• DocumentCode
    2903011
  • Title

    Using Coupled Hidden Markov Models to Model Suspect Interactions in Digital Forensic Analysis

  • Author

    Brewer, Nathan ; Liu, Nianjun ; De Vel, O. ; Caelli, Terry

  • Author_Institution
    Australia Nat. Univ., Canberra, ACT
  • fYear
    2006
  • fDate
    Dec. 2006
  • Firstpage
    58
  • Lastpage
    64
  • Abstract
    This paper expands the use of hidden Markov models in digital forensics by using coupled hidden Markov models to investigate interactions between multiple suspects in forensic cases. This paper compares the output of a coupled hidden Markov model to a similarly trained single-chain hidden Markov models and to expert knowledge in a simulated digital forensic case with two suspects. In the situation modelled, there was a notable improvement in the accuracy of the coupled model compared to single chain models. This demonstrates that there is some form of interaction between suspects in this digital forensic case, and that this interaction can be effectively modelled by a coupled hidden Markov model
  • Keywords
    criminal law; expert systems; hidden Markov models; police data processing; coupled hidden Markov model; digital forensic analysis; expert knowledge; single-chain hidden Markov model; suspect interaction; Australia; Bayesian methods; Coupled mode analysis; Data mining; Decision trees; Digital forensics; Digital systems; Hidden Markov models; Law enforcement; Predictive models;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Integrating AI and Data Mining, 2006. AIDM '06. International Workshop on
  • Conference_Location
    Hobart, Tas.
  • Print_ISBN
    0-7695-2730-2
  • Type

    conf

  • DOI
    10.1109/AIDM.2006.16
  • Filename
    4030713