Privacy Consensus in Anonymization Systems Via Game Theory
Date
2012-03-01T18:26:47Z
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Abstract
Privacy protection appears as a fundamental concern when
personal data is collected, stored, and published. Several anonymization
methods have been proposed to protect individuals' privacy before data
publishing. Each anonymization method has at least one parameter to
adjust the level of privacy protection. Choosing a desirable level of privacy
protection is a crucial decision because it affects the volume and
usability of collected data differently. In this paper, we demonstrate how
to use game theory to model different and conflicting needs of parties involved
in making such decision. We describe a general approach to solve
such games and elaborate the procedure using k-anonymity as a sample
anonymization method. Our model provides a generic framework to find
stable values for privacy parameters within each anonymization method,
to recognize the characteristics of each anonymization method, and to
compare different anonymization methods to distinguish the settings that
make one method more appealing than the others.
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Keywords
Game Theory, k-Anonymity