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Erschienen in:
2011 | OriginalPaper | Buchkapitel
An Accurate System-Wide Anonymity Metric for Probabilistic Attacks
verfasst von : Rajiv Bagai, Huabo Lu, Rong Li, Bin Tang
Erschienen in: Privacy Enhancing Technologies
Verlag: Springer Berlin Heidelberg
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We give a critical analysis of the system-wide anonymity metric of Edman et al. [3], which is based on the permanent value of a doubly-stochastic matrix. By providing an intuitive understanding of the permanent of such a matrix, we show that a metric that looks no further than this composite value is at best a rough indicator of anonymity. We identify situations where its inaccuracy is acute, and reveal a better anonymity indicator. Also, by constructing an information-preserving embedding of a smaller class of attacks into the wider class for which this metric was proposed, we show that this metric fails to possess desirable generalization properties. Finally, we present a new anonymity metric that does not exhibit these shortcomings. Our new metric is accurate as well as general.