College of Computer Science and Engineering, Dalian Minzu University, Dalian, China.
PLoS One. 2024 Sep 19;19(9):e0309743. doi: 10.1371/journal.pone.0309743. eCollection 2024.
The unauthorized replication and distribution of digital images pose significant challenges to copyright protection. While existing solutions incorporate blockchain-based techniques such as perceptual hashing and digital watermarking, they lack large-scale experimental validation and a dedicated blockchain consensus protocol for image copyright management. This paper introduces DRPChain, a novel digital image copyright management system that addresses these issues. DRPChain employs an efficient cropping-resistant robust image hashing algorithm to defend against 14 common image attacks, demonstrating an 85% success rate in watermark extraction, 10% higher than the original scheme. Moreover, the paper designs the K-Raft consensus algorithm tailored for image copyright protection. Comparative experiments with Raft and benchmarking against PoW and PBFT algorithms show that K-Raft reduces block error rates by 2%, improves efficiency by 300ms compared to Raft, and exhibits superior efficiency,decentralization, and throughput compared to PoW and PBFT. These advantages make K-Raft more suitable for digital image copyright protection. This research contributes valuable insights into using blockchain technology for digital copyright protection, providing a solid foundation for future exploration.
未经授权的复制和分发数字图像对版权保护构成了重大挑战。虽然现有的解决方案采用了基于区块链的技术,如感知哈希和数字水印,但它们缺乏大规模的实验验证,并且缺乏用于图像版权管理的专用区块链共识协议。本文介绍了 DRPChain,这是一种新颖的数字图像版权管理系统,解决了这些问题。DRPChain 采用高效的抗裁剪鲁棒图像哈希算法来抵御 14 种常见的图像攻击,在水印提取方面的成功率达到 85%,比原始方案高出 10%。此外,本文还设计了专门用于图像版权保护的 K-Raft 共识算法。与 Raft 的对比实验以及与 PoW 和 PBFT 算法的基准测试表明,K-Raft 降低了 2%的块错误率,与 Raft 相比提高了 300ms 的效率,并且在效率、去中心化和吞吐量方面都优于 PoW 和 PBFT。这些优势使得 K-Raft 更适合数字图像版权保护。这项研究为使用区块链技术进行数字版权保护提供了有价值的见解,为未来的探索奠定了基础。