k-symmetry model for identity anonymization in social networks

With more and more social network data being released, protecting the sensitive information within social networks from leakage has become an important concern of publishers. Adversaries with some background structural knowledge about a target individual can easily re-identify him from the network, even if the identifiers have been replaced by randomized integers(i.e., the network is naively-anonymized). Since there exists numerous topological information that can be used to attack a victim’s privacy, to resist such structural re-identification becomes a great challenge. Previous works only investigated a minority of such structural attacks, without considering protecting against re-identification under any potential structural knowledge about a target. To achieve this objective, in this paper we propose

• Type: Conference
• Year: 2010
• Where: EDBT
• Authors: Wentao Wu, Yanghua Xiao, Wei Wang, Zhenying He, Zhihui Wang
• Keywords: Database, EDBT 2010, Original Network, Social Networks, Structural Knowledge