A Prnu-Based Method to Expose Video Device Compositions in Open-Set Setups

As the diffusion of altered video sequences over social networks and the internet can have severe consequences (e.g., fake news spreading, false accusations, etc.), the forensic research community has started actively working toward the development of methodologies tailored to assess the authenticity and integrity of video sequences. In this work, we focus on the problem of spotting video compilations composed by temporally concatenating sequences acquired with different devices. To solve this problem, we leverage trace characteristics of each video recording device left on each video at acquisition time. Specifically, we propose a method leveraging Photo-Response Non-Uniformity (PRNU) traces along with a binary classifier in order to understand which frames of a video have been acquired with the same device used to record the first few frames. Results show that the proposed solution outperforms baselines based on standard PRNU correlation and thresholding tests. Experiments have been carried out in an open-set scenario and show promising results.