Sun-Jafar-Type Schemes for Weak Private Information Retrieval

TL;DR

This paper introduces Weak Private Information Retrieval (WPIR) schemes that relax perfect privacy constraints to achieve higher data retrieval rates, leveraging and extending existing PIR schemes for various server collusion scenarios and privacy metrics.

Contribution

The paper develops new WPIR protocols based on Sun-Jafar schemes for different collusion scenarios and introduces a novel scheme for the MDS case, providing explicit rate-privacy trade-offs under multiple privacy metrics.

Findings

Achieves higher rates by relaxing privacy constraints.

Provides explicit rate-privacy trade-offs for multiple scenarios.

Demonstrates improved performance in MDS case under certain metrics.

Abstract

In information-theoretic private information retrieval (PIR), a client wants to retrieve one desired file out of $M$ files, stored across $N$ servers, while keeping the index of the desired file private from each $T$-sized subset of servers. A PIR protocol must ideally maximize the rate, which is the ratio of the file size to the total quantum of the download from the servers, while ensuring such privacy. In Weak-PIR (WPIR), the criterion of perfect information-theoretic privacy is relaxed. This enables higher rates to be achieved, while some information about the desired file index leaks to the servers. This leakage is captured by various known privacy metrics. By leveraging the well-established capacity-achieving schemes of Sun and Jafar under non-colluding ($T=1$) and colluding ($1<T\leq N$) scenarios, we present WPIR protocols for these scenarios. We also present a new WPIR scheme for the MDS scenario, by building upon the scheme by Banawan and Ulukus for this scenario. We present corresponding explicit rate-privacy trade-offs for these setups, under the mutual-information and the maximal leakage privacy metrics. In the collusion-free setup, our presented rate-privacy trade-off under maximal leakage matches that of the previous state of the art. With respect to the MDS scenario under the maximal leakage metric, we compare with the non-explicit trade-off in the literature, and show that our scheme performs better for some numerical examples. For the $T$-collusion setup (under both privacy metrics) and for the MDS setup under the mutual information metric, our rate-privacy trade-offs are the first in the literature, to the best of our knowledge.