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Smart Contract Fuzzing Based on Taint Analysis and Genetic Algorithms 被引量:1
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作者 zaoyu wei Jiaqi Wang +1 位作者 Xueqi Shen Qun Luo 《Journal of Quantum Computing》 2020年第1期11-24,共14页
Smart contract has greatly improved the services and capabilities of blockchain,but it has become the weakest link of blockchain security because of its code nature.Therefore,efficient vulnerability detection of smart... Smart contract has greatly improved the services and capabilities of blockchain,but it has become the weakest link of blockchain security because of its code nature.Therefore,efficient vulnerability detection of smart contract is the key to ensure the security of blockchain system.Oriented to Ethereum smart contract,the study solves the problems of redundant input and low coverage in the smart contract fuzz.In this paper,a taint analysis method based on EVM is proposed to reduce the invalid input,a dangerous operation database is designed to identify the dangerous input,and genetic algorithm is used to optimize the code coverage of the input,which construct the fuzzing framework for smart contract together.Finally,by comparing Oyente and ContractFuzzer,the performance and efficiency of the framework are proved. 展开更多
关键词 Smart contract FUZZING taint analysis genetic algorithms
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Smart Contract Fuzzing Based on Taint Analysis and Genetic Algorithms
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作者 zaoyu wei Jiaqi Wang +1 位作者 Xueqi Shen Qun Luo 《Journal of Information Hiding and Privacy Protection》 2020年第1期35-45,共11页
Smart contract has greatly improved the services and capabilities of blockchain,but it has become the weakest link of blockchain security because of its code nature.Therefore,efficient vulnerability detection of smart... Smart contract has greatly improved the services and capabilities of blockchain,but it has become the weakest link of blockchain security because of its code nature.Therefore,efficient vulnerability detection of smart contract is the key to ensure the security of blockchain system.Oriented to Ethereum smart contract,the study solves the problems of redundant input and low coverage in the smart contract fuzz.In this paper,a taint analysis method based on EVM is proposed to reduce the invalid input,a dangerous operation database is designed to identify the dangerous input,and genetic algorithm is used to optimize the code coverage of the input,which construct the fuzzing framework for smart contract together.Finally,by comparing Oyente and ContractFuzzer,the performance and efficiency of the framework are proved. 展开更多
关键词 Smart contract FUZZING taint analysis genetic algorithms
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