reviewACM Computing SurveysJul 1, 2009Closed access

Anomaly detection

University of Minnesota

Indexed incrossref

Abstract

Anomaly detection is an important problem that has been researched within diverse research areas and application domains. Many anomaly detection techniques have been specifically developed for certain application domains, while others are more generic. This survey tries to provide a structured and comprehensive overview of the research on anomaly detection. We have grouped existing techniques into different categories based on the underlying approach adopted by each technique. For each category we have identified key assumptions, which are used by the techniques to differentiate between normal and anomalous behavior. When applying a given technique to a particular domain, these assumptions can be used as…

Citation impact

11,029
total citations
FWCI
339.09
Percentile
100%
References
400
Citations per year

Authors

3

Topics & keywords

Keywords
  • Computer science
  • Anomaly detection
  • Domain (mathematical analysis)
  • Key (lock)
  • Anomaly (physics)
  • Data mining
  • Data science
  • Artificial intelligence
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Funding