Sealed-bid Auctions on Blockchain with Timed Commitment Outsourcing
Jichen Li, Yuanchen Tang, Jing Chen, Xiaotie Deng
TL;DR
This work addresses the cost-shared decryption problem in blockchain sealed-bid auctions by introducing a timed commitment outsourcing market with aggregable time-lock commitments. It designs a two-sided mechanism combining a second-price bidder auction with a reserve and a winner-takes-all solver competition, supported by an aggregable timed commitment protocol and a practical blockchain protocol for bid collection, solving, and payment. The authors prove that, within a broad class of mechanisms, the proposed design achieves $DSIC$ and $IR$ for bidders and $BIC$ and $BIR$ for solvers, attaining revenue-optimality for the auctioneer, while showing a fundamental impossibility result for two-sided $DSIC$ with positive revenue. The framework integrates a concrete aggregation technique, incentive analysis, and protocol-level procedures, offering a principled approach to decentralized, verifiable sealed-bid auctions with outsourced cryptographic work and pointing to avenues for future improvements and non-payment-proportional mechanisms.
Abstract
Sealed-bid auctions play a crucial role in blockchain ecosystems. Previous works introduced viable blockchain sealed-bid auction protocols, leveraging timed commitments for bid encryption. However, a crucial challenge remains unresolved in these works: Who should bear the cost of decrypting these timed commitments? This work introduces a timed commitment outsourcing market as a solution to the aforementioned challenge. We first introduce an aggregation scheme for timed commitments, which combines all bidders' timed commitments into one while ensuring security and correctness and allowing a varying number of bidders. Next, we remodel the utility of auctioneers and timed commitment solvers, developing a new timed commitment competition mechanism and combining it with the sealed-bid auction to form a two-sided market. The protocol includes bid commitment collection, timed commitment solving, and payment. Through game-theoretical analysis, we prove that our protocol satisfies Dominant Strategy Incentive Compatibility (DSIC) for bidders, Bayesian Incentive Compatibility (BIC) for solvers, and achieves optimal revenue for the auctioneer among a large class of mechanisms. Finally, we prove that no mechanism can achieve positive expected revenue for the auctioneer while satisfying DSIC and Individual Rationality (IR) for both bidders and solvers.