jTrans: Jump-Aware Transformer for Binary Code Similarity. (arXiv:2205.12713v1 [cs.CR])

Binary code similarity detection (BCSD) has important applications in various
fields such as vulnerability detection, software component analysis, and
reverse engineering. Recent studies have shown that deep neural networks (DNNs)
can comprehend instructions or control-flow graphs (CFG) of binary code and
support BCSD. In this study, we propose a novel Transformer-based approach,
namely jTrans, to learn representations of binary code. It is the first
solution that embeds control flow information of binary code into
Transformer-based language models, by using a …

binary code similarity