A key management method based on blockchain

Abstract

The present invention relates to the field of data processing technology, and specifically to a key management method based on blockchain, comprising: obtaining key data within the current time period, and processing parameters of multiple dimensions thereof, by calculating the weights of the parameters of each dimension, combining the storage cost and request cost of the key data, evaluating the request cost and storage cost of each key data, the storage cost is calculated based on parameter deviation and weight, and the request cost is used to measure the stability of the key data; by comprehensively calculating the storage cost and the request cost, the management burden of the key data is obtained; if the management burden of the key data is lower than a set threshold, the key data is selected as the target data; the target data is stored on the blockchain and managed through a smart contract. The present invention solves the problem of excessive burden when storing key data of the blockchain.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology. More specifically, the present invention relates to a key management method based on blockchain. Background Art

[0002] With the continuous development of information technology, especially with the increasing application of blockchain technology, the issue of key management has become increasingly important. As the basis of encryption technology, keys are used in many fields such as protecting digital assets, identity authentication, and privacy protection. In blockchain networks, key management is not only a key factor in ensuring transaction security and avoiding data tampering, but also the basis for improving system efficiency and ensuring data privacy. However, with the popularization of blockchain technology, the complexity of key management has gradually increased. Especially in large-scale systems, how to manage keys efficiently and securely has become a bottleneck in the development of technology.

[0003] In blockchain, the core issue of key management is not only the generation, distribution and storage of keys, but also how to effectively implement on-chain and off-chain storage of keys. On-chain storage means recording key data directly on the blockchain. Although this can ensure the immutability and high transparency of data, as the scale of blockchain networks grows, the cost and performance issues of on-chain storage have become increasingly apparent. Blockchain networks usually need to process a large amount of transaction data. When key data is stored on the blockchain as part of transaction data, it may cause an overload of on-chain storage, thereby affecting the overall performance of the system, and may even lead to excessively high storage and access costs, limiting the scalability of blockchain technology in large-scale applications.

[0004] The patent application document with application publication number CN110932855A discloses a quantum key distribution method based on blockchain. The patent application document uses the public quantum channel interconnection to call the quantum key distribution QKD protocol to generate a key stream, solving the problem that the existing quantum key distribution scheme is difficult to meet the needs of multiple users for applying for key pairs, and the problem of low key distribution efficiency in the existing quantum key distribution scheme.

[0005] However, although the above technical solution improves the efficiency of key distribution by adopting a specific algorithm, the technical solution mainly focuses on optimization at the algorithm level, ignores the differences in applicability of different algorithms in actual application environments, and does not fully consider the differences in applicability of different algorithms in actual applications, resulting in the problem of excessive burden when storing the key data of the blockchain. Summary of the invention

[0006] In order to solve the problem of excessive burden when storing the key data of the blockchain proposed in the above background technology, the present invention provides the following solution.

[0007] The present invention provides a key management method based on blockchain, comprising: obtaining each key data of the blockchain in the current time period, wherein the key data includes parameter data of multiple dimensions; calculating the first The weight of the dimension parameter , , where is the normalization function, For the The key data The value of the dimension parameter, is the total number of dimension parameters, is the total number of key data; calculate the The storage cost of key data and request cost , , where For all key data The request cost is the average of the dimension parameter values. The values ​​of each dimension parameter in the key data and the weights of each dimension parameter are negatively correlated, and positively correlated with the total number of each dimension parameter; calculate the The management burden of key data , , To preset hyperparameters, the key data in response to the management burden being less than a set threshold is taken as target data, and the target data is stored on-chain.

[0008] The above technical solution dynamically calculates storage costs, request costs and management burdens, and introduces flexible weighting strategies to optimize the storage and request of key data in different scenarios. By setting thresholds to filter target data and store it on the chain, the security and immutability of key data on the blockchain are ensured, providing more accurate resource allocation and optimization strategies, and solving the problem of excessive burden when storing key data on the blockchain.

[0009] Furthermore, the request cost , , where is the normalization function, For the The key data The value of the dimension parameter, For all key data The mean of the dimension parameter values, For the The weight of the dimension parameters, is the total number of dimension parameters.

[0010] The above technical solution comprehensively evaluates the resource consumption of key data during the request process by combining the deviation and weight of each dimension parameter. By normalizing the relative difference between each dimension parameter and its mean and combining it with the corresponding weight, it can more accurately measure the processing cost required for each key data when requesting. This method can not only effectively reflect the request efficiency of key data in actual applications, but also avoid unnecessary calculation and resource waste, which helps to optimize key management strategies and request scheduling.

[0011] Furthermore, the request cost , , where is the normalization function, For the The key data The value of the dimension parameter, For all key data The standard deviation of the dimension parameter values, For the The weight of the dimension parameters, is the total number of dimension parameters.

[0012] The above technical solution evaluates the processing load of key requests based on the relative difference of the standard deviation of the parameters in each dimension. Compared with the above method, the standard deviation is used as an indicator to measure the volatility of data distribution, so that this solution can more accurately capture the fluctuation range of key data in different dimensions, and optimize the calculation of request cost by combining the weights of each dimension. Through this method, the actual computational complexity of key data in the request process can be more effectively reflected, ensuring a reasonable evaluation of the request cost of highly volatile key data, thereby optimizing resource allocation and improving the efficiency of request processing.

[0013] Furthermore, when the storage cost Request cost When the absolute value of the ratio is greater than 1, ; When storage cost Request cost When the absolute value of the ratio is less than 1, , where is the normalization function, The average cost of all key data requests.

[0014] The above technical solution automatically optimizes the calculation of management burden for different storage and request cost ratios by dynamically adjusting the weighting coefficient. When the storage cost is significantly higher than the request cost, the weighting coefficient is directly adjusted through the proportional relationship to ensure that the storage burden has a more prominent impact on the management strategy; and when the request cost is higher than the storage cost, the Sigmoid function is used for further smoothing adjustments to ensure that the calculation of management burden takes into account the difference between storage and request, and can be appropriately corrected according to the overall level of request cost. This flexible adjustment mechanism can adaptively optimize resource allocation according to actual conditions, ensuring that the system can effectively balance the storage and request burdens when processing different types of key data, improving overall management efficiency and system responsiveness, and reducing resource waste.

[0015] Furthermore, the multiple dimensional parameter data include: the size of the key data, the usage frequency of the key data and the encryption strength of the key data.

[0016] Furthermore, it also includes: using a smart contract mechanism to manage the storage of target data in the blockchain.

[0017] The above technical solution manages the storage of target data in the blockchain by using the smart contract mechanism, thus achieving automation and transparency of the storage process. Smart contracts can automatically perform data storage, access control and verification operations according to preset rules to ensure the security, integrity and immutability of data. By storing data on the blockchain, the credibility and traceability of the data are further enhanced, and any changes to the data will be automatically recorded and verified, avoiding the risk of human intervention or malicious tampering. At the same time, the introduction of smart contracts reduces the need for manual management, improves the efficiency of system operation, and reduces the possibility of operational errors.

[0018] Furthermore, it also includes standardizing the key data.

[0019] Furthermore, the set threshold is 0.6.

[0020] Furthermore, the preset hyperparameter is 0.5.

[0021] Furthermore, the normalization function is maximum-minimum normalization.

[0022] The beneficial effects of the present invention are:

[0023] The present invention realizes efficient and automated key management by combining the calculation of multi-dimensional key data with blockchain technology. By dynamically calculating storage cost, request cost and management burden, and introducing flexible weighting strategies, the storage and request of key data can be reasonably optimized in different scenarios. By setting thresholds to screen target data and storing it on-chain, the security and non-tamperability of key data on the blockchain are ensured. At the same time, the smart contract mechanism is used to further improve the degree of automation of management and reduce manual intervention. The present invention not only improves the efficiency and security of key data management, but also provides more accurate resource allocation and optimization strategies, especially in large-scale key data management and processing scenarios, which can significantly improve the performance, stability and responsiveness of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a flowchart schematically illustrating a blockchain-based key management method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0025] The specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0026] An embodiment of a key management method based on blockchain.

[0027] like Figure 1 As shown, a flowchart of a key management method based on blockchain in an embodiment of the present invention includes the following steps:

[0028] S1: Get the key data of the blockchain in the current time period.

[0029] In one embodiment, the key data includes a plurality of key attributes, which are used to comprehensively evaluate the performance and security of the key. Specifically, the composition of the key data includes: the size of the key data, the usage frequency of the key data, and the encryption strength of the key data.

[0030] Size of key data: The length of a key directly affects its security and computational complexity. Longer keys generally mean higher security, as the computational time required for brute force cracking increases exponentially. Therefore, the size of a key is an important indicator for evaluating its security and performance.

[0031] Frequency of use of key data: The frequency of use of a key refers to the number of times the key is actually used within a certain period of time. Keys with higher frequency of use may face greater risks, because long-term and frequent use of the same key may expose it to potential attack threats. Therefore, the frequency of use of a key is a key factor in evaluating whether it needs to be replaced or updated.

[0032] Encryption strength of key data: Encryption strength is a measure of the key's ability to resist attacks during the encryption process. Encryption strength is usually closely related to the complexity of the key, the type of encryption algorithm, and the way the key is generated. Keys with high encryption strength can effectively resist various attack methods, such as brute force cracking and known plaintext attacks.

[0033] In order to ensure that the comprehensive performance of the key data is optimal, this embodiment performs standardization on the above-mentioned key data. The purpose of standardization is to eliminate the dimensional differences between the various attributes so that the various data can be compared and analyzed under a unified scale. Through standardization, the performance of different key data in actual use can be more accurately evaluated, and priority ranking or other subsequent operations can be performed on them, such as key update, optimization of encryption strategy, etc.

[0034] S2: Calculate the storage cost and request cost of each key data.

[0035] In one embodiment, the calculation The storage cost of key data , , where For all key data The mean of the parameter values ​​of each dimension. By calculating the storage cost of each key data, the deviation and corresponding weight of each dimension parameter are comprehensively considered, so as to effectively evaluate the storage demand of the key data. Through normalization and weighted calculation, the storage differences of each key data in each dimension can be quantified, and these differences can be combined with their corresponding weights to ensure that the calculation of storage cost is more accurate and reasonable. This method can provide more accurate storage cost evaluation in key management, help optimize the storage strategy and resource allocation of key data, thereby improving storage efficiency and reducing unnecessary storage overhead. At the same time, considering the mean and difference of each dimension, it can also better reflect the concentration trend and dispersion of key data, and further enhance the overall performance of the system.

[0036] Among them, The weight of the dimension parameter , , where is the normalization function, For the The key data The value of the dimension parameter, is the total number of dimension parameters, is the total number of key data; normalizing the weights of the parameters of each dimension can effectively balance the influence of different dimensional parameters in the key data. Specifically, by calculating the relative proportion of each dimensional parameter in all key data and normalizing it, the weight of each dimension can be obtained. This method ensures that each dimension of the key data is reasonably weighted during the evaluation process, which helps to improve the accuracy of the comprehensive evaluation of the key data and avoid certain dimensions from excessively affecting the final result. Through this optimization, the system can analyze and screen the key data more scientifically, thereby improving the accuracy of key management and encryption strength evaluation, and enhancing the security and efficiency of the system.

[0037] The request cost , , where is the normalization function, For the The key data The value of the dimension parameter, For all key data The mean of the dimension parameter values, For the The weight of the dimension parameters, is the total number of dimension parameters. By normalizing the relative differences between each dimension parameter and its mean in each key data, and combining the weights of each dimension to measure the processing cost required in the request process, the contribution and influence of each dimension parameter in different scenarios can be carefully reflected, so that when requesting key data, its computing and storage requirements can be accurately evaluated. At the same time, the introduction of weight factors can more flexibly adjust resource allocation to adapt to the request characteristics and storage requirements of different key data, avoiding the waste of resources caused by a single standardized method. Compared with traditional methods, this request cost evaluation method that combines deviation, weight and normalization more accurately reflects the request efficiency and resource utilization efficiency of key data in actual applications.

[0038] In another embodiment, the request cost , , where is a normalization function. Exemplarily, the normalization function may be a maximum-minimum normalization. For the The key data The value of the dimension parameter, For all key data The standard deviation of the dimension parameter values, For the The weight of the dimension parameters, is the total number of dimension parameters. By calculating the request cost of key data, the processing load during key request is evaluated based on the relative difference of the standard deviation of each dimension parameter. Compared with the traditional mean-based deviation method, the standard deviation is used as an indicator to measure the volatility of data distribution, so that the scheme can more accurately capture the volatility and change range of key data in different dimensions. The standard deviation reflects the degree of dispersion of data points around the mean, and this information is crucial for evaluating the computational load that may be generated during the request process. By introducing the standard deviation into the calculation of the request cost, the dynamic changes of key data can be more comprehensively evaluated, especially for key data with large fluctuations, which can provide more targeted load estimates.

[0039] S3: Calculates management burden based on storage cost and request cost.

[0040] In one embodiment, the calculation The management burden of key data , , The preset hyperparameter is 0.5, which can be set according to the actual situation. For the The storage cost of key data, For the The solution calculates the request cost of key data by weighted combination of storage cost and request cost, thus providing a more comprehensive evaluation of key management. By introducing an adjustable hyperparameter, the solution can flexibly balance the impact of storage and request costs, so that the calculation of management burden takes into account both the resource consumption required for key storage and the processing overhead brought by the key during the request process. This method can optimize resource allocation strategies according to the needs of different scenarios, improve the management efficiency of the system, and provide a quantitative basis for the optimized storage and request scheduling of keys, which helps to reduce the overall system burden and improve performance and response speed.

[0041] Furthermore, when the storage cost Request cost When the absolute value of the ratio is greater than 1, ; When storage cost Request cost When the absolute value of the ratio is less than 1, , where is the normalization function, is the average of the request costs of all key data. By dynamically adjusting the weighting coefficient, when the storage cost is significantly higher than the request cost, the weighting coefficient is adjusted directly according to the proportional relationship between the storage and request costs to ensure that the storage burden occupies a larger weight in the management strategy, thereby highlighting the impact of storage costs on system management. This ratio-based adjustment mechanism can accurately capture the difference between storage and requests. When the storage burden is heavy, it optimizes the allocation of resources, avoids over-reliance on request costs, ensures that resources are mainly concentrated on storage management, and avoids possible storage bottlenecks. When the request cost is higher than the storage cost, the Sigmoid function is used to smoothly adjust the weighting coefficient to ensure that the calculation of the management burden is not only based on the simple ratio between storage and requests, but can also be appropriately corrected according to the overall level of request costs. The introduction of the Sigmoid function can avoid excessive bias towards storage or request when the request cost is high, thereby making the calculation of the management burden smoother and more flexible, and adapting to dynamically changing request patterns.

[0042] S4: In response to the key data having a management burden less than a set threshold being the target data, the target data is stored on-chain.

[0043] In one embodiment, when the management burden of key data is lower than the set threshold, the key data is identified as target data and stored on the chain. In order to ensure efficient operation of the system, the set threshold can be 0.6. Of course, this value can be adjusted according to specific application requirements and actual conditions. By dynamically setting the threshold, the storage strategy can be flexibly adjusted according to different data characteristics while ensuring storage efficiency.

[0044] Furthermore, the blockchain storage of target data is managed by a smart contract mechanism, which has significant advantages in improving the transparency, reliability and immutability of the system. Smart contracts can not only automatically perform storage operations, but also ensure that the access, modification and verification processes of all stored data comply with preset rules, avoiding human intervention or unnecessary operations. At the same time, the decentralized nature of blockchain is used to further enhance the security and tamper-proof capabilities of data, making the target data more reliable during storage and processing.

[0045] The scheme of the present invention significantly improves the storage, request and management efficiency of key data through a blockchain-based key management method combined with data processing and dynamic management mechanisms of multi-dimensional parameters. By calculating the storage cost, request cost and management burden of each key data, the storage demand and request stability of the key data in the blockchain can be accurately evaluated, so as to intelligently select appropriate key data for storage according to actual conditions, reducing unnecessary storage and computing overhead. The smart contract mechanism is further adopted to perform on-chain storage management of target data to ensure the automation, transparency and security of data storage. At the same time, through standardized processing of data and dynamic adjustment of parameter weights, the system can adapt to different operating environments and requirements, optimize resource allocation, and improve the overall performance and reliability of blockchain key management. Not only does it enhance the security of key management, but it also achieves efficient and flexible control in the storage and request process, providing an innovative solution for the application of blockchain technology in the field of key management.

[0046] In the description of this specification, "plurality" or "several" means at least two, such as two, three or more, etc., unless otherwise clearly and specifically defined.

[0047] Although this specification has shown and described a number of embodiments of the present invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Those skilled in the art will conceive of many modifications, changes and alternatives without departing from the ideas and spirit of the present invention. It should be understood that in the practice of the present invention, various alternatives to the embodiments of the present invention described herein may be employed.

Claims

1. A key management method based on blockchain, characterized in that: include: Obtaining key data of the blockchain in the current time period, wherein the key data includes parameter data of multiple dimensions; Calculate the The weight of the dimension parameter , , where is the normalization function, For the The key data The value of the dimension parameter, is the total number of dimension parameters, is the total number of key data; calculate the The storage cost of key data and request cost , , where For all key data The mean of the dimension parameter values; The request cost is the same as The value of each dimension parameter in the key data and the weight of each dimension parameter are negatively correlated, and positively correlated with the total number of each dimension parameter. The calculation method is: , where is the normalization function, For the The key data The value of the dimension parameter, For all key data The mean of the dimension parameter values, For the The weight of the dimension parameters, is the total number of dimension parameters; Calculate the The management burden of key data , , To preset hyperparameters, the key data in response to the management burden being less than a set threshold is taken as target data, and the target data is stored on-chain.

2. A blockchain-based key management method according to claim 1, characterized in that: The request cost The calculation method also includes, , where is the normalization function, For the The key data The value of the dimension parameter, For all key data The standard deviation of the dimension parameter values, For the The weight of the dimension parameters, is the total number of dimension parameters.

3. The blockchain-based key management method according to claim 1, characterized in that: When storage costs Request cost When the absolute value of the ratio is greater than 1, ; When storage cost Request cost When the absolute value of the ratio is less than 1, , where is the normalization function, The average cost of all key data requests.

4. The blockchain-based key management method according to claim 1, characterized in that: The parameter data of the multiple dimensions include: the size of the key data, the usage frequency of the key data and the encryption strength of the key data.

5. The blockchain-based key management method according to claim 1, characterized in that: Also includes: The storage of target data in the blockchain is managed using the smart contract mechanism.

6. The blockchain-based key management method according to claim 1, characterized in that: The method also includes standardizing the key data.

7. The blockchain-based key management method according to claim 1, characterized in that: The threshold value is set to 0.

6.

8. The blockchain-based key management method according to claim 1, characterized in that: The preset hyperparameter is 0.

5.

9. The blockchain-based key management method according to claim 1, characterized in that: The normalization function is maximum-minimum normalization.

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