Cross-Modality Mutual Learning for Enhancing Smart Contract Vulnerability Detection on Bytecode
Peng Qian, Zhenguang Liu, Yifang Yin, Qinming He
Abstract
Over the past couple of years, smart contracts have been plagued by multifarious vulnerabilities, which have led to catastrophic financial losses. Their security issues, therefore, have drawn intense attention. As countermeasures, a family of tools has been developed to identify vulnerabilities in smart contracts at the source-code level. Unfortunately, only a small fraction of smart contracts is currently open-sourced. Another spectrum of work is presented to deal with pure bytecode, but most such efforts still suffer from relatively low performance due to the inherent difficulty in restoring abundant semantics in the source code from the bytecode.
Topics & Concepts
BytecodeComputer scienceVulnerability (computing)Modality (human–computer interaction)Computer securitySemantics (computer science)Code (set theory)Source codeProgramming languageArtificial intelligenceJavaSet (abstract data type)Blockchain Technology Applications and SecurityAdvanced Malware Detection TechniquesCybercrime and Law Enforcement Studies