Secure Cloud-Based Image Tampering Detection and Localization Using POB Number System

Abstract

The benefits of high-end computation infrastructure facilities provided by cloud-based multimedia systems are attracting people all around the globe. However, such cloud-based systems possess security issues as third party servers become involved in them. Rendering data in an unreadable form so that no information is revealed to the cloud data centers will serve as the best solution to these security issues. One such image encryption scheme based on a Permutation Ordered Binary Number System has been proposed in this work. It distributes the image information in totally random shares, which can be stored at the cloud data centers. Further, the proposed scheme authenticates the shares at the pixel level. If any tampering is done at the cloud servers, the scheme can accurately identify the altered pixels via authentication bits and localizes the tampered area. The tampered portion is also reflected back in the reconstructed image that is obtained at the authentic user end. The experimental results validate the efficacy of the proposed scheme against various kinds of possible attacks, tested with a variety of images. The tamper detection accuracy has been computed on a pixel basis and found to be satisfactorily high for most of the tampering scenarios.