Paper 2024/1775

zkMarket : Privacy-preserving Digital Data Trade System via Blockchain

Abstract

Ensuring fairness in blockchain-based data trading presents significant challenges, as the transparency of blockchain can expose sensitive details and compromise fairness. Fairness ensures that the seller receives payment only if they provide the correct data, and the buyer gains access to the data only after making the payment. Existing approaches face limitations in efficiency particularly when applied to large-scale data. Moreover, preserving privacy has also been a significant challenge in blockchain. In this paper, we introduce zkMarket, a privacy-preserving fair trade system on the blockchain. we make the data registration process more concise and improve the seller's proving time by leveraging our novel pseudorandom generator named matrix-formed PRG (MatPRG), and existing commit-and-prove SNARK (CP-SNARK). To ensure transaction privacy, zkMarket is built upon an anonymous transfer protocol. By combining encryption with zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARK), both the seller and the buyer are enabled to trade fairly. Experimental results demonstrate that zkMarket significantly reduces the computational overhead associated with traditional blockchain solutions while maintaining robust security and privacy. Our evaluation demonstrates that zkMarket achieves high efficiency while maintaining robust security and privacy. The seller can register 1MB of data in 2.8 seconds, the buyer can generate the trade transaction in 0.2 seconds, and the seller can finalize the trade within 0.4 seconds.