2008 Third International Conference on Availability, Reliability and Security
A Post-processing Method to Lessen k-Anonymity Dissimilarities
March 04-March 07
ISBN: 978-0-7695-3102-1
Protecting personal data is essential to guarantee the rule of law\footnote{We use the term rule of law to referto the \textit{Rechtsstaat} as a concept borrowed from German jurisprudence. It is a state in which the exercise of governmental power is constrained by the law. It is a foundational rule for a country to be a liberal democracy.}.Due to the new Information and Communication Technologies (ICTs) unprecedented amounts of personal datacan be stored and analysed. Thus, if the proper measures are not taken, individual privacy could be in jeopardy. Being the aim to protect individual privacy, a great variety of statistical disclosure control (SDC) techniques has been proposed. Amongst many others, k-anonymity is a promising property that, if properly achieved, can help protect individual privacy. In this paper, we propose a new post-processing method that can be applied after a k-anonymity algorithm, being the aim to lessen the errors resulting from the aggregation of data. We show that our method can be extended to work with many other SDC techniques and we provide some experimental results which emphasise the usefulness of our proposal.
Index Terms:
Privacy, Security, k-anonymity, micro-aggreagtion
Citation:
Agusti Solanas, Gloria Pujol, Antoni Martinez-Balleste, Josep M. Mateo-Sanz, "A Post-processing Method to Lessen k-Anonymity Dissimilarities," ares, pp.1060-1066, 2008 Third International Conference on Availability, Reliability and Security, 2008