A faster secure content-based image retrieval using clustering for cloud

Secure indexing, ranking, searching, and retrieval in encrypted domain without compromising privacy is a challenging task. This is even more difficult in the case of images. In this paper, we propose a faster, more efficient, and highly scalable secure content-based image retrieval scheme using clustering for cloud. In the proposed scheme, the image owner extracts MPEG-7 visual descriptors from all the images and clusters them for indexing. These image features and cluster centers encrypted using Asymmetric scalar-product preserving encryption are offloaded to the cloud along with encrypted images to ensure secure retrieval of images. We also propose a copy-deterrence mechanism to identify untrustworthy query users. The proposed scheme is highly scalable, up to seven times faster in searching and up to 23 times faster in indexing with better retrieval precision compared with the fastest state-of-the-art scheme. The proposed copy deterrence mechanism ensures better speed and perceptual quality of watermarked images with better or comparable extraction accuracy when compromised. •A novel and faster SCBIR using clustering and ASPE with copy deterrence for cloud.•Highly scalable SCBIR with faster searching, indexing, and trapdoor generation.•A practical and light-weight SCBIR scheme with better retrieval precision.•Proposed copy deterrence ensures better speed and minimal image quality degradation.