• DocumentCode
    3316648
  • Title

    ACComplice: Location inference using accelerometers on smartphones

  • Author

    Han, Jun ; Owusu, Emmanuel ; Nguyen, Le T. ; Perrig, Adrian ; Zhang, Joy

  • Author_Institution
    Carnegie Mellon Univ., Pittsburgh, PA, USA
  • fYear
    2012
  • fDate
    3-7 Jan. 2012
  • Firstpage
    1
  • Lastpage
    9
  • Abstract
    The security and privacy risks posed by smartphone sensors such as microphones and cameras have been well documented. However, the importance of accelerometers have been largely ignored. We show that accelerometer readings can be used to infer the trajectory and starting point of an individual who is driving. This raises concerns for two main reasons. First, unauthorized access to an individual´s location is a serious invasion of privacy and security. Second, current smartphone operating systems allow any application to observe accelerometer readings without requiring special privileges. We demonstrate that accelerometers can be used to locate a device owner to within a 200 meter radius of the true location. Our results are comparable to the typical accuracy for handheld global positioning systems.
  • Keywords
    accelerometers; mobile computing; operating systems (computers); smart phones; telecommunication security; ACComplice; Global Positioning Systems; accelerometers; cameras; location inference; microphones; operating systems; privacy risk; security risk; smartphone sensor; Accelerometers; Dead reckoning; Motion segmentation; Probability; Roads; Sensors; Trajectory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communication Systems and Networks (COMSNETS), 2012 Fourth International Conference on
  • Conference_Location
    Bangalore
  • Print_ISBN
    978-1-4673-0296-8
  • Electronic_ISBN
    978-1-4673-0297-5
  • Type

    conf

  • DOI
    10.1109/COMSNETS.2012.6151305
  • Filename
    6151305