Computer Science ›› 2022, Vol. 49 ›› Issue (3): 52-61.doi: 10.11896/jsjkx.210700004

• Novel Distributed Computing Technology and System • Previous Articles     Next Articles

Overview of Vulnerability Detection Methods for Ethereum Solidity Smart Contracts

ZHANG Ying-li, MA Jia-li, LIU Zi-ang, LIU Xin, ZHOU Rui   

  1. School of Information Science & Engineering,Lanzhou University,Lanzhou 730000,China
  • Received:2021-07-01 Revised:2021-08-19 Online:2022-03-15 Published:2022-03-15
  • About author:ZHANG Ying-li,born in 1997,postgra-duate.Her main research interests include web security and blockchain security.
    ZHOU Rui,born in 1981,associate professor.His main research interests include distributed systems,embedded systems and machine learning.
  • Supported by:
    National Key R & D Program of China(2020YFC0832500),Gansu Provincial Science and Technology Major Special Innovation Consortium Project(Project No.1),National Natural Science Foundation of China(61402210),Science and Technology Plan of Qinghai Province(2020-GX-164),Ministry of Education-China Mobile Research Foundation(MCM20170206) and Fundamental Research Funds for the Central Universities(lzujbky-2021-sp47,lzujbky-2020-sp02,lzujbky-2019-kb51,lzujbky-2018-k12).

Abstract: Based on blockchain technology,Ethereum Solidity smart contract as a computer protocol is designed to spread,verify,or execute contracts in an informative way,and it provides a foundation for various distributed application services.Although implemented for less than six years,its security problems have frequently broken out and caused substantial financial losses,which attracts more attention in the security inspection research.This paper firstly introduces some specific mechanisms and operating principles of smart contracts based on Ethereum related techniques,and analyzes some smart contract vulnerabilities occurring frequently and deriving from the characteristics of smart contracts.Then,this paper explains the traditional mainstream smart contract vulnerability detecting tools in terms of symbolic execution,fuzzing,formal verification,and taint analysis.In addition,in order to cope with the endless new vulnerabilities and the need to improve the efficiency of detection,vulnerabilities detection based on machine learning in recent years is classified and summarized according to the various ways of problem transformation in three perspectives including text processing,non-Euclidean graph and standard image.Finally,this paper proposes to formulate more extensive and accurate standardized information database and measurement indicators towards the insufficiency of the detection methods in two directions.

Key words: Blockchain, Machine learning, Security vulnerability, Smart contracts, Vulnerability detection tools

CLC Number: 

  • TP311
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