• DocumentCode
    119633
  • Title

    Detecting suspicious behavior using a graph-based approach

  • Author

    Mookiah, Lenin ; Eberle, William ; Holder, Lawrence

  • Author_Institution
    Tennessee Tech University
  • fYear
    2014
  • fDate
    25-31 Oct. 2014
  • Firstpage
    357
  • Lastpage
    358
  • Abstract
    The ability to discover illicit behaviour in complex, heterogeneous data is a daunting problem. In the VAST 2014 competition, one of the challenges involves identifying for local law enforcement which employees are involved and where they should be concentrating their efforts. One approach to handling this problem is a graph-based approach. In this paper, we present a graph-based anomaly detection approach for discovering suspicious employees and geographic locations.
  • Keywords
    graph-based anomaly detection; knowledge discovery;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Visual Analytics Science and Technology (VAST), 2014 IEEE Conference on
  • Conference_Location
    Paris, France
  • Type

    conf

  • DOI
    10.1109/VAST.2014.7042564
  • Filename
    7042564