Private Structured-Subset Retrieval
Maha Issa, Anoosheh Heidarzadeh

TL;DR
This paper introduces the Private Structured-Subset Retrieval (PSSR) problem, generalizing MPIR to structured demand families, and develops schemes that optimize retrieval rate and subpacketization, outperforming existing methods.
Contribution
It formulates PSSR, derives bounds, and provides an optimization framework for constructing efficient schemes tailored to structured demand families.
Findings
PSSR schemes can achieve higher rates than traditional MPIR.
The framework reduces subpacketization levels for structured demands.
Specialized schemes outperform existing MPIR schemes in examples.
Abstract
We introduce the \emph{Private Structured-Subset Retrieval (PSSR)} problem, where a user retrieves messages from a database of messages replicated across non-colluding servers, and the demand is restricted to a known structured family of -subsets. This formulation generalizes Multi-message Private Information Retrieval (MPIR) and captures settings where the demand space is constrained by application-specific structure. Focusing on balanced -linear schemes, a class that includes several best-known MPIR schemes, we derive converse bounds on the maximum retrieval rate and minimum subpacketization level required to achieve any given rate. We also develop an optimization-based framework to construct schemes for general structured demand families, providing flexibility in optimizing the retrieval rate or the subpacketization level. When specialized to the full demand…
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