Article history: Received 27 April 2010 Received in revised form 21 June 2011 Accepted 21 June 2011 Available online 2 July 2011 We present a multidisciplinary solution to the problems of anonymous microaggregation and clustering, illustrated with two applications, namely privacy protection in databases, and private retrieval of location-based information. Our solution is perturbative, is based...

DEFINITION Spatial cloaking is a technique to blur a user’s exact location into a spatial region in order to preserve her location privacy. The blurred spatial region must satisfy the user’s specified privacy requirement. The most widely used privacy requirements are k-anonymity and minimum spatial area. The k-anonymity requirement guarantees that a user location is indistinguishable among k us...

Trajectories of mobile objects, are automatically collected in huge quantities. Publishing and exploiting such data is essential to improve planning, but it threatens the privacy of individuals: re-identification of the individual behind a trajectory is easy unless precautions are taken. We present two heuristics for privacy-preserving publication of trajectories. Both of them publish only true...

The data mining figures out accurate information for requesting user after the raw data is analyzed. Among lots of developments, data mining face hot issues on security, privacy and integrity. Data mining use one of the latest technique called privacy preserving data publishing (PPDP), which enforces security for the digital information provided by governments, corporations, companies and indiv...

Location based services (LBS) aim to deliver information based on a mobile user’s location. However, knowledge of the location can be used by an adversary to physically locate the person, leading to the risk of physical harm, as well as possible leakage of certain personal information. This has serious consequences on privacy. The concept of location kanonymity has been proposed to address this...

Originally K-anonymity principle was first used in relational databases to tackle the problem of data anonymity. In earlier protection techniques K threshold is used as personalization factor for mobile users. In case, K users are not present around needy client mobile user, query can be delayed and thus it will not help to achieve the Quality of service parameter. Moreover, authors have adopte...

Motivated by a strongly growing interest in graph anonymization, we study the NP-hard Degree Anonymity problem asking whether a graph can be made k-anonymous by adding at most a given number of edges. Herein, a graph is k-anonymous if for every vertex in the graph there are at least k−1 other vertices of the same degree. Our algorithmic results shed light on the performance quality of a popular...