Improved Storage for Efficient Private Information Retrieval
This work addresses efficient data retrieval with privacy guarantees for users accessing distributed databases, presenting an incremental improvement over existing schemes.
The paper tackles the problem of private information retrieval from storage-constrained databases by characterizing the optimal tradeoff between storage cost and download cost, showing that a hybrid scheme combining MDS coding and uncoded partial replication reduces download costs compared to prior methods.
We consider the problem of private information retrieval from $N$ \emph{storage-constrained} databases. In this problem, a user wishes to retrieve a single message out of $M$ messages (of size $L$) without revealing any information about the identity of the message to individual databases. Each database stores $μML$ symbols, i.e., a $μ$ fraction of the entire library, where $\frac{1}{N} \leq μ\leq 1$. Our goal is to characterize the optimal tradeoff curve for the storage cost (captured by $μ$) and the normalized download cost ($D/L$). We show that the download cost can be reduced by employing a hybrid storage scheme that combines \emph{MDS coding} ideas with \emph{uncoded partial replication} ideas. When there is no coding, our scheme reduces to Attia-Kumar-Tandon storage scheme, which was initially introduced by Maddah-Ali-Niesen in the context of the caching problem, and when there is no uncoded partial replication, our scheme reduces to Banawan-Ulukus storage scheme; in general, our scheme outperforms both.