Blockchain-based Data Trading Platform for Anti-Resale with Zero-Knowledge Proof and Block-Based Watermarking

Abstract

In blockchain-based data trading platforms, the illegal resale of image data has led to serious copyright infringement issues. Traditional protective measures typically rely on embedding digital watermarks into images to verify data ownership and integrity. However, to ensure the correctness of the watermark embedding process, the embedded results need to be verified. Existing zero-knowledge proof schemes like Groth16 offer efficient verification but are limited in practical applications due to the high computational costs associated with the trusted setup phase required for third-party computations. To address this issue, this paper proposes a watermark embedding and verification mechanism based on block-based processing. By partitioning the image and embedding the watermark incrementally, the time required for the trusted setup and zkey generation in zero-knowledge proofs is significantly reduced, thereby improving the overall efficiency of proof generation. Experimental results show that after partitioning, the total proof generation time is reduced to 24.274% of that in the unpartitioned case. This demonstrates that the proposed method significantly reduces proof generation time, making it more efficient for large-scale image data transactions in blockchain environments.