April 24, 2023, 1:10 a.m. | Tamer Abdelaziz, Aquinas Hobor

cs.CR updates on arXiv.org arxiv.org

We introduce Deep Learning Vulnerability Analyzer (DLVA), a vulnerability
detection tool for Ethereum smart contracts based on powerful deep learning
techniques for sequential data adapted for bytecode. We train DLVA to judge
bytecode even though the supervising oracle, Slither, can only judge source
code. DLVA's training algorithm is general: we "extend" a source code analysis
to bytecode without any manual feature engineering, predefined patterns, or
expert rules. DLVA's training algorithm is also robust: it overcame a 1.25%
error rate mislabeled …

algorithm analysis bytecode code code analysis data deep learning detection engineering error ethereum expert find general judge oracle patterns rate rules slither smart smart contracts source code student techniques tool train training vulnerability vulnerability detection vulnerable

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