Distributed Function Computation Under Privacy Constraints

Details Distributed Function Computation Under Privacy Constraints Distributed Function Computation Under Privacy Constraints

2012-04-11

arxiv.org/abs/1204.2518v1

Computer Science

Information Theory

Submitted to IEEE JSAC: In-Network Computation: Exploring the Fundamental Limits

Scientific paper

A set of terminals observe correlated data and seek to compute functions of the data using interactive public communication. At the same time, it is required that the value of a private function of the data remains concealed from an eavesdropper observing this communication. In general, the private function and the functions computed by the nodes can be all different. We show that a class of functions are securely computable if and only if the conditional entropy of data given the value of private function is greater than the least rate of interactive communication required for a related multiterminal source-coding task. A single-letter formula is provided for this rate in special cases.

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