Cluster-Based Anomaly Detection is a method of identifying anomalous instances by grouping data into clusters and classifying points that reside in low-density regions or distant from cluster centroids as anomalies.
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Publications
489
Intrusion detection with unlabeled data using clustering
Leonid Portnoy · Open MIND · 2000 · 757 citations · Full text
A cooperative intrusion detection system for ad hoc networks
Yi-an Huang, Wenke Lee · 2003 · 483 citations
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The University of Melbourne
Melbourne, Australia
11 h-index
47 publications
3K citations
Amirkabir University of Technology
Tehran, Iran
9 h-index
19 publications
1.1K citations
Chinese Academy of Sciences
Beijing, China
7 h-index
20 publications
3.2K citations
Nanjing University
Nanjing, China
6 h-index
14 publications
518 citations
Northeastern University
Shenyang, China
6 h-index
15 publications
415 citations
Chongqing University
Chongqing, China
6 h-index
16 publications
977 citations
Ames Research Center
Mountain View, United States
5 h-index
9 publications
471 citations
Tsinghua University
Beijing, China
5 h-index
14 publications
794 citations
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14 publications · 799 citations
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9 publications · 324 citations
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7 publications · 1.2K citations
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- Knowledge-Based Systems
6 publications · 860 citations
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- Sensors
6 publications · 140 citations
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