Detecting vulnerabilities in smart contract within blockchain: a review and comparative analysis of key approaches

Abstract

Blockchain technology was created with security in mind. However, in recent years, there has been various confirmed cases of breach, worth billions of dollars loss in Blockchain associated to smart contracts. In order to address this growing concern, it is crucial to investigate detection and mitigation of vulnerabilities in smart contract, and this paper critically reviews and analyses key approaches for detecting vulnerabilities in smart contract within Blockchain. In order to achieve the purpose of this paper, five key approaches, notably the application of OWASP Top 10, SCSVS, vulnerability detection tools, fuzz testing and the AI-driven approaches are critically reviewed and compared. As part of the comparison performed, a penetration testing quality model was applied to study six quality metrics, notably extensibility, maintainability, domain coverage, usability, availability and reliability. Results revealed limitations of the studied vulnerability detection approaches and findings are expected to help in decision making especially when selecting approaches to be used during security analysis and pen-testing

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