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Deim Seminar


[Rescheduled] Privacy in Distributed Networks: Information Theory vs. Estimation Theory


Shabab Asoodeh

Professor/a organitzador/a

Josep Domingo-Ferrer


Queen's University, Canada


18-07-2016 11:00


Motivated by applications in social networks, we talk about different measures of privacy and utility using information-theoretic and estimation-theoretic quantities. Informally, we define privacy and utility as the amount of information that is leaked into the "displayed data" about the "private data" and "non-private data", respectively. We then formulate the underlying conflict between utility and privacy by introducing the "privacy-utility function" and also "estimation noise-to-signal ratio". Despite their intuitive definitions, these two functions have the following shortcomings; (1) they are very difficult to be computed, unless the joint distribution of private data and non-private data satisfies a notion of symmetry, and (2) they lack information-theoretic "operational" interpretations. Then to (partially) overcome these problems, we propose a new privacy-utility tradeoff which is both intuitive and information-theoretically operational when both private and non-private data have discrete distributions. We then talk about the properties of this new quantity and show how this generalizes the previous results in this area.


Laboratori 231