Privacy-preserving Image Retrieval in IoT-Cloud

Within the IoT-cloud, security has a very significant role to play. One of the best means by which the security and privacy of an image may be safeguarded confidentially is through encryption. However, this methodological process engenders a disadvantage in that it is difficult to search through encrypted images. A number of different means by which encrypted image can be searched have been devised; however, certain security solutions may not be used for smart devices within an IoT-cloud due to the fact that such solutions are not lightweight. We present a lightweight scheme that is able to provide a content-based search through images that have been encrypted. More specifically, images are represented using local features. A similar methodology further described in [1] is also used for image similarity discrimination. In addition, we use a hashing method concerning a locality sensitive hash (LSH) so that the searchable index can be devised. The use of the LSH index means that the proficiency and effectiveness of the system is increased, which allows the retrieval of only relevant images with a minimum number of distance evaluations. Refining vector techniques are used to refine relevant results efficiently and securely. Our index construction process ensures that stored data and trapdoors are kept private.