PRNU-based source device attribution for YouTube videos
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Date
2019-03-17
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Abstract
Photo Response Non-Uniformity (PRNU) is a camera imaging sensor imperfection which has earned a great interest for source device attribution of digital videos. A majority of recent researches about PRNU-based source device attribution for digital videos do not take into consideration the effects of video compression on the PRNU noise in video frames, but rather consider video frames as isolated images of equal importance. As a result, these methods perform poorly on re-compressed or low bit-rate videos. This paper proposes a novel method for PRNU fingerprint estimation from video frames taking into account the effects of video compression on the PRNU noise in these frames. With this method, we aim to determine whether two videos from unknown sources originate from the same device or not. Experimental results on a large set of videos show that the method we propose is more effective than existing frame-based methods that use either only I frames or all (I-B-P) frames, especially on YouTube videos.
Description
Keywords
Computer science, Video forensics, Source device attribution, Photo-response non-uniformity (PRNU), H.264/AVC, YouTube, Computer graphics, Image coding, Image compression, Multimedia systems, H.264/AVC, Photo response non uniformities (PRNU), Source device attribution, Video forensics, Digital forensics
Citation
Kouokam, E. K. ve Dirik, A. E. (2019). ''PRNU-based source device attribution for YouTube videos''. Digital Investigation, 29, 91-100.