XColor: Protecting General Proximity Privacy

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 ( , )-dissimilarity [14] 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.

• Type: Conference
• Year: 2010
• Where: ICDE
• Authors: Ting Wang, Ling Liu
• Keywords: Database, General Proximity Attack, ICDE 2010, Proximity Breach, Such Breach