• DocumentCode
    2710222
  • Title

    Comparative Evaluation of Anomaly Detection Techniques for Sequence Data

  • Author

    Chandola, Varun ; Mithal, Varun ; Kumar, Vipin

  • Author_Institution
    Univ. of Minnesota, Minneapolis, MN
  • fYear
    2008
  • fDate
    15-19 Dec. 2008
  • Firstpage
    743
  • Lastpage
    748
  • 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.
  • Keywords
    security of data; anomaly detection technique; artificially generated data set; publicly available data set; sequence data; Automata; Data mining; Hidden Markov models; Intrusion detection; Kernel; Nearest neighbor searches; Object detection; Performance evaluation; Postal services; Testing; Anomaly Detection; Sequences;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining, 2008. ICDM '08. Eighth IEEE International Conference on
  • Conference_Location
    Pisa
  • ISSN
    1550-4786
  • Print_ISBN
    978-0-7695-3502-9
  • Type

    conf

  • DOI
    10.1109/ICDM.2008.151
  • Filename
    4781172
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2710222