• DocumentCode
    144192
  • Title

    Geo-Location Inference Attacks: From Modelling to Privacy Risk Assessment (Short Paper)

  • Author

    Nunez del Prado Cortez, Miguel ; Frignal, Jesus

  • Author_Institution
    LAAS, Toulouse, France
  • fYear
    2014
  • fDate
    13-16 May 2014
  • Firstpage
    222
  • Lastpage
    225
  • Abstract
    Despite the commercial success of Location-Based Services (LBS), the sensitivity of the data they manage, specially those concerning the user´s location, makes them a suitable target for geo-location inference attacks. These attacks are a new variant of traditional inference attacks aiming at disclosing personal aspects of users´ life from their geo-location datasets. Since this threat might dramatically compromise the privacy of users, and so the confidence of LBS, a deeper knowledge of geo-location inference attacks becomes essential to protect LBS. To contribute to this goal, this short paper makes a step forward to model well-known types of geo-location inference attacks as a previous step to quantitatively assess the privacy risk they pose.
  • Keywords
    data privacy; mobile computing; risk management; LBS; geo-location datasets; geo-location inference attacks; location-based services; privacy risk assessment modelling; Data privacy; Hidden Markov models; Privacy; Security; Semantics; Trajectory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Dependable Computing Conference (EDCC), 2014 Tenth European
  • Conference_Location
    Newcastle
  • Type

    conf

  • DOI
    10.1109/EDCC.2014.32
  • Filename
    6821108