Runtime Anomaly Detection
Runtime Anomaly Detection is a dynamic vulnerability analysis method that identifies deviations from established behavioral norms during program execution to detect潜在 security violations or malfunctions in real time.
123
Publications
7.7K
Citations
457
Authors
191
Institutions
Publications per year
2017–2026
66
123
Experience Report: System Log Analysis for Anomaly Detection
Shilin He, Jieming Zhu, Pinjia He et al. · 2016 · 567 citations
A survey on anomaly detection for technical systems using LSTM networks
B. Lindemann, Benjamin Maschler, Nada Sahlab et al. · Computers in Industry · 2021 · 425 citations · Full text
Detecting object usage anomalies
Andrzej Wasylkowski, Andreas Zeller, Christian Lindig · 2007 · 274 citations
Unicorn: Runtime Provenance-Based Detector for Advanced Persistent Threats
2020 · 271 citations · Full text
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191

Concordia University
Montreal, Canada
4 h-index
9 publications
277 citations
University of Illinois Urbana-Champaign
Urbana, United States
4 h-index
7 publications
412 citations
Virginia Tech
Blacksburg, United States
4 h-index
10 publications
507 citations
North Carolina State University
Raleigh, United States
3 h-index
7 publications
518 citations
IBM (United States)
Armonk, United States
3 h-index
4 publications
806 citations

Chinese Academy of Sciences
Beijing, China
3 h-index
14 publications
347 citations

National University of Defense Technology
Changsha, China
2 h-index
5 publications
180 citations

Université Fédérale de Toulouse Midi-Pyrénées
Toulouse, France
2 h-index
8 publications
286 citations
1–8 of 191
Repository · 5 publications · 121 citations
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4 publications · 258 citations
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JSS · 4 publications · 207 citations
4
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FGCS · 2 publications · 81 citations
2
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TECS · 2 publications · 50 citations
2
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