Title: Privacy preserving data obfuscation for inherently clustered data

Authors: Rupa Parameswaran, Douglas M. Blough

Addresses: School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA. ' School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA

Abstract: Privacy is defined as the freedom from unauthorised intrusion. The availability of public records along with intelligent search engines and data mining tools allow easy access to useful information. They also serve as a haven for individuals with malicious intent. This paper proposes an approach that protects the privacy of individual records while retaining the information content. The techniques that have been proposed for privacy protection so far either provide insufficient privacy or too much useful information on account of privacy protection. This paper proposes an attack model to analyse the different types of privacy breaches, proposes a set of properties for good privacy protection, proposes a robust data protection technique, and compares the privacy and usability properties of the new technique with some of the existing techniques.

Keywords: privacy protection; data perturbation; attack models; data randomisation; data obfuscation; anonymity; collaborative filtering; privacy preservation; data mining; information security; computer security; clustered data; data protection.

DOI: 10.1504/IJICS.2008.016819

International Journal of Information and Computer Security, 2008 Vol.2 No.1, pp.4 - 26

Published online: 24 Jan 2008 *

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