Plenary lecture 7: digital video tamper and forgery detection techniques

DIGITAL Image tampering or forgery has become major problem lately, due to ease of artificially synthesizing photographic fakes- for promoting a story by media channels and social networking websites. This is due to significant advances in computer graphics and animation technologies, and availability of low cost off-the-shelf digital image manipulation and cloning tools. With lack of proper regulatory frameworks and infrastructure for prosecution of such evolving cyber-crimes, there is an increasing dissatisfaction about use of such tools for law enforcement, and a feeling of cynicism and mistrust among the civilian operating environments. Another problem this has lead to, is a slow diffusion of otherwise extremely efficient image based surveillance and identity authentication technologies in real-world civilian operating scenarios. In this talk, we present novel algorithmic frameworks being developed for detecting image tampering and forgery based on different source features, their transformation in optimal subspaces and and statisical modelling of intra-frame and inter-frame image pixel sub blocks in video sequences. The proposed algorithmic models allow detecting the tamper or forgery in low-bandwidth video (Internet streaming videos), using blind and passive tamper detection techniques and attempt to model the source signatures embedded in camera pre-processing chain, and show immense potential in detections of evolving image tampering attacks, such as JPEG double compression, re-sampling and retouching. The promising results obtained can result in the development of digital image forensic tools, that can help investigate and solve evolving cyber crimes.