A Video Forensic Framework for the Unsupervised Analysis of MP4-Like File Container

• Published in: IEEE transactions on information forensics and security Vol. 14; no. 3; pp. 635 - 645
• Main Authors: Iuliani, Massimo, Shullani, Dasara, Fontani, Marco, Meucci, Saverio, Piva, Alessandro
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.03.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Containers; file container; forensic analysis; Forensic engineering; Forensics; Inspection; Integrity; ISO Standards; Life cycle analysis; Life cycle engineering; Media; Metadata; New technology; smartphone; Smartphones; Streaming media; Video data; Video forensics
• ISSN: 1556-6013; 1556-6021
• DOI: 10.1109/TIFS.2018.2859760

Video forensics keeps developing new technologies to verify the authenticity and the integrity of digital videos. While most of the existing methods rely on the analysis of the video data stream, recently, a new line of research was introduced to investigate video life cycle based on the analysis of the video container. Anyway, existing contributions in this field are based on manual comparison of video container structure and content, which is time demanding and error-prone. In this paper, we introduce a method for unsupervised analysis of video file containers, and present two main forensic applications of such method: the first one deals with video integrity verification, based on the dissimilarity between a reference and a query file container; the second one focuses on the identification and classification of the source device brand, based on the analysis of containers structure and content. Noticeably, the latter application relies on the likelihood-ratio framework, which is more and more approved by the forensic community as the appropriate way to exhibit findings in court. We tested and proved the effectiveness of both applications on a dataset composed by 578 videos taken with modern smartphones from major brands and models. The proposed approaches are proved to be valuable also for requiring an extremely small computational cost as opposed to all available techniques based on the video stream analysis or manual inspection of file containers.