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Image Feature Computation in Encrypted Domain Based on Mean Value

by Xiangshu Ou, Mingfang Jiang, Shuai Li, Yao Bai

1 Department of Mathematics and Computational Science, Hunan First Normal University, Changsha, 410205, China
2 Department of Information Science and Engineering, Hunan First Normal University, Changsha, 410205, China

* Corresponding Author: Mingfang Jiang. Email: email

Journal of Cyber Security 2020, 2(3), 123-130. https://doi.org/10.32604/jcs.2020.09703

Abstract

In smart environments, more and more teaching data sources are uploaded to remote cloud centers which promote the development of the smart campus. The outsourcing of massive teaching data can reduce storage burden and computational cost, but causes some privacy concerns because those teaching data (especially personal image data) may contain personal private information. In this paper, a privacy-preserving image feature extraction algorithm is proposed by using mean value features. Clients use block scrambling and chaotic map to encrypt original images before uploading to the remote servers. Cloud servers can directly extract image mean value features from encrypted images. Experiments show the effectiveness and security of our algorithm. It can achieve information search over the encrypted images on the smart campus.

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Cite This Article

APA Style
Ou, X., Jiang, M., Li, S., Bai, Y. (2020). Image feature computation in encrypted domain based on mean value. Journal of Cyber Security, 2(3), 123-130. https://doi.org/10.32604/jcs.2020.09703
Vancouver Style
Ou X, Jiang M, Li S, Bai Y. Image feature computation in encrypted domain based on mean value. J Cyber Secur . 2020;2(3):123-130 https://doi.org/10.32604/jcs.2020.09703
IEEE Style
X. Ou, M. Jiang, S. Li, and Y. Bai, “Image Feature Computation in Encrypted Domain Based on Mean Value,” J. Cyber Secur. , vol. 2, no. 3, pp. 123-130, 2020. https://doi.org/10.32604/jcs.2020.09703



cc Copyright © 2020 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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