Truth, Justice, and Secrecy: Cake Cutting Under Privacy Constraints
Yaron Salman, Tamir Tassa, Omer Lev, Roie Zivan

TL;DR
This paper introduces the first privacy-preserving cake-cutting protocol that guarantees fairness, strategyproofness, and privacy, using cryptographic techniques to enable truthful preference reporting without exposure.
Contribution
It extends existing strategyproof cake-cutting algorithms by integrating cryptographic methods to ensure privacy, fairness, and strategyproofness simultaneously.
Findings
Protocol is envy-free, strategyproof, and privacy-preserving.
Cryptographic techniques enable secure, fair resource allocation.
First known protocol combining privacy with cake-cutting fairness.
Abstract
Cake-cutting algorithms, which aim to fairly allocate a continuous resource based on individual agent preferences, have seen significant progress over the past two decades. Much of the research has concentrated on fairness, with comparatively less attention given to other important aspects. Chen et al. (2010) introduced an algorithm that, in addition to ensuring fairness, was strategyproof -- meaning agents had no incentive to misreport their valuations. However, even in the absence of strategic incentives to misreport, agents may still hesitate to reveal their true preferences due to privacy concerns (e.g., when allocating advertising time between firms, revealing preferences could inadvertently expose planned marketing strategies or product launch timelines). In this work, we extend the strategyproof algorithm of Chen et al. by introducing a privacy-preserving dimension. To the best…
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Taxonomy
TopicsGame Theory and Voting Systems · Cryptography and Data Security · Auction Theory and Applications
