To ensure the image security, a large number of ciphertext image retrieval methods have been studied and applied, such as homomorphic encryption and multi-key encryption. However, most of these algorithms do not consider the protection of image copyright, user information and traitor tracking. For this reason, this paper proposes a privacy-preserving and traitor tracking content-based image retrieval scheme in cloud computing. This method introduces the DenseNet network to strengthen statistical features. One-way hash algorithm and XOR operation are used to protect copyright and user information, and reversible information hiding algorithm is accessed for traitor tracking. Experimental results show that compared with other algorithms that support leak tracking, our method achieves higher retrieval precision, higher retrieval efficiency and simpler architecture.

为了确保图像的安全性，已经研究并应用了许多密文图像检索方法，例如同态加密和多密钥加密。但是，大多数这些算法都没有考虑保护图像版权，用户信息和叛徒追踪。为此，本文提出了一种基于隐私和叛逆者跟踪内容的云计算图像检索方案。此方法引入了DenseNet网络以增强统计功能。使用单向哈希算法和XOR操作来保护版权和用户信息，并访问可逆信息隐藏算法以进行叛徒跟踪。实验结果表明，与其他支持泄漏跟踪的算法相比，我们的方法具有更高的检索精度，