• DocumentCode
    654154
  • Title

    Diagnosing smartphone´s abnormal behavior through robust outlier detection methods

  • Author

    El Attar, Ali ; Khatoun, Rida ; Lemercier, Marc

  • Author_Institution
    ICD / ERA &STMR, Univ. of Technol. of Troyes (UTT), Troyes, France
  • fYear
    2013
  • fDate
    28-31 Oct. 2013
  • Firstpage
    1
  • Lastpage
    3
  • Abstract
    Smartphones have become increasingly popular and nowadays with the using of 3G networks, the needs in terms of connectivity in a business environment are substantial. Malicious use of such devices is highly dangerous since users may be victims of such use. In this paper, we present two statistical methods (Minimum Covariance Determinant (MCD) and Minimum Volume Ellipsoid (MVE) used to detect abnormal smartphone´s applications. Initial experiments results prove the efficiency and the accuracy of the MVE and MCD in detecting abnormal smartphone´s applications.
  • Keywords
    covariance analysis; smart phones; 3G networks; MCD; MVE; business environment; minimum covariance determinant; minimum volume ellipsoid; robust outlier detection methods; smart phone abnormal behavior diagnosis; statistical methods; Batteries; Covariance matrices; Ellipsoids; Malware; Robustness; Smart phones;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Global Information Infrastructure Symposium, 2013
  • Conference_Location
    Trento
  • Type

    conf

  • DOI
    10.1109/GIIS.2013.6684358
  • Filename
    6684358