More is Merrier: Relax the Non-Collusion Assumption in Multi-Server PIR
Tiantian Gong, Ryan Henry, Alexandros Psomas, Aniket Kate

TL;DR
This paper proposes a new approach to multi-server 1-private information retrieval that relaxes the non-collusion assumption by leveraging a large number of servers and incentive mechanisms to deter collusion.
Contribution
It introduces a collusion mitigation mechanism using a public bulletin board and payment functions, extending privacy protection even with rational or malicious servers.
Findings
Collusion resistance increases with more servers available.
Incentive mechanisms effectively deter rational collusion.
Privacy is maintained over an extended period post-query.
Abstract
A long line of research on secure computation has confirmed that anything that can be computed, can be computed securely using a set of non-colluding parties. Indeed, this non-collusion assumption makes a number of problems solvable, as well as reduces overheads and bypasses computational hardness results, and it is pervasive across different privacy-enhancing technologies. However, it remains highly susceptible to covert, undetectable collusion among computing parties. This work stems from an observation that if the number of available computing parties is much higher than the number of parties required to perform a secure computation task, collusion attempts in privacy-preserving computations could be deterred. We focus on the prominent privacy-preserving computation task of multi-server -private information retrieval (PIR) that inherently assumes no pair-wise collusion. For PIR…
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Taxonomy
TopicsCryptography and Data Security · Blockchain Technology Applications and Security · Privacy-Preserving Technologies in Data
