The present chapter deals with the issue of information manipulation detection from an algorithmic point of view, examining a variety of authentication methods, which target assisting average users and media professionals to secure themselves from forged content. The specific domain forms a very interesting, highly interdisciplinary research field, where remarkable progress has been conducted during the last years. The chapter outlines the current state of the art, providing an overview of the different modalities, aiming at evaluating the various types of digital data (text, image, audio, video), in conjunction with the associated falsification attacks and the available forensic investigation tools. In the coming years, the problem of fake news is expected to become even more complicated, as journalism is heading towards an era of heightened automation. Overall, it is anticipated that machine-driven verification assistance means can speed up the required validation processes, reducing the spread of unverified reports.
Video Face Manipulation Detection Through Ensemble of CNNs