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Preserving Relation Privacy in Online Social Network Data

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3 Author(s)
Na Li ; Univ. of Texas at Arlington, Arlington, TX, USA ; Nan Zhang ; Das, S.K.

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.

Published in:

Internet Computing, IEEE  (Volume:15 ,  Issue: 3 )