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Dataset for file fragment classification of video file formats

Authors
  • Sadeghi, Narges1
  • Fahiminia, Mohadeseh1
  • Teimouri, Mehdi1
  • 1 University of Tehran, Tehran, Iran , Tehran (Iran)
Type
Published Article
Journal
BMC Research Notes
Publisher
Springer (Biomed Central Ltd.)
Publication Date
Apr 15, 2020
Volume
13
Issue
1
Identifiers
DOI: 10.1186/s13104-020-05037-x
Source
Springer Nature
Keywords
License
Green

Abstract

ObjectivesFile fragment classification of video file formats is a topic of interest in network forensics. There are some publicly available datasets for file fragments of various file types such as textual, audio, and image file formats. However, there is no public dataset for file fragments of video file formats. So, in order to evaluate and compare the performance of the classification methods, a challenge is the need to have such datasets.Data descriptionIn this study, we present a dataset that contains file fragments of 10 video file formats: 3GP, AVI, ASF, FLV, MKV, MOV, MP4, WebM, OGV, and RMVB. Corresponding to each format, the dataset contains the file fragments of video files with different video codec types: H.263, MPEG-4, WMV, H.264, FLV1, H.265, VP8, VP9, Theora, and RealVideo. Totally, 20 different pairs of video format and codec are employed. For each pair of video format and codec, 30,000 file fragments are provided. Totally, the dataset contains 600,000 file fragments.

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