ITC-MNP: a diverse dataset for image file fragment classification
The dataset includes image file fragments of 4096 bytes from five formats (JPG, BMP, GIF, PNG, and TIFF), each processed with different conversion settings. The source images are categorized into three content types: Nature, People, and Medical. In total, the dataset contains 501,000 fragments. These fragments consist of file headers and incomplete end-of-file fragments, completed with random bytes to approximate how operating systems handle data when file sizes are not multiples of the sector size. This approach aims to simulate typical scenarios where fragments are recovered from a hard drive, though it may not capture all real-world complexities such as data corruption and complex file structures.
Authors
- Babak Tavassoli (ORCID: https://orcid.org/0000-0003-1127-7331)
- Mehdi Teimouri (ORCID: https://orcid.org/0000-0003-4662-5535)
- Zhino Naghshbandi
Institutions
- University of Tehran (IR)
Publication Details
- Journal
- BMC Research Notes
- Published
- 2024-12-19
- DOI
- https://doi.org/10.1186/s13104-024-07034-w
- Citations
- 3
- Primary Topic
- Digital Media Forensic Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.75