Detection of Double-Compressed Videos Using Descriptors of Video Encoders

Author:

Lee Yun Gu,Na Gihyun,Byun Junseok

Abstract

In digital forensics, video becomes important evidence in an accident or a crime. However, video editing programs are easily available in the market, and even non-experts can delete or modify a section of an evidence video that contains adverse evidence. The tampered video is compressed again and stored. Therefore, detecting a double-compressed video is one of the important methods in the field of digital video tampering detection. In this paper, we present a new approach to detecting a double-compressed video using the proposed descriptors of video encoders. The implementation of real-time video encoders is so complex that manufacturers should develop hardware video encoders considering a trade-off between complexity and performance. According to our observation, hardware video encoders practically do not use all possible encoding modes defined in the video coding standard but only a subset of the encoding modes. The proposed method defines this subset of encoding modes as the descriptor of the video encoder. If a video is double-compressed, the descriptor of the double-compressed video is changed to the descriptor of the video encoder used for double-compression. Therefore, the proposed method detects the double-compressed video by checking whether the descriptor of the test video is changed or not. In our experiments, we show descriptors of various H.264 and High-Efficiency Video Coding (HEVC) video encoders and demonstrate that our proposed method successfully detects double-compressed videos in most cases.

Funder

Research Grant of Kwangwoon University

Institute of Information & communications Technology Planning & Evaluation

Korean government

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Reference36 articles.

1. Poisel, R., and Tjoa, S. (2011, January 10–12). Forensics investigations of multimedia data: A review of the state-of-the-art. Proceedings of the 2011 Sixth International Conference on IT Security Incident Management and IT Forensics, Stuttgart, Germany.

2. Overview of state-of-the-art in digital image forensics;Sencar;Algorithms Archit. Inf. Syst. Secur.,2008

3. An Examination of Digital Forensic Models;Reith;Int. J. Digit. Evid.,2002

4. Digital forensics research: The next 10 years;Simson;Digit. Investig.,2010

5. Digital forensics;Delp;IEEE Signal Process.,2009

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