Feature Extraction Methods for Binary Code Similarity Detection Using Neural Machine Translation Models
Norimitsu Ito,
Masaki Hashimoto,
Akira Otsuka
Abstract:Binary code similarity detection is an effective analysis technique for vulnerability, bug, and plagiarism detection in software for which the source code cannot be obtained. The recent proliferation of IoT devices has also increased the demand for similarity detection across different architectures. However, there are currently not many examples of feature extraction methods using neural machine translation models being applied to similarity detection in basic block units across different architectures. In th… Show more
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