Abstract
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.










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Acknowledgements
This work was supported in part by the National Natural Science Foundation of China under Grant 61772561, in part by the Science Research Projects of Hunan Provincial Education Department under Grant 18A174, 19B584 and 18C0262, in part by the Key Research and Development Plan of Hunan Province under Grant 2019SK2022, in part by the Natural Science Foundation of Hunan Province under Grant 2020JJ4140 and 2020JJ4141, in part by the Degree and Postgraduate Education Reform Project of Hunan Province under Grant 2019JGYB154, and in part by the Postgraduate Excellent teaching team Project of Hunan Province under Grant [2019]370-133.
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Wang, Z., Qin, J., Xiang, X. et al. A privacy-preserving and traitor tracking content-based image retrieval scheme in cloud computing. Multimedia Systems 27, 403–415 (2021). https://doi.org/10.1007/s00530-020-00734-w
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DOI: https://doi.org/10.1007/s00530-020-00734-w