Encryption Independent Multi Owner Multi User Secure Content Based Image Retrieval for JPEG Images

Abstract

Image retrieval systems help users to browse and search among extensive images in real-time. Various image retrieval techniques have been developed over the years. Content based image retrieval is a technique employed to search and retrieve similar images based on their visual content (query image) rather than text-based query. On the other hand, secure content-based image retrieval is meant to retrieve similar images from encrypted images. At present, various secure content-based image retrieval schemes have been developed which encrypt images first and extract features subsequently. However, none of existing schemes uses NIST approved / globally accepted encryption nor there are any techniques available which gives liberty to user to use any encryption scheme resulting in restricting user’s liberty, which is contradictory to multi-user environment of cloud. In this research, we propose a novel paradigm which gives independence to users to use any encryption primitive as per their security needs. Applicable to optimized JPEG images, our proposed system employs segmented encryption to encrypt image data segment of JPEG images. Subsequently, huffman tables; extracted from encrypted images are used for retrieval tasks employing machine learning in both supervised and unsupervised domain. Experiments reveal that our scheme achieves excellent performance in terms of efficiency.