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A Dataset for Forensic Analysis of Videos in the Wild

  • Dasara ShullaniEmail author
  • Omar Al Shaya
  • Massimo Iuliani
  • Marco Fontani
  • Alessandro Piva
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 766)

Abstract

The Multimedia Forensics community has developed a wide variety of tools for investigating the processing history of digital videos. One of the main problems, however, is the lack of benchmark datasets allowing to evaluate tools performance on a common reference. In fact, contrarily to the case of image forensics, only a few datasets exist for video forensics, that are limited in size and outdated when compared to today’s real-world scenario (e.g., they contain videos at very low resolution, captured with outdated camcorders, compressed with legacy encoders, etc.). In this paper, we propose a novel dataset made of 622 native videos, most of which in FullHD resolution, captured with 35 different portable devices, belonging to 11 manufacturers and running iOS, Android and Windows Phone OS. Videos have been captured in three different scenarios (indoor, outdoor, flat-field), and with three different kinds of motion (move, still, panrot). Since videos are increasingly shared through social media platforms, we also provide the YouTube version of most videos. Finally, in order to avoid that the proposed dataset becomes outdated in a few moths, we propose a mobile application (MOSES) that allows the acquisition of video contents from recent iOS and Android devices along with their metadata. In this way, the dataset can grow in the future and remain up-to-date.

Keywords

Dataset Video forensics Multimedia forensics Source identification Social media platforms 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Dasara Shullani
    • 1
    Email author
  • Omar Al Shaya
    • 1
    • 3
  • Massimo Iuliani
    • 1
    • 2
  • Marco Fontani
    • 1
    • 2
  • Alessandro Piva
    • 1
    • 2
  1. 1.Department of Information EngineeringUniversity of FlorenceFlorenceItaly
  2. 2.FORLAB, Multimedia Forensics LaboratoryPIN ScrlPratoItaly
  3. 3.Department of Electronic MediaSaudi Electronic UniversityRiyadhSaudi Arabia

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