@Article{cmc.2020.07819, AUTHOR = {Jiaohua Qin, Yusi Cao, Xuyu Xiang, *, Yun Tan, Lingyun Xiang, Jianjun Zhang}, TITLE = {An Encrypted Image Retrieval Method Based on SimHash in Cloud Computing}, JOURNAL = {Computers, Materials \& Continua}, VOLUME = {63}, YEAR = {2020}, NUMBER = {1}, PAGES = {389--399}, URL = {http://www.techscience.com/cmc/v63n1/38455}, ISSN = {1546-2226}, ABSTRACT = {With the massive growth of images data and the rise of cloud computing that can provide cheap storage space and convenient access, more and more users store data in cloud server. However, how to quickly query the expected data with privacy-preserving is still a challenging in the encryption image data retrieval. Towards this goal, this paper proposes a ciphertext image retrieval method based on SimHash in cloud computing. Firstly, we extract local feature of images, and then cluster the features by K-means. Based on it, the visual word codebook is introduced to represent feature information of images, which hashes the codebook to the corresponding fingerprint. Finally, the image feature vector is generated by SimHash searchable encryption feature algorithm for similarity retrieval. Extensive experiments on two public datasets validate the effectiveness of our method. Besides, the proposed method outperforms one popular searchable encryption, and the results are competitive to the state-of-the-art.}, DOI = {10.32604/cmc.2020.07819} }