With the growing popularity of mobile devices that have sophisticated localization capability, it becomes more convenient and tempting to give away location data in exchange for recognition and status in the social networks. Geosocial networks, as an example, offer the ability to notify a user or trigger a service when a friend is within geographical proximity. In this paper, we present two methods to support secure distance computation on encrypted location data; that is, computing distance functions without knowing the actual coordinates of users. The underlying security is ensured by the homomorphic encryption scheme which supports computation on encrypted data. We demonstrate feasibility of the proposed approaches by conducting various performance evaluations on platforms with different specifications. We argue that the novelty of this work enables a new breed of pervasive and mobile computing concepts, which was previously not possible due to the lack of feasible mechanisms that support computation on encrypted location data.

Date of creation, presentation, or exhibit



Presented at the 2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), Fourth International Workshop on Security and Privacy in Big Data, San Francisco, CA, April 10-14, 2016

Document Type

Conference Paper

Department, Program, or Center

Computer Science (GCCIS)


RIT – Main Campus