Iris: Dynamic Privacy Preserving Search in Structured Peer-to-Peer Networks

• URL: http://arxiv.org/abs/2310.19634v1
• Date: Mon, 30 Oct 2023 15:24:47 GMT
• Title: Iris: Dynamic Privacy Preserving Search in Structured Peer-to-Peer Networks
• Authors: Angeliki Aktypi, Kasper Rasmussen,
• Abstract summary: We study the query privacy of structured P2P networks, particularly the Chord protocol. We introduce a new privacy notion that allows us to evaluate the privacy guarantees even in the presence of a strong adversary. We design Iris, an algorithm that allows a requester to conceal the target of a query in Chord from the intermediate nodes that take part in the routing.
• Score: 1.6114012813668932
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In structured peer-to-peer networks like Chord, the users manage to retrieve the information they seek by asking other nodes from the network for the information they search. Revealing to other nodes the search target makes structured peer-to-peer networks unsuitable for applications that demand query privacy, i.e., hiding the query's target from the intermediate nodes that take part in the routing. This paper studies the query privacy of structured P2P networks, particularly the Chord protocol. We initially observe that already proposed privacy notions, such as $k$-anonymity, do not allow us to reason about the privacy guarantees of a query in Chord in the presence of a strong adversary. Thus, we introduce a new privacy notion that we call $(\alpha,\delta)$-privacy that allows us to evaluate the privacy guarantees even when considering the worst-case scenario regarding an attacker's background knowledge. We then design Iris, an algorithm that allows a requester to conceal the target of a query in Chord from the intermediate nodes that take part in the routing. Iris achieves that by having the requester query for other than the target addresses so as reaching each one of them allows the requester to get closer to the target address. We perform a security analysis of the proposed algorithm, based on the privacy notion we introduce. We also develop a prototype of the algorithm in Matlab and evaluate its performance. Our analysis proves Iris to be $(\alpha,\delta)$-private while introducing a modest performance overhead.

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