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