extract the information submitted during node pre-registration from the node resource pool, and extract the node's past verification data from the blockchain ledger or contract storage to calculate the matching degree of declared characteristics; the degree of matching between the node's declared verification characteristics and each preset dimension, and simultaneously calculate the actual performance adaptability; the weighted comprehensive value of the task proportion, verification accuracy, and response speed of each characteristic dimension in the node's historical processing tasks.

[0101] For each feature dimension, calculate the node's "feature adaptation comprehensive score" (combining registration declaration and historical performance to avoid bias from a single data point), sort the nodes in descending order of comprehensive score, and the dimension with the highest score is the node's core verification feature, as shown in the formula below:

[0102] ;

[0103] Where D2 represents the actual performance fit of a certain feature dimension, w1 represents the task proportion weight, and T r w2 is the proportion of tasks in this dimension to the total historical tasks of the node, w3 is the weight of the verification accuracy, A is the average verification accuracy of tasks in this dimension, and S is the normalized value of the average response speed of tasks in this dimension.

[0104] ;

[0105] Among them, S c The score represents the overall score for a certain feature dimension, where D1 is the matching degree of the declared feature for that dimension, C is the credibility of the registration declaration (based on the capability proof review results during node registration), α is the weight of the registration declaration, and β is the weight of the actual performance.

[0106] S4. Based on the verification effect and verification characteristics, set the verification weight and reorganize the nodes in the verification node group. Then, input the transaction value and qualification data according to the verification characteristics of the nodes to obtain the security score output by each node.

[0107] The steps for S4 are as follows:

[0108] S4.1 Based on the effect score obtained in S3.3, set the verification weight for the nodes in the verification node group; the higher the effect score, the higher the verification weight set.

[0109] A score normalization method is used to set the verification weight of each node, ensuring that the sum of the weights is 1 and that the score is positively correlated with the weight. The weight value of each node is recorded and synchronized to the verification collaboration contract for subsequent comprehensive calculation of the security score. The formula is as follows:

[0110] ;

[0111] Among them, W i Let F1 be the validation weight of the i-th node. i Let n be the score for the simulation verification effect of the i-th node, and n be the total number of nodes in the current verification node group.

[0112] S4.2 Analyze the verification data contained in this cross-chain exchange and determine the verification characteristics corresponding to the verification data. Then, combine the verification characteristics corresponding to the verification data with the verification characteristics obtained in S3.5 to perform verification characteristic coverage analysis. If the analysis results show that the verification characteristics obtained in S3.5 are not covered, then extract nodes from the node resource pool according to the missing verification characteristics, thereby reorganizing and updating the verification node group.

[0113] The process of reorganizing and updating the verification node group involves extracting nodes from the node resource pool and adding nodes to the verification node group. The steps are as follows:

[0114] The core verification data of the current cross-chain transaction is broken down (such as the initiator / receiver address, transaction value, target chain contract information, and asset type). Based on the data type, the target verification characteristics required for the transaction are determined (i.e., the characteristic dimensions that must be covered to complete the security verification of the transaction). Then, a list of target verification characteristics is compiled.

[0115] Extract the verification features of each node in S3.5, summarize the covered feature set of the current verification node group, compare the target verification feature list with the covered feature set, calculate the coverage, and when the coverage is less than 1, identify the uncovered missing features (e.g., the target feature contains "behavioral pattern analysis", but the current node group does not have a node with this feature).

[0116] For missing features, nodes that meet the following conditions are selected from the node resource pool: the verification feature includes the missing feature, the simulation verification effect score is greater than or equal to the effect threshold corresponding to the current transaction risk (same as the threshold standard of S3.5), and the node is not included in the current verification node group (to avoid duplication).

[0117] Based on the number of missing features, select a corresponding number of nodes and add them to the original verification node group to complete the reorganization and update. At the same time, set verification weights for the selected nodes step by step, as shown in the following formula:

[0118] ;

[0119] Where Coverage is the verification feature coverage, T is the target verification feature set for cross-chain transactions, C is the covered feature set of the current node group, Num(T∩C) is the number of intersections between the target feature and the covered features, and Num(T) is the total number of target verification features.

[0120] ;

[0121] Among them, Supplement m Ratio is the number of replacement nodes for the m-th missing characteristic, and Num(T) is the redundancy coefficient. m ) represents the number of missing features in the m-th class. This is a rounding function (ensuring at least one node is selected to avoid insufficient coverage).

[0122] S4.3. Based on the verification characteristics of the nodes in the verification node group, relevant data related to the node verification characteristics are extracted from the transaction value and qualification data as input. Each node independently conducts a risk assessment based on the relevant data, and then each node outputs a corresponding security score. The steps are as follows:

[0123] For each reorganized node, its verification characteristics are extracted. Data fragments strongly related to these characteristics are extracted from transaction value and qualification data (irrelevant data is not input to avoid interference). Then, the targeted data is sent to the corresponding node through an independent encrypted channel (one channel for each node) to ensure data isolation.

[0124] Each node runs its own risk assessment algorithm (such as a rule engine or machine learning model) based on the received targeted data, independently determines the risk, and outputs a standardized security score. At the same time, the node is required to return the security score to the verification collaboration contract in encryption within a preset time window (such as 5 seconds). If the score is not returned within the time limit, it is considered an invalid score (weight is reduced to zero).

[0125] S5. Verify the collaborative contract and determine the verification result of the cross-chain transaction by comprehensively verifying the security score output by the node group. If the verification result is passed, the cross-chain transaction is executed.

[0126] In S5, the steps to verify the collaborative contract response triggered by S1 are as follows:

[0127] S5.1 Summarize the security scores output by each node in S4.3, and then use the consensus algorithm to combine the security scores of all nodes to determine the verification result of this cross-chain transaction;

[0128] The security score is verified by validating the score signature (node ​​private key signature, contract public key verification) to prevent score tampering. Then, a weighted average consensus algorithm (combining node weights to reflect the decision priority of high-capability nodes, best practice) is used to calculate the final comprehensive security score for cross-chain transactions and output the final comprehensive security score.

[0129] S5.2 When the verification result is passed, the cross-chain bridging mechanism set in the blockchain is triggered to execute the cross-chain transaction; in this process, the cross-chain transaction assets of the initiator are locked (through the asset locking contract), the transaction instructions are synchronized to the target chain through the encrypted channel, and after the cross-chain bridging contract receives the instructions, the corresponding assets are released to the recipient's address to complete the transaction.

[0130] Conversely, if the verification result is unsuccessful, the cross-chain transaction will be terminated and the relevant funds will be returned to the initiator. Specifically, asset locking will be rejected to ensure that the initiator's funds have not been transferred, a transaction failure notification will be generated, and feedback will be sent to the initiator's address via a smart contract.

[0131] The second objective of this invention is to provide a smart contract collaboration system based on cross-chain transactions, including any of the above-mentioned smart contract collaboration methods based on cross-chain transactions, including a transaction monitoring module, a qualification review module, a node management module, and a verification collaboration module.

[0132] Initiating a cross-chain transaction on the source chain triggers the qualification review contract, node management contract, and verification collaboration contract set on the source chain;

[0133] The qualification review module extracts the qualification data of the initiator and the recipient, as well as the transaction value of the cross-chain transaction, based on the initiated cross-chain transaction. It then performs a risk quantification analysis of the cross-chain transaction based on the qualification data and transaction value, and determines the risk value based on the analysis results.

[0134] The node management module establishes a node resource pool, randomly selects verification nodes from the node resource pool based on risk values ​​to form a verification node group, and performs simulated verification effect analysis and verification characteristic determination based on the historical verification results and verification objects of the verification node group. Based on the verification effect and verification characteristics, the verification weight is set and the nodes are reorganized for the verification node group. Then, transaction value and qualification data are input according to the verification characteristics of the nodes to obtain the security score output by each node.

[0135] The verification collaboration module is used to determine the verification result of cross-chain transactions by comprehensively verifying the security scores output by the node group. If the verification result is passed, the cross-chain transaction is executed.

[0136] The third objective of this invention is to provide a smart contract collaboration device based on cross-chain transactions, including any one of the above-mentioned smart contract collaboration methods based on cross-chain transactions, including a first smart contract interface, a second smart contract, a third smart contract, and a fourth smart contract.

[0137] The first smart contract interface is used to receive cross-chain transaction requests triggered by the transaction initiator;

[0138] The second smart contract is used to assess the risk of cross-chain transaction requests;

[0139] The third smart contract is used to dynamically configure verification nodes based on risk values;

[0140] The fourth smart contract is used to process and make decisions based on the feedback from the verification nodes.

[0141] To this end, embodiments of this application also provide a storage medium storing a plurality of instructions that can be loaded by a processor to execute the steps in the low-power control method provided in embodiments of this application.

[0142] Optionally, the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0143] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A cross-chain transaction-based smart contract collaboration method, characterized in that: Comprise the following steps: S1, initiate cross-chain transaction on the source chain, trigger the qualification review contract, node management contract, verification coordination contract set in the source chain; S2, the qualification review contract, according to the initiated cross-chain transaction, extract the qualification data of the initiator and the receiver, and the transaction value of cross-chain transaction, according to the qualification data and transaction value, risk quantitative analysis is carried out on cross-chain transaction, and the risk value is determined according to the analysis result; S3, the node management contract, establish node resource pool, according to the risk value, randomly select the verification node in the node resource pool, form the verification node group, and according to the historical verification result of the verification node group, the simulation verification effect analysis is carried out on the verification node, and the verification characteristic dimension of the verification node is determined; The verification characteristic dimension is the dimension that can cover the mainstream verification demand under the cross-chain transaction scene; S4, according to the verification effect, the verification weight of the verification node group is set, and the node recombination of the verification node group is carried out according to the verification characteristic dimension, then the transaction value and the qualification data are inputted according to the verification characteristic of the verification node, so as to obtain the security score output by each verification node; The node recombination includes: determining the verification characteristic dimension that must be covered in the completion of the current transaction security verification, summarizing the covered verification characteristic dimension set of the current verification node group, comparing the two, when the missing verification characteristic dimension is found, the verification node meeting the condition is selected from the node resource pool and added to the verification node group; S5, the verification coordination contract, the verification result of cross-chain transaction is determined by comprehensively analyzing the security score output by the verification node group, and when the verification result is passed, the cross-chain transaction is executed. 2.The cross-chain transaction-based smart contract collaboration method of claim 1, wherein: In the S1, the smart contract is set in the block chain, and the transaction is monitored by using the smart contract, when the cross-chain transaction is initiated by the user in the block chain, the smart contract management transaction initiator and receiver are triggered; The smart contract includes qualification review contract, node management contract, verification coordination contract and transaction monitoring function. 3.The cross-chain transaction-based smart contract collaboration method of claim 1, wherein: In the S2, the qualification review contract is triggered in response to S1, and the steps are as follows: S2.1, the initiator address and receiver address are extracted in the initiated cross-chain transaction, and the transaction value corresponding to this cross-chain transaction is determined; S2.2, according to the initiator address, the qualification data of the initiator is obtained; According to the receiver address, the qualification data of the receiver is obtained; The qualification data includes historical transaction record, asset pledge situation, address risk situation; S2.3, the qualification data and transaction value are combined to evaluate the risk of cross-chain transaction by using multi-dimensional quantitative method, and the risk value of this cross-chain transaction is output according to the evaluation result; S2.3.1, the qualification data and transaction value are normalized to obtain the standard evaluation value, then the hierarchical analysis of historical transaction record and transaction record is carried out, and the weight coefficient of standard evaluation value is determined according to the analysis result; S2.3.2, the standard evaluation value is combined with the weight coefficient to carry out weighted summation, so as to calculate the comprehensive risk value. 4.The cross-chain transaction-based smart contract collaboration method of claim 1, wherein: In the S3, the node management contract is triggered in response to S1, and the steps are as follows: S3.1, pre-register a plurality of verification nodes to form a node resource pool, then receive a risk value determined by a qualification review contract, and randomly select verification nodes from the resource nodes according to the risk value to form a verification node group; The higher the risk value, the more nodes the verification node group contains; The lower the risk value, the fewer nodes the verification node group contains; S3.2, generate a simulated verification data set similar to the current cross-chain transaction in combination with the risk value, and set a benchmark standard answer for the verification data of the simulated verification data set; S3.3, input the simulated verification data set into the nodes of the verification node group, and obtain the simulated verification results output by each node for the simulated verification data, evaluate the simulated verification results of the nodes in combination with the benchmark standard answer, and determine the effect score of each node according to the evaluation result; S3.4, set an effect threshold according to the risk value, compare the effect score of the node with the effect threshold, when the effect score of the node is lower than the effect threshold, delete the node from the verification node group, and reselect from the node resource pool, otherwise, when the effect score of the node is higher than the effect threshold, keep it; S3.5, obtain the registration information and historical verification record of the node, and determine the verification characteristics of the node according to the registration information and historical verification record. 5.The cross-chain transaction-based smart contract collaboration method of claim 4, wherein: The steps of S4 are as follows: S4.1, according to the effect score obtained in S3.3, set the verification weight of the nodes in the verification node group; wherein the higher the effect score, the higher the set verification weight; S4.2, analyze the verification data contained in this cross-chain transaction, and determine the verification characteristics corresponding to the verification data, then perform verification characteristic coverage analysis on the verification characteristics corresponding to the verification data in combination with the verification characteristics obtained in S3.5, when the analysis result shows that the verification characteristics obtained in S3.5 are not covered, extract nodes from the node resource pool according to the missing verification characteristics to reorganize and update the verification node group; Wherein, reorganize and update the verification node group, extract nodes from the node resource pool to increase the nodes in the verification node group; S4.3, according to the verification characteristics of the nodes in the verification node group, extract the data related to the verification characteristics of the nodes as input from the transaction value and qualification data, and each node independently performs risk assessment according to the related data, and then each node outputs a security score. 6.The cross-chain transaction-based smart contract collaboration method of claim 5, wherein: In S5, the verification collaboration contract responds to S1 trigger, and the steps are as follows: S5.1, aggregate the security scores output by each node in S4.3, then integrate the security scores of all nodes by consensus algorithm to determine the verification result of this cross-chain transaction; S5.2, when the verification result is passed, trigger the cross-chain bridging mechanism set in the blockchain to execute the cross-chain transaction, otherwise, when the verification result is not passed, terminate this cross-chain transaction and return the related funds to the initiator.

7. A cross-chain transaction-based smart contract coordination system for performing the cross-chain transaction-based smart contract coordination method according to any one of claims 1-6, characterized in that: It includes a transaction monitoring module, a qualification review module, a node management module and a verification collaboration module; The qualification review contract, the node management contract and the verification collaboration contract are triggered and set in the source chain when the cross-chain transaction is initiated in the source chain; The qualification examination module extracts qualification data of the initiator and the receiver according to the initiated cross-chain transaction, and extracts the transaction value of the cross-chain transaction, performs risk quantitative analysis on the cross-chain transaction according to the qualification data and the transaction value, and determines a risk value according to an analysis result; The node management module establishes a node resource pool, randomly selects a verification node in the node resource pool according to the risk value, forms a verification node group, and performs simulation verification effect analysis and verification characteristic determination according to a historical verification result of the verification node group and a verification object, sets a verification weight of the verification node group and recombines the nodes according to the verification effect and the verification characteristic, then inputs relevant data according to the verification characteristic of the nodes, so as to obtain a security score output by each node; The verification cooperation module is used for determining a verification result of the cross-chain transaction according to the security score output by the verification node group, and executing the cross-chain transaction when the verification result is passed.

8. A cross-chain transaction based smart contract collaboration device for performing the cross-chain transaction based smart contract collaboration method according to any one of claims 1-6, characterized in that: The first smart contract interface, the second smart contract, the third smart contract and the fourth smart contract are included. The first smart contract interface is used for receiving a cross-chain transaction request triggered by a transaction initiator. The second smart contract is used for performing risk assessment on the cross-chain transaction request. The third smart contract is used for dynamically configuring a verification node according to the risk value. The fourth smart contract is used for processing feedback of the verification node and making a decision. 9.A readable storage medium comprising a memory storing execution instructions, when a processor executes the execution instructions stored in the memory, the processor executes the cross-chain transaction-based smart contract cooperation method in any one of claims 1-6.

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