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Dataset for file fragment classification of image file formats
OBJECTIVES: 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 fr...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6881973/ https://www.ncbi.nlm.nih.gov/pubmed/31775855 http://dx.doi.org/10.1186/s13104-019-4812-0 |
Sumario: | OBJECTIVES: 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. DATA DESCRIPTION: 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. |
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