Private Function Retrieval
Mahtab Mirmohseni, Mohammad Ali Maddah-Ali

TL;DR
This paper introduces the private function retrieval (PFR) problem, analyzing its fundamental communication limits and extending PIR concepts to retrieve linear functions privately from multiple servers.
Contribution
It defines the PFR problem, derives its capacity for two servers, and generalizes the scheme to multiple servers with arbitrary coefficients in GF(q).
Findings
Capacity for two servers with binary coefficients derived.
Extended scheme for multiple servers and arbitrary coefficients.
Achieves minimal communication cost for private function retrieval.
Abstract
The widespread use of cloud computing services raises the question of how one can delegate the processing tasks to the untrusted distributed parties without breeching the privacy of its data and algorithms. Motivated by the algorithm privacy concerns in a distributed computing system, in this paper, we introduce the private function retrieval (PFR) problem, where a user wishes to efficiently retrieve a linear function of messages from non-communicating replicated servers while keeping the function hidden from each individual server. The goal is to find a scheme with minimum communication cost. To characterize the fundamental limits of the communication cost, we define the capacity of PFR problem as the size of the message that can be privately retrieved (which is the size of one file) normalized to the required downloaded information bits. We first show that for the PFR problem…
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