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Protecting Image Copyrights Based on the AUL Algorithm and Blockchain

  • Qianyi Zhan,
  • Yuanyuan Liu

摘要

With the advent of the digital age, the copyright protection of images is facing increasingly complex challenges, creating new problems for creators. This paper aims to address this challenge by proposing a solution based on deep learning and blockchain technology. First, we introduce an AUL plagiarism detection algorithm that demonstrates its excellent performance in various image tampering scenarios through extensive experiments. According to the experiments, the AUL algorithm outperforms traditional machine learning algorithms and other deep learning methods in terms of comprehensive performance, achieving an accuracy rate of 95.451% and a recall rate of 99.101%. In addition, we integrate blockchain technology with IPFS to utilize their advantages in information protection to provide innovative solutions for image copyright protection.