Achieving Maximum Distance Separable Private Information Retrieval Capacity With Linear Codes
Siddhartha Kumar, Hsuan-Yin Lin, Eirik Rosnes, Alexandre, Graell i Amat

TL;DR
This paper introduces three PIR protocols for distributed storage systems using linear codes, achieving maximum distance separable capacity with various code classes and scenarios, including colluding nodes.
Contribution
It proposes new PIR protocols that attain MDS-PIR capacity for arbitrary linear codes and provides conditions and code classes that achieve optimal rates.
Findings
Protocols achieve maximum PIR capacity with MDS and certain linear codes.
Conditions identified for codes to reach PIR capacity.
RM and cyclic codes achieve optimal PIR rates in proposed protocols.
Abstract
We propose three private information retrieval (PIR) protocols for distributed storage systems (DSSs) where data is stored using an arbitrary linear code. The first two protocols, named Protocol 1 and Protocol 2, achieve privacy for the scenario with noncolluding nodes. Protocol 1 requires a file size that is exponential in the number of files in the system, while Protocol 2 requires a file size that is independent of the number of files and is hence simpler. We prove that, for certain linear codes, Protocol 1 achieves the maximum distance separable (MDS) PIR capacity, i.e., the maximum PIR rate (the ratio of the amount of retrieved stored data per unit of downloaded data) for a DSS that uses an MDS code to store any given (finite and infinite) number of files, and Protocol 2 achieves the asymptotic MDS-PIR capacity (with infinitely large number of files in the DSS). In particular, we…
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Taxonomy
TopicsAdvanced Data Storage Technologies · Cryptography and Data Security · Privacy-Preserving Technologies in Data
