2010 IEEE 26th International Conference on Data Engineering (ICDE 2010) (2010)
Long Beach, CA, USA
Mar. 1, 2010 to Mar. 6, 2010
Ting Wang , College of Computing, Georgia Institute of Technology, USA
Ling Liu , College of Computing, Georgia Institute of Technology, USA
As a severe threat in anonymized data publication, proximity breach is gaining increasing attention. Such breach occurs when an attacker learns with high confidence that the sensitive information of a victim associates with a set of semantically proximate values, even though not sure about the exact one. Recently (∈, δ)-dissimilarity  has been proposed as an effective countermeasure against general proximity attack. In this paper, we present a detailed analytical study on the fulfillment of this principle, derive criteria to efficiently test its satisfiability for given microdata, and point to a novel anonymization model, XCOLOR, with theoretical guarantees on both operation efficiency and utility preservation.
L. Liu and T. Wang, "XColor: Protecting general proximity privacy," 2010 IEEE 26th International Conference on Data Engineering (ICDE 2010)(ICDE), Long Beach, CA, USA, 2010, pp. 960-963.