Improving Smart Contract Security with Contrastive Learning-based Vulnerability Detection

arXiv:2404.17839v1 Announce Type: new
Abstract: Currently, smart contract vulnerabilities (SCVs) have emerged as a major factor threatening the transaction security of blockchain. Existing state-of-the-art methods rely on deep learning to mitigate this threat. They treat each input contract as an independent entity and feed it into a deep learning model to learn vulnerability patterns by fitting vulnerability labels. It is a pity that they disregard the correlation between contracts, failing to consider the commonalities between contracts of the same type …

art arxiv blockchain contract cs.cr cs.se deep learning detection factor feed input major security smart smart contract state threat transaction vulnerabilities vulnerability vulnerability detection