• DocumentCode
    3294490
  • Title

    Anomaly detection approach using Hidden Markov Model

  • Author

    Dorj, E. ; Altangerel, Erdenebaatar

  • Author_Institution
    CSMS/Comput. Sci., MUST, Ulaanbaatar, Mongolia
  • Volume
    2
  • fYear
    2013
  • fDate
    June 28 2013-July 1 2013
  • Firstpage
    141
  • Lastpage
    144
  • Abstract
    Anomaly detection is an important problem that has been researched within diverse research areas. Numerous methods and approaches based on Hidden Markov Model regarding the anomaly detection have been proposed and reported in the literature. However, the potential applications using Hidden Markov Model classification based anomaly detection technique have not yet been fully explored and still in its infancy. This paper investigates the capabilities the use of Hidden Markov Model in anomaly detection for discrete sequences.
  • Keywords
    hidden Markov models; security of data; anomaly detection; discrete sequences; hidden Markov model; Atmospheric modeling; Bayes methods; Computational modeling; Hidden Markov models; Indexes; Markov processes; NASA; Anomaly detection; Baum-Welch algorithm; Data discretization; Hidden Markov Model; Likelihood;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Strategic Technology (IFOST), 2013 8th International Forum on
  • Conference_Location
    Ulaanbaatar
  • Print_ISBN
    978-1-4799-0931-5
  • Type

    conf

  • DOI
    10.1109/IFOST.2013.6616874
  • Filename
    6616874