CT-ISG: Collaborative Research: A Context-Aware
Approach to the Design and Evaluation of Privacy Preservation Techniques in
Location-Based Services
Sponsored by NSF Cybertrust Program
08/01/2007-07/31/2010
PIs
Sushil Jajodia and Claudio Bettini, CSIS, George Mason University, Fairfax,
Virginia
X. Sean Wang, Computer Science Department, The University of Vermont,
Burlington, Vermont
Abstract
Privacy protection challenges arising from location-based services (LBS) are
critical to users as well as service providers. This project concentrates on
designing and evaluating privacy protection techniques in LBS. The important
departure of this project from the existing research is in its emphasis of the
role of request contexts. A context refers to the external information/knowledge
that the attacker may use, together with the requests themselves, to gain user
private information. For example, with the external knowledge of a user’s
approximate location at a particular time, the attacker may single out the user
of a particular LBS request and thus link the private information in the request
to the user. By its nature, context changes from requests to requests and
different contexts may call for different privacy protection techniques. The
technical objectives of the project are therefore to (1) systematically
categorize privacy contexts, (2) analyze existing defense strategies, and (3)
design and evaluate new defense strategies. From an educational perspective,
the project will (1) involve graduate students and expose them to leading-edge
researches, and (2) incorporate research results into classrooms. In addition,
the project will provide a platform for active collaborations among a broader
set of researchers of the two institutions. The results from this project will
have a positive impact on protecting user privacy and on people's willingness to
adopt LBS in enhancing their living and working conditions. Research results
will be disseminated through technical reports, publications at conferences and
journals, and the websites at
http://csis.gmu.edu/NSFLBSprivacy and at
http://www.cs.uvm.edu/~xywang/NSFLBSprivacy.