Function-Level Similarity is a malware attribution technique that analyzes the structural and behavioral resemblance of individual functions across binary samples to identify shared code or authorship, distinguishing itself from other similarity measures by focusing specifically on function-scale features rather than file-level or system-level characteristics.
45
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3.4K
Citations
159
Authors
71
Institutions
Publications per year
2017–2026
17
Parents
Publications
45
1–5 of 45
Authors
159
- BF
2
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2
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2
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2
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1–5 of 159
Institutions
71
Pennsylvania State University
State College, United States
2 h-index
4 publications
140 citations
University of Chinese Academy of Sciences
Beijing, China
2 h-index
12 publications
265 citations
Purdue University West Lafayette
West Lafayette, United States
2 h-index
11 publications
288 citations
University of Edinburgh
Edinburgh, United Kingdom
2 h-index
4 publications
72 citations
University of Bremen
Bremen, Germany
2 h-index
6 publications
369 citations
Technion – Israel Institute of Technology
Haifa, Israel
2 h-index
4 publications
450 citations
Qualcomm (United States)
San Diego, United States
2 h-index
4 publications
72 citations
University of California, Santa Cruz
Santa Cruz, United States
1 h-index
3 publications
273 citations
1–8 of 71
Venues
- IEEE Transactions on Software Engineering
TSE · 2 publications · 61 citations
2
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- ACM SIGPLAN Notices
2 publications · 97 citations
2
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- ACM SIGSOFT Software Engineering Notes
SEN · 1 publications · 12 citations
1
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- ACM Transactions on Software Engineering and Methodology
TOSEM · 1 publications · 22 citations
1
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- Journal of Software Maintenance and Evolution Research and Practice
1 publications · 50 citations
1
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