Title :
Enhancing Mobile Social Network Privacy
Author :
Chang, Wei ; Wu, Jie ; Tan, Chiu C.
Author_Institution :
Dept. of Comput. & Inf. Sci., Temple Univ., Philadelphia, PA, USA
Abstract :
Privacy is an important concern for location based services (LBSs). In this paper, we consider a specific type of LBS known as a mobile social network (MSN). We demonstrate a new type of attack, where an adversary can combine the location and friendship information found in a MSN, to violate user privacy. We propose a fake location reporting solution that does not require any additional trusted third party deployment. We use extensive simulations to determine the validity of our scheme.
Keywords :
data privacy; mobile computing; social networking (online); LBS; location based services; mobile social network privacy; Estimation error; Kalman filters; Mutual information; Noise; Privacy; Trajectory;
Conference_Titel :
Global Telecommunications Conference (GLOBECOM 2011), 2011 IEEE
Conference_Location :
Houston, TX, USA
Print_ISBN :
978-1-4244-9266-4
Electronic_ISBN :
1930-529X
DOI :
10.1109/GLOCOM.2011.6133610