Sensor-based Anomaly Detection
Sensor-Based Anomaly Detection is a systematic method for identifying deviations from normal operational behavior in critical infrastructure systems by analyzing real-time data streams collected through physical or virtual sensors.
491
Publications
22.7K
Citations
1.6K
Authors
630
Institutions
Publications per year
2017–2026
309
491
Approximate Data Collection in Sensor Networks using Probabilistic Models
David Chu, Amol Deshpande, Joseph M. Hellerstein et al. · 2006 · 472 citations
Computing, Data Science, Data Mining +11
Anomaly detection in wireless sensor networks: A survey
Miao Xie, Song Han, Biming Tian et al. · Journal of Network and Computer Applications · 2011 · 349 citations
1–5 of 491
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630

Harbin Institute of Technology
Harbin, China
10 h-index
37 publications
1.2K citations

The University of Melbourne
Melbourne, Australia
8 h-index
26 publications
2.1K citations
University of Illinois Urbana-Champaign
Urbana, United States
8 h-index
19 publications
1.1K citations
Tsinghua University
Beijing, China
8 h-index
18 publications
579 citations
University of Technology Malaysia
Johor Bahru, Malaysia
8 h-index
18 publications
599 citations

Idaho National Laboratory
Idaho Falls, United States
7 h-index
9 publications
276 citations
Laboratoire Informatique Paris Descartes
Paris, France
7 h-index
19 publications
1.3K citations
Siemens (Germany)
Munich, Germany
6 h-index
13 publications
198 citations
1–8 of 630
28 publications · 1.3K citations
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16 publications · 865 citations
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13 publications · 915 citations
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9 publications · 510 citations
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7 publications · 388 citations
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