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POISIDD: privacy-preserving outsourced image sharing scheme with illegal distributor detection in cloud computing

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Abstract

Privacy-preserving outsourced image sharing schemes can help relieve the local storage of image owners and protect images’ privacy by sending encrypted images to receivers, but they cannot prevent the decrypted image from being illegally distributed by illegal distributors. To cope with this issue, we propose a privacy-preserving image sharing scheme with illegal distributor detection (POISIDD). POISIDD embeds the authentication information of image receiver in the encrypted form based on discrete cosine transform (DCT) and privacy-preserving outsourced calculation on floating point numbers (POCF) . Moreover, in order to prevent all operations from being carried out by the single cloud which may lead to privacy disclosure, we adopt two platforms (Storage Center and Authentication Center) to achieve the embedding of authentication information(AI) by the communications between them. Furthermore, in order to better defend against attackers, we generate random vectors based on the original AI and use them instead of the AI as the embedded data. The aim of identifying illegal distributor will be achieved with the help of Authentication Center. The scheme is secure under the defined attack model, and its robustness under different attacks has been shown by experiments.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (No.61872090, No.61872086).

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Authors and Affiliations

  1. College of Computer and Cyber Security, Fujian Normal University, Fuzhou, 350117, China

    Tianpeng Deng, Xuan Li, Jinbo Xiong & Ying Wu

  2. Fujian Provincial Key Laboratory of Network Security and Cryptology, Fuzhou, 350117, China

    Xuan Li & Jinbo Xiong

  3. Digital Fujian Big Data Security Technology Institute, Fuzhou, 350117, China

    Xuan Li

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  1. Tianpeng Deng
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  2. Xuan Li
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  3. Jinbo Xiong
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  4. Ying Wu
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We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted.

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Deng, T., Li, X., Xiong, J. et al. POISIDD: privacy-preserving outsourced image sharing scheme with illegal distributor detection in cloud computing. Multimed Tools Appl 81, 3693–3714 (2022). https://doi.org/10.1007/s11042-021-11737-8

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  • DOI: https://doi.org/10.1007/s11042-021-11737-8

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