Preserving Relation Privacy in Online Social Network Data

Authors:
Na Li;Nan Zhang;Sajal Das
Affiliations:
University of Texas at Arlington;George Washington University;University of Texas at Arlington
Venue:
IEEE Internet Computing
Year:
2011

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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.