Dataset for file fragment classification of image file formats.


Journal

BMC research notes
ISSN: 1756-0500
Titre abrégé: BMC Res Notes
Pays: England
ID NLM: 101462768

Informations de publication

Date de publication:
27 Nov 2019
Historique:
received: 24 10 2019
accepted: 14 11 2019
entrez: 29 11 2019
pubmed: 30 11 2019
medline: 16 4 2020
Statut: epublish

Résumé

File fragment classification of image file formats is a topic of interest in network forensics. There are a few publicly available datasets of files with image formats. Therewith, there is no public dataset for file fragments of image file formats. So, a big research challenge in file fragment classification of image file formats is to compare the performance of the developed methods over the same datasets. In this study, we present a dataset that contains file fragments of ten image file formats: Bitmap, Better Portable Graphics, Free Lossless Image Format, Graphics Interchange Format, Joint Photographic Experts Group, Joint Photographic Experts Group 2000, Joint Photographic Experts Group Extended Range, Portable Network Graphic, Tagged Image File Format, and Web Picture. Corresponding to each format, the dataset contains the file fragments of image files with different compression settings. For each pair of file format and compression setting, 800 file fragments are provided. Totally, the dataset contains 25,600 file fragments.

Identifiants

pubmed: 31775855
doi: 10.1186/s13104-019-4812-0
pii: 10.1186/s13104-019-4812-0
pmc: PMC6881973
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

774

Références

BMC Res Notes. 2019 Nov 27;12(1):774
pubmed: 31775855

Auteurs

Reyhane Fakouri (R)

Information Theory and Coding Laboratory, University of Tehran, Tehran, Iran.

Mehdi Teimouri (M)

Information Theory and Coding Laboratory, University of Tehran, Tehran, Iran. mehditeimouri@ut.ac.ir.

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Classifications MeSH