CN115168870A - Block chain safety assessment method based on comprehensive evaluation - Google Patents

Block chain safety assessment method based on comprehensive evaluation Download PDF

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CN115168870A
CN115168870A CN202210908237.4A CN202210908237A CN115168870A CN 115168870 A CN115168870 A CN 115168870A CN 202210908237 A CN202210908237 A CN 202210908237A CN 115168870 A CN115168870 A CN 115168870A
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safety
block chain
index
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陈锦富
许容天
蔡赛华
王栋杰
冯乔伟
陈宇豪
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Jiangsu University
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/50—Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
    • G06F21/57—Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
    • G06F21/577—Assessing vulnerabilities and evaluating computer system security
    • G—PHYSICS
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Abstract

The invention provides a block chain safety assessment method based on comprehensive evaluation. The method comprises the following steps: step 1, establishing a block chain safety evaluation index model according to the technical architecture of the block chain; step 2, weighting the safety assessment index model by using an improved analytic hierarchy process to obtain the safety weight of each safety index; step 3, correcting the weight of the safety index by applying an improved entropy weight method; step 4, applying an improved good-bad solution distance method to the corrected safety index weight to obtain a safety score of the block chain; and 5, obtaining the safety evaluation grade of the block chain according to the safety evaluation result obtained in the step 4.

Description

Block chain safety assessment method based on comprehensive evaluation
Technical Field
The invention belongs to the technical field of block chain safety in software testing, and relates to a block chain safety evaluation method based on comprehensive evaluation.
Background
At present, the blockchain technology and application are in a rapid development stage, and by means of decentralization, tamper resistance and other security characteristics, the blockchain gradually becomes an important application technology in the fields of finance, finance and the like. However, the blockchain also faces a wide variety of security risks, and the security of ecological application of the blockchain, including user private key security, account security, application software security, use security and the like, includes various complex service scenes and service logics, and is easy to become an attacked object; the system design of the block chain also has security risks, the problems of bifurcation, double-flower attack and the like can be caused due to improper design of a consensus mechanism, and illegal transactions can be legalized due to logic loopholes of an intelligent contract; the blockchain system provides a number of basic components for which the security risks are classified as: network security, cryptography security, data storage security. Therefore, the security problem of the block chain is getting attention, and is becoming a focus of research at home and abroad.
In recent years, some methods have been proposed for evaluating the security risk of a blockchain, and most studies analyze the influence on a blockchain attack, such as a 51% attack, a eclipse attack, and the like, from the viewpoint of an attack mode, thereby evaluating the security of the blockchain. However, the security problem of the blockchain is widely distributed and has high risk, and the security of the blockchain cannot be fully embodied only by analyzing a certain attack mode. According to literature review, the existing safety assessment research on the block chain is still in an exploration stage, the industry lacks a unified evaluation standard, and pain points that the safety of the block chain is difficult to assess and compare are faced. Therefore, the invention provides a block chain safety evaluation method based on comprehensive evaluation, which adopts a hierarchical structure model thought of a hierarchy analysis method in the comprehensive evaluation to establish a block chain-oriented safety evaluation index model and carries out combined improvement on three comprehensive evaluation methods of the hierarchy analysis method, an entropy weight method and a good-bad solution distance method, thereby calculating the safety score of the block chain.
Disclosure of Invention
In order to solve the problem of how to comprehensively and objectively evaluate and compare the block chain safety, the invention provides a block chain safety evaluation method based on comprehensive evaluation, and the experimental result of the method is compared with the authoritative block chain evaluation organization data, so that the effectiveness of the method and the accuracy of the evaluation result are verified.
The technical scheme of the invention is as follows:
step 1, establishing a block chain safety evaluation index model according to the technical architecture of the block chain;
step 2, weighting the safety assessment index model by using an improved analytic hierarchy process to obtain the safety weight of each safety index;
step 3, correcting the weight of the safety index by applying an improved entropy weight method;
step 4, applying an improved good-bad solution distance method to the corrected safety index weight to obtain a safety score of the block chain;
and 5, obtaining the safety evaluation grade of the block chain according to the safety scoring result obtained in the step 4.
In a first aspect, the specific steps of step 1 are as follows:
step 1.1, establishing a hierarchical index model structure of block chain safety evaluation according to the block chain safety characteristics, and taking the block chain safety as the highest target layer;
step 1.2, extracting attributes which obviously affect the safety of the block chain from the block chain technical architecture, wherein the attributes comprise a data layer, a network layer, a consensus layer, a contract layer and an application layer and serve as first-level indexes of a second layer in a safety evaluation index model;
and step 1.3, extracting attributes which obviously influence the block chain safety from each primary index of the safety evaluation index model, wherein the attributes comprise a data structure of a data layer, a network structure of a network layer, a consensus mechanism of a consensus layer, a contract language of a contract layer and an application field of an application layer, and the attributes are used as secondary indexes of a third layer under each primary index.
In a second aspect, the specific steps of step 2 are as follows:
step 2.1, using 1-9 scale method and a 0 ～a 8 A judging matrix A is constructed for a safety evaluation index model by a calibration method, and the relative importance of the factors of the current layer to the factors of the previous layer is compared in pairs from an objective information source;
step 2.2, solving a weight vector Wi of the judgment matrix by adopting a square root method, and calculating a maximum eigenvalue lambda of the judgment matrix;
step 2.3, checking the consistency of the judgment matrix;
and 2.4, if the consistency is checked to be passed, obtaining the hierarchical index weight w in the safety evaluation index model, and if not, reconstructing a judgment matrix.
In a third aspect, the process of solving the judgment matrix by the square root method includes:
calculating the n-th power root M of the product of each row of the judgment matrix A i N represents the order of the judgment matrix, and the calculation mode is as follows:
Figure BDA0003773283700000021
wherein, a ij Representing the comparison result of the ith factor relative to the jth factor;
will M i Carrying out normalization processing to obtain a weight vector Wi of the judgment matrix, wherein the calculation mode is as follows:
Figure BDA0003773283700000022
calculating the maximum eigenvalue lambda of the judgment matrix in the following way:
Figure BDA0003773283700000023
in a fourth aspect, the checking process for consistency of the judgment matrix includes:
CI is a measure judgment matrix deviation consistency index, and the calculation mode is as follows:
Figure BDA0003773283700000024
wherein n represents the order number of the judgment matrix, lambda represents the maximum characteristic value of the judgment matrix, the larger the CI is, the worse the consistency of the judgment matrix is, and when the CI is 0, the judgment matrix has complete consistency;
CR is the consistency ratio and is calculated by the formula:
Figure BDA0003773283700000031
wherein RI is the average random consistency index when CR is<At 0.1, the decision matrix may be considered to pass the consistency check.
In a fifth aspect, the specific steps of step 3 are as follows:
step 3.1, adopting the weighted block chain safety assessment index model obtained in the step 2, carrying out safety index value taking on the block chain item to be tested, and constructing an entropy weight judgment matrix B;
step 3.2, standardizing the data of the entropy weight judgment matrix B by adopting a range standardization method, wherein the calculation mode is as follows:
Figure BDA0003773283700000032
obtaining a standardized judgment matrix R;
step 3.3, calculating the information entropy value e of the index in the block chain safety assessment index model by adopting an improved entropy weight method j Solving the entropy weight index weight u according to the entropy value j ；
And 3.4, correcting the hierarchical index weight w obtained in the step 2 by the obtained entropy weight index weight u to obtain a corrected index weight theta, wherein the calculation mode is as follows: θ = ρ w + (1- ρ) u, where ρ represents a weighting factor.
In a sixth aspect, the process of calculating the weight of the entropy index includes:
calculating an information entropy value e of an index j The calculation method is as follows:
Figure BDA0003773283700000033
wherein f is ij Represents the weight of the index obtained by the ith item under the jth index, f ij The calculation method is as follows:
Figure BDA0003773283700000034
wherein R is ij The value of the ith row and the jth column in the standardized judgment matrix R is represented;
solving entropy weight index weight u according to entropy value j The calculation method is as follows:
Figure BDA0003773283700000035
wherein e is j An information entropy value representing an index.
In a seventh aspect, the specific steps of step 4 are as follows:
step 4.1, performing data index homotrenization treatment by adopting the entropy weight judgment matrix B obtained in the step 3, so as to make the directions of original data indexes consistent and obtain a forward judgment matrix X;
step 4.2, a vector normalization method of cosine distance measurement is adopted to carry out normalization processing on the forward judgment matrix X, and the calculation mode is as follows:
Figure BDA0003773283700000036
thereby obtaining a normalized matrix Z;
and 4.3, calculating the degree of closeness of the evaluation index to the optimal vector and the worst vector, wherein the calculation modes are respectively as follows:
Figure BDA0003773283700000041
wherein θ represents the corrected index weight obtained in step 3, Z + Represents an optimal vector, consisting of the maximum of each column of elements in Z, Z - Representing the worst vector, which is formed by the minimum value of each column of elements in Z;
step 4.4, solving the block chain security score C by adopting a mode of the closeness degree of the evaluation object and the optimal scheme i The calculation method is as follows:
Figure BDA0003773283700000042
C i a larger value indicates a higher security of the blockchain item under test.
Compared with the prior art, the invention has the following beneficial effects:
1. the block chain safety evaluation method based on comprehensive evaluation can analyze the safety characteristics of the block chain more comprehensively. The block chain safety evaluation method based on comprehensive evaluation extracts a plurality of attributes influencing the block chain safety into a hierarchical structure index model, weights the safety index by adopting a combined improved comprehensive evaluation method, and reasonably calculates the index weight to obtain the safety score of the block chain.
2. The block chain safety evaluation method based on comprehensive evaluation can well make objective evaluation on the block chain safety. The block chain safety evaluation method based on comprehensive evaluation combines and improves the three comprehensive evaluation methods, and can be better applied to the safety evaluation of the block chain. The method improves the scaling method when the traditional analytic hierarchy process constructs the judgment matrix, adopts a mode of combining two scaling methods, and selects the comparative value of the index safety importance from an objective information source, thereby improving the problems that the traditional analytic hierarchy process depends on expert scoring and has over-strong subjectivity; the calculation mode of the index weight in the traditional entropy weight method is improved, and the correction problem generated under the special numerical value condition is solved; the method improves the difference calculation mode of the evaluation object and the optimal and worst vectors in the traditional good and bad solution distance method, and makes the evaluation mode more suitable for the safety evaluation of the block chain.
3. The block chain safety assessment method based on comprehensive evaluation has high accuracy of the safety assessment result. Experiments prove that the block chain safety evaluation method based on comprehensive evaluation has high consistency in comparison of the safety evaluation result of the block chain item with the evaluation result of an authoritative block chain safety evaluation organization TokenInsight, so that the block chain safety evaluation method based on comprehensive evaluation has high accuracy.
Drawings
Fig. 1 is a general flowchart of a block chain security evaluation method based on comprehensive evaluation.
FIG. 2 is a block chain security assessment index model hierarchy diagram.
FIG. 3 is a scale for building a decision matrix in the improved analytic hierarchy process.
FIG. 4 is a diagram of an entitled security assessment indicator.
FIG. 5 is a safety index value of the block chain item under test according to the present invention.
FIG. 6 is an entropy weight index weight calculated using the security index of a blockchain item.
FIG. 7 shows the result of the security evaluation of the blockchain under test item according to the present invention.
FIG. 8 shows the result of the security evaluation of the block chain item under test by TokenInsight.
FIG. 9 is a comparison of the evaluation accuracy of the same blockchain item of the present invention versus TokenInsight.
Detailed Description
In order to clearly understand the technical content of the blockchain security assessment method based on comprehensive evaluation, the invention is further described with reference to the drawings and specific embodiments, and it should be noted that the embodiments are described to facilitate understanding of the invention and do not limit the invention.
As shown in fig. 1, the block chain security evaluation method based on comprehensive evaluation provided by the present invention includes:
step 201, establishing a block chain safety evaluation index model according to the technical architecture of the block chain;
step 2011, according to the safety characteristics of the blockchain, a hierarchical index model structure of blockchain safety evaluation is established, and the blockchain safety is used as the highest target layer;
step 2012 extracts attributes significantly affecting the safety of the block chain from the block chain technical architecture, including a data layer, a network layer, a consensus layer, a contract layer and an application layer, as first-level indexes of a second layer in the safety assessment index model;
step 2013, extracting attributes which obviously affect the safety of the block chain from each primary index of the safety assessment index model, wherein the attributes comprise a data structure of a data layer, a network structure of a network layer, a consensus mechanism of a consensus layer, a contract language of a contract layer and an application field of an application layer, and the attributes are used as secondary indexes of a third layer under each primary index.
According to the contrastive security attributes of each level in the block chain technical architecture and the detected block chain items selected in the embodiment of the invention, the first level indexes in the block chain security evaluation index model are respectively a data layer, a network layer, a consensus layer, a contract layer and an application layer, the second level indexes of the data layer comprise a merge tree, a merge patricia tree and a merge bucket tree, the second level indexes of the network layer comprise a fully distributed unstructured network, a fully distributed structured network and a semi-distributed network, the second level indexes of the consensus layer comprise a PoW consensus mechanism, a PoS consensus mechanism and a BFT/PBFT consensus mechanism, the second level indexes of the contract layer comprise a script type contract language, a picture-based contract language and a verifiable type contract language, and the second level indexes of the application layer comprise programmable currency, programmable financial and programmable society. Fig. 2 shows a block chain security assessment index model hierarchy diagram.
Step 202, weighting the safety assessment index model by using an improved analytic hierarchy process to obtain the safety weight of each safety index;
step 2021 uses a 1-9 scale and 0 ～a 8 a judging matrix A is constructed for a safety evaluation index model by a calibration method, and the relative importance of the factors of the current layer to the factors of the previous layer is compared in pairs from an objective information source;
when the judgment matrix is constructed, the pair-wise relative importance comparison is carried out by taking the factors of the same layer and the factors of the higher layer as the criteria, for example, the importance degree in the block chain security evaluation is compared in pair by taking the block chain security evaluation target layer as the criteria among the data layer, the network layer, the consensus layer, the contract layer and the application layer. The ratio between the factors is the scale, and in order to quantify the judgment, the invention is based on the 1-9 scale method and a 0 ～a 8 The scaling method determines the relative importance of each factor, the 1-9 scaling method divides the importance degree into 1-9 nine scaling grades, if the ratio of the importance of the factor i to the importance of the factor j is a ij The ratio of the importance of factor i to factor j is then a ji ＝1/a ij Constructing a judgment matrix according to the judgment matrix; a is 0 ～a 8 The scaling method divides the degree of importance into a 0 ～a 8 Nine scale levels, where a takes on a value of 1.316, if the ratio of the importance of factor i to factor j is a ij The ratio of the importance of factor i to factor j is then a ji ＝1/a ij Thus, a judgment matrix is constructed. FIG. 3 shows the scaling values for the improved analytic hierarchy process for creating the decision matrix.
Step 2022, solving the weight vector Wi of the judgment matrix by adopting a square root method, and calculating the maximum eigenvalue lambda of the judgment matrix;
the process of solving the judgment matrix by the square root method comprises the following steps: calculating the n-th power root M of the product of each row of the judgment matrix A i N represents the order of the judgment matrix, and the calculation mode is as follows:
Figure BDA0003773283700000061
wherein, a ij Representing the comparison result of the ith factor relative to the jth factor; will M i Carrying out normalization processing to obtain a weight vector Wi of the judgment matrix, wherein the calculation mode is as follows:
Figure BDA0003773283700000062
calculating the maximum eigenvalue lambda of the judgment matrix in the following way:
Figure BDA0003773283700000063
step 2023, checking the consistency of the judgment matrix, wherein the process includes:
CI is a measure judgment matrix deviation consistency index, and the calculation mode is as follows:
Figure BDA0003773283700000064
wherein n represents the order number of the judgment matrix, lambda represents the maximum characteristic value of the judgment matrix, the larger the CI is, the worse the consistency of the judgment matrix is, and when the CI is 0, the judgment matrix has complete consistency; CR is the consistency ratio and is calculated by the formula:
Figure BDA0003773283700000065
wherein RI is the average random consistency index when CR is<At 0.1, the decision matrix may be considered to pass the consistency check.
Step 2024, if the consistency check is passed, processing the index weights calculated by the two scaling methods by using an arithmetic mean method to obtain the hierarchical index weight w in the safety assessment index model, otherwise, reconstructing a judgment matrix.
The invention selects representative documents published in high-level periodicals as objective information sources, adopts two scaling methods to respectively construct a judgment matrix, and constructs each judgment matrix three times to improve the accuracy of calculation results. Fig. 4 shows the hierarchy index weights calculated by modified analytic hierarchy process.
Step 203, correcting the weight of the safety index by applying an improved entropy weight method;
step 2031, adopting the weighted block chain security assessment index model obtained in step 202, performing security index dereferencing on 20 tested block chain items, and constructing an entropy weight judgment matrix B;
step 2032, standardizing the data of the entropy weight judgment matrix B by a range standardization method, wherein the calculation method is as follows:
Figure BDA0003773283700000071
wherein r is ij Representing the value of the ith item in the jth index in the entropy weight judgment matrix B to obtain a standardized judgment matrix R;
step 2033 of calculating the information entropy e of the index in the block chain safety evaluation index model by using the improved entropy weight method j Solving the entropy weight index weight u according to the entropy value j ；
The entropy index weight calculation process comprises the following steps: calculating an information entropy value e of an index j The calculation method is as follows:
Figure BDA0003773283700000072
wherein f is ij Represents the weight of the index obtained from the ith item under the jth index, f ij The calculation method is as follows:
Figure BDA0003773283700000073
wherein R is ij The value of the ith row and the jth column in the standardized judgment matrix R is represented; solving entropy weight index weight u according to entropy value j The calculation method is as follows:
Figure BDA0003773283700000074
wherein e is j An information entropy value representing an index.
Step 2034, the obtained entropy weight index weight u is corrected to the level index weight w obtained in step 202, so as to obtain a corrected index weight θ, and the calculation method is as follows: θ = ρ w + (1- ρ) u, where ρ represents a weighting factor.
Step 204, applying an improved good-bad solution distance method to the corrected security index weight to obtain a security score of the block chain;
2041, performing data index homotrenization processing by using the entropy weight judgment matrix B obtained in step 203, so as to make the directions of the original data indexes consistent and obtain a forward judgment matrix X;
in the implementation case of the invention, the forward index is an index with higher evaluation value, the reverse index is an index with lower evaluation value, the moderate index is an index with higher evaluation value, and the trend processing aims at converting all indexes into the forward index, so that indexes with different characteristics have the same numerical direction.
Step 2042, normalization processing is performed on the forward judgment matrix X by using a vector normalization method of cosine distance measurement, and the calculation method is as follows:
Figure BDA0003773283700000075
wherein x is ij Representing the value of the ith item in the forward judgment matrix X in the jth index so as to obtain a normalized standardized matrix Z;
step 2043 calculates the degree of closeness of the evaluation index to the optimal vector and the worst vector, and the calculation methods are respectively as follows:
Figure BDA0003773283700000076
wherein, theta j Indicating the corrected index weight obtained in step 3,
Figure BDA0003773283700000077
representing an optimum vector, consisting of the maximum value of each column of elements in the normalized matrix Z,
Figure BDA0003773283700000078
representing the worst vector, consisting of the minimum of each column of elements in a normalized matrix Z, Z ij Representing the value of the ith item in the normalized matrix Z in the jth index;
step 2044, the block chain security score C is obtained by means of the closeness degree of the evaluation object and the optimal scheme i The calculation method is as follows:
Figure BDA0003773283700000081
C i a larger value indicates a higher security of the blockchain item under test.
Step 205 obtains the security evaluation level of the blockchain according to the security scoring result obtained in step 204.
In order to verify the effectiveness of the method, 20 famous public chain items are collected as experimental objects, and the method is compared with the evaluation result of a block chain evaluation mechanism TokenInsight. Fig. 5 shows a security index value obtained by applying the hierarchical structure index model of the invention to a blockchain item, fig. 6 shows an entropy weight index weight calculated by using the security index of the blockchain item, fig. 7 shows a security evaluation result of the method of the invention on the blockchain item to be tested, and fig. 8 shows a security evaluation result of the tokenlnight on the blockchain item to be tested. FIG. 9 shows the comparison of the evaluation accuracy of the present invention and TokenInsight for the same blockchain item. The result shows that the block chain safety evaluation of the method has high consistency with the evaluation result of an authoritative third-party block chain evaluation organization, and the feasibility of the model used by the method and the effectiveness of the method are verified.
The foregoing is merely for the purpose of illustrating particular embodiments of the invention and is not to be construed as limiting the scope of the invention, as any modifications, alterations and the like may be made without departing from the spirit and scope of the invention.

Claims (5)

1. A block chain safety assessment method based on comprehensive evaluation comprises the following steps:
step 1, establishing a block chain safety evaluation index model according to the technical architecture of the block chain;
step 2, weighting the safety assessment index model by using an improved analytic hierarchy process to obtain the safety weight of each safety index;
step 3, correcting the weight of the safety index by applying an improved entropy weight method;
step 4, applying an improved good-bad solution distance method to the corrected safety index weight to obtain a safety score of the block chain;
and 5, obtaining the safety evaluation grade of the block chain according to the safety evaluation result obtained in the step 4.
2. The block chain safety assessment method based on comprehensive evaluation as claimed in claim 1, wherein the specific implementation of the step 1 comprises the following steps:
step 1.1, establishing a hierarchical index model structure of block chain safety evaluation according to the block chain safety characteristic, and taking the block chain safety as a highest target layer;
step 1.2, extracting attributes which obviously affect the safety of the block chain from the block chain technical architecture, wherein the attributes comprise a data layer, a network layer, a consensus layer, a contract layer and an application layer and serve as first-level indexes of a second layer in a safety evaluation index model;
and step 1.3, extracting attributes which obviously influence the block chain safety from each primary index of the safety evaluation index model, wherein the attributes comprise a data structure of a data layer, a network structure of a network layer, a consensus mechanism of a consensus layer, a contract language of a contract layer and an application field of an application layer, and the attributes are used as secondary indexes of a third layer under each primary index.
3. The block chain security evaluation method based on comprehensive evaluation according to claim 1, wherein the specific implementation of step 2 includes the following steps:
step 2.1, using 1-9 scale method and a 0 ～a 8 A judging matrix A is constructed for the safety evaluation index model by a calibration method, and the relative importance of the factors of the current layer to the factors of the previous layer is compared in pairs from an objective information source;
step 2.2, solving a weight vector Wi of the judgment matrix by adopting a square root method, and calculating a maximum eigenvalue lambda of the judgment matrix;
step 2.3, checking the consistency of the judgment matrix;
and 2.4, if the consistency is checked to be passed, obtaining the hierarchical index weight w in the safety evaluation index model, and if not, reconstructing a judgment matrix.
4. The block chain safety assessment method based on comprehensive evaluation as claimed in claim 1, wherein the specific implementation of step 3 comprises the following steps:
step 3.1, adopting the weighted block chain safety assessment index model obtained in the step 2, carrying out safety index value taking on the block chain item to be tested, and constructing an entropy weight judgment matrix B;
step 3.2, standardizing the data of the entropy weight judgment matrix B by adopting a range standardization method to obtain a standardized judgment matrix R;
step 3.3, calculating the information entropy value e of the index in the block chain safety assessment index model by adopting an improved entropy weight method j Solving the entropy weight index weight u according to the entropy value j ；
And 3.4, correcting the hierarchical index weight w obtained in the step 2 by using the obtained entropy weight index weight u to obtain a corrected index weight theta.
5. The block chain safety assessment method based on comprehensive evaluation as claimed in claim 1, wherein the specific implementation of the step 4 comprises the following steps:
step 4.1, performing data index homotrenization treatment by adopting the entropy weight judgment matrix B obtained in the step 3, so as to make the directions of original data indexes consistent and obtain a forward judgment matrix X;
step 4.2, normalizing the forward judgment matrix X by adopting a vector normalization method of cosine distance measurement, so that data with different attributes have comparability and operability, and obtaining a normalized standardized matrix Z;
step 4.3, calculating an evaluation index and an optimal vector Z by adopting the corrected index weight theta obtained in the step 3 + The worst vector Z - In which Z is + Is formed by the maximum value of each column element in Z, and represents the optimal vector, Z - The minimum value of each column of elements in Z is used for representing the worst vector;
step 4.4, solving the block chain security score C by adopting a mode of the closeness degree of the evaluation object and the optimal scheme i ，C i A larger value indicates a higher security of the blockchain item under test.
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CN115695269A (en) * 2022-10-31 2023-02-03 中物院成都科学技术发展中心 Comprehensive quantitative evaluation method for performance of fuzzy test tool
CN115695269B (en) * 2022-10-31 2023-10-27 中物院成都科学技术发展中心 Comprehensive quantitative evaluation method for performance of fuzzy test tool
CN115494881A (en) * 2022-11-18 2022-12-20 西北工业大学 Unconstrained optimization index weighting method for unmanned aerial vehicle formation collaborative track planning
CN115494881B (en) * 2022-11-18 2023-03-10 西北工业大学 Unconstrained optimization index weighting method for unmanned aerial vehicle formation collaborative track planning

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