Malware Sample Clustering
Malware Sample Clustering is the computational process of grouping malware samples into coherent classes based on shared behavioral, structural, or code-level attributes, enabling automated categorization and triage in large-scale malware analysis.
41
Publications
1.9K
Citations
135
Authors
65
Institutions
Publications per year
2017–2026
15
Parents
41
Scalable, behavior-based malware clustering
Ulrich Bayer · 2009 · 571 citations
Is data clustering in adversarial settings secure?
Battista Biggio, Ignazio Pillai, Samuel Rota Bulò et al. · 2013 · 114 citations
MutantX-S: scalable malware clustering based on static features
Xin Hu, Sandeep Bhatkar, Kent Griffin et al. · 2013 · 89 citations
peHash: a novel approach to fast malware clustering
Georg Wicherski · 2009 · 82 citations
Graph Embedding Based Familial Analysis of Android Malware using Unsupervised Learning
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University of Portsmouth
Portsmouth, United Kingdom
2 h-index
3 publications
64 citations
EURECOM
Valbonne, France
2 h-index
2 publications
77 citations
San Jose State University
San Jose, United States
2 h-index
6 publications
204 citations

University of Sannio
Benevento, Italy
2 h-index
4 publications
136 citations
Carnegie Mellon University
Pittsburgh, United States
1 h-index
2 publications
30 citations

Federation University
Ballarat, Australia
1 h-index
3 publications
60 citations
Northumbria University
Newcastle upon Tyne, United Kingdom
1 h-index
1 publications
28 citations
University of Brighton
Brighton, United Kingdom
1 h-index
1 publications
18 citations
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5 publications · 105 citations
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2 publications · 30 citations
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1 publications · 10 citations
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1 publications · 62 citations
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1 publications · 14 citations
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