ArXiv TLDR

Local Private Information Retrieval: A New Privacy Perspective for Graph-Based Replicated Systems

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2605.10872

Shreya Meel, Mohamed Nomeir, Sennur Ulukus

cs.ITcs.CRcs.NIeess.SP

TLDR

This paper introduces "local PIR" for graph-replicated systems, showing significant communication efficiency gains by redefining user privacy.

Key contributions

  • Introduces "local user privacy" for graph-replicated PIR, where privacy is conditional on server storage.
  • Shows multiplicative gain in local PIR capacity for disjoint union graphs over canonical PIR.
  • Achieves improved capacity lower bounds for edge-transitive and bipartite connected graphs.
  • Derives exact local PIR capacity for cyclic graphs and path graphs with an odd number of vertices.

Why it matters

This work offers a new privacy paradigm for PIR systems, significantly boosting communication efficiency. By relaxing privacy constraints based on server storage, it enables more practical and scalable data retrieval. This could lead to more efficient and deployable private data access solutions.

Original Abstract

We rethink the definition of privacy in multi-server, graph-replicated private information retrieval (PIR) systems, and introduce a novel setting where the user's privacy is governed by the servers' storage structure. In particular, while retrieving a message from a server, the user is concerned with hiding their desired message index from the server, only if the server stores the corresponding message. We coin this privacy requirement as local user privacy and the resulting PIR problem as local PIR on the graph. Our goal is to measure the gain in communication efficiency of local PIR, compared to that of canonical PIR, by establishing its capacity, i.e., the maximum number of message symbols retrieved, per downloaded symbol. To this end, we observe a remarkable gain in the local PIR capacity of graphs, that are disjoint union of distinct graphs, which is multiplicative, compared to the PIR capacity, when the individual graphs are identical. For connected graphs, we propose schemes to establish capacity lower bounds for edge-transitive and bipartite graphs, which are greater than the best-known PIR capacity bounds. Finally, we derive the exact local PIR capacity for the cyclic graph, and the path graph with an odd number of vertices.

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