Weakly Private Information Retrieval Under the Maximal Leakage Metric

Zhou, Ruida; Guo, Tao; Tian, Chao

doi:10.1109/isit44484.2020.9174334

Cited by 21 publications

(19 citation statements)

References 13 publications

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“…where indicates the amount of information leakage allowance. Also in [18], the maximal leakage metric is proposed as a measure of information leakage defined as…”

Section: B Information Leakage In Pirmentioning

confidence: 99%

“…Since then, many studies on PIR have been actively conducted for diverse assumptions and environments [3]- [12]. Among the several derivatives of the classical PIR, recent studies [13]- [18] investigated information leakage in PIR problems in order to achieve lower communication costs. We refer to such PIR scenarios as weakly PIR (WPIR).…”

Section: Introductionmentioning

confidence: 99%

“…In [15]- [17], they proposed the mutual information or the maximal leakage metric as an information leakage measure. Also in [18] independently, a weakly PIR problem is formulated with the maximal leakage metric by taking into account the Tian-Sun-Chen (TSC) scheme [11]. In such studies with information leakage, privacy is relaxed in exchange for the improved download cost.…”

Section: Introductionmentioning

confidence: 99%

“…The problem is reduced to equivalent Rényi entropy maximization with arbitrary order. Interestingly, the optimal solution to minimize the Rényi divergence (i.e., maximize the Rényi entropy) turns out to be the same as the optimum solution to minimize the maximum leakage if we adopt the TSC scheme as in [18].…”

Section: Introductionmentioning

confidence: 99%

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Weakly Private Information Retrieval Under Rényi Divergence

Tak¹,

Kim²,

Kim³

et al. 2021

Preprint

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Private information retrieval (PIR) is a protocol that guarantees the privacy of a user who is in communication with databases. The user wants to download one of the messages stored in the databases while hiding the identity of the desired message. Recently, the benefits that can be obtained by weakening the privacy requirement have been studied, but the definition of weak privacy needs to be elaborated upon. In this paper, we attempt to quantify the weak privacy (i.e., information leakage) in PIR problems by using the Rényi divergence that generalizes the Kullback-Leibler divergence. By introducing Rényi divergence into the existing PIR problem, the tradeoff relationship between privacy (information leakage) and PIR performance (download cost) is characterized via convex optimization. Furthermore, we propose an alternative PIR scheme with smaller message sizes than the Tian-Sun-Chen (TSC) scheme. The proposed scheme cannot achieve the PIR capacity of perfect privacy since the message size of the TSC scheme is the minimum to achieve the PIR capacity. However, we show that the proposed scheme can be better than the TSC scheme in the weakly PIR setting, especially under a low download cost regime.

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“…where indicates the amount of information leakage allowance. Also in [18], the maximal leakage metric is proposed as a measure of information leakage defined as…”

Section: B Information Leakage In Pirmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Weakly Private Information Retrieval Under Rényi Divergence

Tak¹,

Kim²,

Kim³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…In [18], an exact expression for the WPIR capacity in the single server scenario was derived using both mutual information and maximal leakage (MaxL) [21], [22] as a privacy metric. Recently, the multi-server WPIR problem under the MaxL metric has also been studied in [23], [24].…”

Section: Introductionmentioning

confidence: 99%

Optimal Rate-Distortion-Leakage Tradeoff for Single-Server Information Retrieval

Yakimenka¹,

Lin²,

Rosnes³

et al. 2021

Preprint

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Private information retrieval protocols guarantee that a user can privately and losslessly retrieve a single file from a database stored across multiple servers. In this work, we propose to simultaneously relax the conditions of perfect retrievability and privacy in order to obtain improved download rates when all files are stored uncoded on a single server. Information leakage is measured in terms of the average success probability for the server of correctly guessing the identity of the desired file. The main findings are: i) the derivation of the optimal tradeoff between download rate, distortion, and information leakage when the file size is infinite. Closed-form expressions of the optimal tradeoff for the special cases of "no-leakage" and "no-privacy" are also given. ii) A novel approach based on linear programming (LP) to construct schemes for a finite file size and an arbitrary number of files. The proposed LP approach can be leveraged to find provably optimal schemes with corresponding closedform expressions for the rate-distortion-leakage tradeoff when the database contains at most four bits. Finally, for a database that contains 320 bits, we compare two construction methods based on the LP approach with a nonconstructive scheme downloading subsets of files using a finite-length lossy compressor based on random coding.

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