MSF Seminar 3

Digital video are widely used in today’s society due to the availability of a wide range of affordable digital video cameras with different specifications and functions. The manipulation of digital video is made simple with easily available processing tools, making it harder to trust them. This is where the role of digital forensics becomes important; to ensure the integrity of the evidence is restored. Digital forensics helps by providing some essential information about a video, such as to tracing the source of a digital video to the device that captured it. In this research, we propose a video camera identification technique based on the conditional probability features (CP Features). Specifically we focus on its performance for identification of video sources using cameras of different models. Using three cameras of different model, we demonstrate that the CP Features are able to correctly match the test video frames with their source. These findings provide a good indication that CP Features are suitable for digital video forensics.