A privacy-preserving and traitor tracking content-based image retrieval scheme in cloud computing

• Published in: Multimedia systems 2021-06, Vol.27 (3), p.403-415
• Main Authors: Wang, Zhangdong, Qin, Jiaohua, Xiang, Xuyu, Tan, Yun
• Format: Article
• Language: English
• Subjects: Algorithms; Cloud computing; Computer Communication Networks; Computer Graphics; Computer Science; Cryptology; Data Storage Representation; Encryption; Image management; Image retrieval; Low Complexity Methods for Multimedia Security; Operating Systems; Privacy; Special Issue Paper; Tracking
• ISSN: 0942-4962; 1432-1882
• DOI: 10.1007/s00530-020-00734-w

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.