Using Extracted Behavioral Features to Improve Privacy for Shared Route Tracks

  • Mads Schaarup Andersen
  • Mikkel Baun Kjærgaard
  • Kaj Grønbæk
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 107)


Track-based services, such as road pricing, usage-based insurance, and sports trackers, require users to share entire tracks of locations, however this may seriously violate users’ privacy. Existing privacy methods suffer from the fact that they degrade service quality when adding privacy. In this paper, we present the concept of privacy by substitution that addresses the problem without degrading service quality by substituting location tracks with less privacy invasive behavioral data extracted from raw tracks of location data or other sensing data. We explore this concept by designing and implementing TracM, a track-based community service for runners to share and compare their running performance. We show how such a service can be implemented by substituting location tracks with less privacy invasive behavioral data. Furthermore, we discuss the lessons learned from building TracM and discuss the application of the concept to other types of track-based services.


Location Privacy Track-based services Privacy-By-Substitution Behavioral Features Running 


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Copyright information

© ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering 2012

Authors and Affiliations

  • Mads Schaarup Andersen
    • 1
  • Mikkel Baun Kjærgaard
    • 1
  • Kaj Grønbæk
    • 1
  1. 1.Department of Computer ScienceAarhus UniversityDenmark

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