Video forensics is an emerging discipline, that aims at inferring information about the processing history undergone by a digital video in a blind fashion. In this work we introduce a new forensic footprint and, based on it, propose a method for detecting whether a video has been encoded twice; if this is the case, we also estimate the size of the Group Of Pictures (GOP) employed during the first encoding. As shown in the experiments, the footprint proves to be very robust even in realistic settings (i.e., when encoding is carried out using typical compression rates), that are rarely addressed by existing techniques.

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Camera identification using sensor fingerprints is nowadays a well-established technology for reliably linking an image or a video clip to a specific camera. The sensor fingerprint is typically estimated from images (video frames) provably taken by the imaging device. An image or a video clip is then associated with the fingerprint when some form of a matched filter exceeds a certain threshold, which is set to achieve a prescribed false alarm. However, when the images from which the sensor fingerprint is estimated are lossy compressed, the statistical properties of the detection statistic change, which requires an adjustment of the decision threshold to guarantee the same false-alarm rate. In this paper, we study this effect both theoretically and experimentally. A very good match between the theoretical and experimental results validates our approach. This study is especially important for video forensic because of the higher compression rates.