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A Cryptograph Domain Image Retrieval Method Based on Paillier Homomorphic Block Encryption

Wenjia Xu1, Shijun Xiang1,*, Vasily Sachnev2

School of Information Science and Technology, Jinan University, No. 601, West Huangpu Avenue, Guangzhou and 510632, China.
Department of Information, Communications and Electronic Engineering, The Catholic University of Korea, Seoul and 02841, South Korea.

* Corresponding author: Shijun Xiang. Email: email.

Computers, Materials & Continua 2018, 55(2), 285-295. https://doi.org/10.3970/cmc.2018.01719

Abstract

With the rapid development of information network, the computing resources and storage capacity of ordinary users cannot meet their needs of data processing. The emergence of cloud computing solves this problem but brings data security problems. How to manage and retrieve ciphertext data effectively becomes a challenging problem. To these problems, a new image retrieval method in ciphertext domain by block image encrypting based on Paillier homomophic cryptosystem is proposed in this paper. This can be described as follows: According to the Paillier encryption technology, the image owner encrypts the original image in blocks, obtains the image in ciphertext domain, then passes it to the third party server. The server calculates the difference histogram of the image in ciphertext domain according to the public key and establishes the index database. The user passes the retrieved image to the server. The server computes the differential histogram of the retrieved image by public key. Then, compares the similarity of it with the histogram in index database and selects larger similarity images in ciphertext and send them to the user. The user obtains the target image with the private key. The experimental results show that the method is feasible and simple.

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Cite This Article

W. . Xu, S. . Xiang and V. . Sachnev, "A cryptograph domain image retrieval method based on paillier homomorphic block encryption," Computers, Materials & Continua, vol. 55, no.2, pp. 285–295, 2018. https://doi.org/10.3970/cmc.2018.01719



cc 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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