Publication Details
CoinWatch: A Clone-Based Approach for Detecting Vulnerabilities in Cryptocurrencies
Tan Wei Jin (SUTD)
Tey Shi Ying (SUTD)
Lenus Latasha (SUTD)
Homoliak Ivan, doc. Ing., Ph.D. (DITS FIT BUT)
Lin Yun (NUS)
Sun Jun (SMU)
clone detection, cryptocurrencies, security, vulnerability propagation
Cryptocurrencies have become very popular in recent years. Thousands of new cryptocurrencies have emerged, proposing new and novel techniques that improve on Bitcoin's core innovation of the blockchain data structure and consensus mechanism. However, cryptocurrencies are a major target for cyber-attacks, as they can be sold on exchanges anonymously and most cryptocurrencies have their codebases publicly available. One particular issue is the prevalence of code clones in cryptocurrencies, which may amplify security threats. If a vulnerability is found in one cryptocurrency, it might be propagated into other cloned cryptocurrencies. In this work, we propose a systematic remedy to this problem, and we propose CoinWatch (CW). Given a reported vulnerability at the input, CW uses the code evolution analysis and a clone detection technique for indication of cryptocurrencies that might be vulnerable. We applied CW on 1094 cryptocurrencies using 4 CVEs and obtained 786 true vulnerabilities present in 384 projects, which were confirmed with developers and successfully reported as CVE extensions.
@INPROCEEDINGS{FITPUB12363, author = "Qingze Hum and Jin Wei Tan and Ying Shi Tey and Latasha Lenus and Ivan Homoliak and Yun Lin and Jun Sun", title = "CoinWatch: A Clone-Based Approach for Detecting Vulnerabilities in Cryptocurrencies", pages = "17--25", booktitle = "3rd IEEE INTERNATIONAL CONFERENCE ON BLOCKCHAIN (BLOCKCHAIN 2020)", year = 2020, location = "Rhodos, GR", publisher = "Institute of Electrical and Electronics Engineers", ISBN = "978-0-7381-0495-9", doi = "10.1109/Blockchain50366.2020.00011", language = "english", url = "https://www.fit.vut.cz/research/publication/12363" }