[Resource Topic] 2024/978: Distributed PIR: Scaling Private Messaging via the Users' Machines

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Distributed PIR: Scaling Private Messaging via the Users’ Machines

Authors: Elkana Tovey, Jonathan Weiss, Yossi Gilad


This paper presents a new architecture for metadata-private messaging that
counters scalability challenges by offloading most computations to the clients.
At the core of our design is a distributed private information retrieval (PIR)
protocol, where the responder delegates its work to alleviate PIR’s
computational bottleneck and catches misbehaving delegates by efficiently
verifying their results. We introduce DPIR, a messaging system that uses
distributed PIR to let a server storing messages delegate the work to the
system’s clients, such that each client contributes proportional processing to
the number of messages it reads. The server removes clients returning invalid
results, which DPIR leverages to integrate an incentive mechanism for honest
client behavior by conditioning messaging through DPIR on correctly processing
PIR requests from other users. The result is a metadata-private messaging system
that asymptotically improves scalability over prior work with the same threat
model. We show through experiments on a prototype implementation that DPIR
concretely improves performance by 3.25\times and 4.31\times over prior
work and that the performance gap grows
with the user base size.

ePrint: https://eprint.iacr.org/2024/978

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