Private Information Retrieval From MDS Coded Data in Distributed Storage Systems

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IEEE Transactions on Information Theory · 2018 · 132 citations · 22 references

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TL;DR

Private information retrieval in distributed storage systems protects user queries from spy nodes, but naïve solutions that download all data are prohibitively costly. The authors aim to design PIR schemes that minimize download cost. They propose universal, information‑theoretic PIR schemes that depend only on the MDS code rate and reveal no query information to spy nodes. For a single spy node the schemes achieve the optimal download cost of 1/(1‑R), and for up to n‑δk spies they attain a communication cost of (b+δk)/δ per unit of data.

Abstract

The problem of providing privacy, in the private information retrieval (PIR) sense, to users requesting data from a distributed storage system (DSS), is considered. The DSS is coded by an $(n,k,d)$ Maximum Distance Separable (MDS) code to store the data reliably on unreliable storage nodes. Some of these nodes can be spies which report to a third party, such as an oppressive regime, which data is being requested by the user. An information theoretic PIR scheme ensures that a user can satisfy its request while revealing, to the spy nodes, no information on which data is being requested. A user can trivially achieve PIR by downloading all the data in the DSS. However, this is not a feasible solution due to its high communication cost. We construct PIR schemes with low download communication cost. When there is $b=1$ spy node in the DSS, we construct PIR schemes with download cost $\frac{1}{1-R}$ per unit of requested data ($R=k/n$ is the code rate), achieving the information theoretic limit for linear schemes. The proposed schemes are universal since they depend on the code rate, but not on the generator matrix of the code. Also, when $b\leq n-\delta k$, for some $\delta \in \mathbb{N^+}$, we construct linear PIR schemes with $cPoP = \frac{b+\delta k}{\delta}$.

References

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