Binary Similarity Analysis
Binary Similarity Analysis is a method in the field of malware analysis that identifies and quantifies structural and semantic correspondences between executable binaries to infer relationships such as code reuse, plagiarism, or common provenance, distinguishing itself from other program comparison techniques by operating solely on compiled machine code without reliance on source code or symbolic information.
116
Publications
7.6K
Citations
330
Authors
129
Institutions
Publications per year
2017–2026
56
116
A Survey of Binary Similarity and Distance Measures
Seung-Seok Choi, Sung-Hyuk Cha · 2010 · 842 citations · Full text
DeepSim: deep learning code functional similarity
Gang Zhao, Jeff Huang · 2018 · 265 citations
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330
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129
Technion – Israel Institute of Technology
Haifa, Israel
9 h-index
23 publications
1.8K citations
Institute of Information Engineering
Beijing, China
6 h-index
34 publications
2.1K citations

Chinese Academy of Sciences
Beijing, China
4 h-index
11 publications
577 citations
University of Chinese Academy of Sciences
Beijing, China
4 h-index
27 publications
1.5K citations

Hanyang University
Seoul, South Korea
4 h-index
13 publications
529 citations

Shanghai Jiao Tong University
Shanghai, China
4 h-index
14 publications
1.1K citations
Carnegie Mellon University
Pittsburgh, United States
3 h-index
14 publications
1.1K citations

University of Saskatchewan
Saskatoon, Canada
3 h-index
6 publications
244 citations
1–8 of 129
Repository · 5 publications · 112 citations
5
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4 publications · 231 citations
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TOSEM · 3 publications · 98 citations
3
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2 publications · 73 citations
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TSE · 2 publications · 117 citations
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