Title :
Preserving Relation Privacy in Online Social Network Data
Author :
Li, Na ; Zhang, Nan ; Das, Sajal K.
Author_Institution :
Univ. of Texas at Arlington, Arlington, TX, USA
Abstract :
Online social networks routinely publish data of interest to third parties, but in so doing often reveal relationships, such as a friendship or contractual association, that an attacker can exploit. This systematic look at existing privacy-preservation techniques highlights the vulnerabilities of users even in networks that completely anonymize identities. Through a taxonomy that categorizes techniques according to the degree of user identity exposure, the authors examine the ways that existing approaches compromise relation privacy and offer more secure alternatives.
Keywords :
data privacy; social networking (online); contractual association; online social network data; privacy preservation techniques; relation privacy; user identity exposure; Data privacy; Electronic mail; Loss measurement; Privacy; Publishing; Social network services; Topology; Keywords: relation privacy; online social networks; user privacy; utility loss.;
Journal_Title :
Internet Computing, IEEE
DOI :
10.1109/MIC.2011.26