Comparative evaluation of anomaly detection techniques for sequence data

Varun Chandola, Varun Mithal, Vipin Kumar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

72 Scopus citations

Abstract

We present a comparative evaluation of a large number of anomaly detection techniques on a variety of publicly available as well as artificially generated data sets. Many of these are existing techniques while some are slight variants and/or adaptations of traditional anomaly detection techniques to sequence data.

Original languageEnglish (US)
Title of host publicationProceedings - 8th IEEE International Conference on Data Mining, ICDM 2008
Pages743-748
Number of pages6
DOIs
StatePublished - 2008
Event8th IEEE International Conference on Data Mining, ICDM 2008 - Pisa, Italy
Duration: Dec 15 2008Dec 19 2008

Publication series

NameProceedings - IEEE International Conference on Data Mining, ICDM
ISSN (Print)1550-4786

Other

Other8th IEEE International Conference on Data Mining, ICDM 2008
CountryItaly
CityPisa
Period12/15/0812/19/08

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  • Cite this

    Chandola, V., Mithal, V., & Kumar, V. (2008). Comparative evaluation of anomaly detection techniques for sequence data. In Proceedings - 8th IEEE International Conference on Data Mining, ICDM 2008 (pp. 743-748). [4781172] (Proceedings - IEEE International Conference on Data Mining, ICDM). https://doi.org/10.1109/ICDM.2008.151