PRNU-Based Video Source Attribution: Which Frames Are You Using?

Abstract

Photo Response Non-Uniformity (PRNU) is reputed the most successful trace to identify the source of a digital video. However, its effectiveness is mainly limited by compression and the effect of recently introduced electronic image stabilization on several devices. In the last decade, several approaches were proposed to overcome both these issues, mainly by selecting those video frames which are considered more informative. However, the two problems were always treated separately, and the combined effect of compression and digital stabilization was never considered. This separated analysis makes it hard to understand if achieved conclusions still stand for digitally stabilized videos and if those choices represent a general optimum strategy to perform video source attribution. In this paper, we explore whether an optimum strategy exists in selecting frames based on their type and their positions within the groups of pictures. We, therefore, systematically analyze the PRNU contribute provided by all frames belonging to either digitally stabilized or not stabilized videos. Results on the VISION dataset come up with some insights into optimizing video source attribution in different use cases.