We are living in a world where seeing (or hearing) is no longer believing. The technology that allows for digital media to be manipulated and distorted is developing at break-neck speeds. And at the same time, our understanding of the technological, ethical, and legal implications is lagging behind. We are, therefore, developing mathematical and computational algorithms to detect tampering in digital media (in the absence of any type of digital watermark or signature). To do so, we quantify statistical correlations that result from specific forms of digital tampering, and devise detection schemes to reveal these correlations.
