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Cloud Based Image Retrieval Scheme Using Feature Vector

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International Conference on Applications and Techniques in Cyber Security and Intelligence (ATCI 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 580))

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Abstract

With the development of cloud computing, outsourcing storage-more and more people of all ages. Powerful cloud Server provides customers with a great deal of storage space. In order to protect privacy of outsourcing information, customer information must be encrypted, and redaction. However, it is difficult to search for information in the encrypted file. In this paper, we study the encrypted image retrieval technique of outsourcing. An image retrieval based on content encryption scheme is proposed. In this scenario, using blind method based on discrete logarithm problem of eigenvectors to maintain confidentiality and a clever retrieval method is used. This is a dynamic programme, support a fuzzy search. Clients can control the search. During the search, the original image does not leak.

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Acknowledgment

The authors of this paper are members of Shanghai Engineering Research Center of Intelligent Video Surveillance. This work was supported in part the National Natural Science Foundation of China under Grant 61300202, 61332018, 61403084. Our research was sponsored by Program of Science and Technology Commission of Shanghai Municipality (No. 15530701300, 15XD15202000, 16511101700), in part by the technical research program of Chinese ministry of public security (2015JSYJB26).

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Correspondence to Pan Gao .

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Gao, P., Ye, J. (2018). Cloud Based Image Retrieval Scheme Using Feature Vector. In: Abawajy, J., Choo, KK., Islam, R. (eds) International Conference on Applications and Techniques in Cyber Security and Intelligence. ATCI 2017. Advances in Intelligent Systems and Computing, vol 580. Edizioni della Normale, Cham. https://doi.org/10.1007/978-3-319-67071-3_3

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  • DOI: https://doi.org/10.1007/978-3-319-67071-3_3

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  • Publisher Name: Edizioni della Normale, Cham

  • Print ISBN: 978-3-319-67070-6

  • Online ISBN: 978-3-319-67071-3

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