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Dataset for file fragment classification of textual file formats
OBJECTIVES: Classification of textual file formats is a topic of interest in network forensics. There are a few publicly available datasets of files with textual formats. Therewith, there is no public dataset for file fragments of textual file formats. So, a big research challenge in file fragment c...
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/PMC6907108/ https://www.ncbi.nlm.nih.gov/pubmed/31829258 http://dx.doi.org/10.1186/s13104-019-4837-4 |
_version_ | 1783478482679889920 |
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author | Mansouri Hanis, Fatemeh Teimouri, Mehdi |
author_facet | Mansouri Hanis, Fatemeh Teimouri, Mehdi |
author_sort | Mansouri Hanis, Fatemeh |
collection | PubMed |
description | OBJECTIVES: Classification of textual file formats is a topic of interest in network forensics. There are a few publicly available datasets of files with textual formats. Therewith, there is no public dataset for file fragments of textual file formats. So, a big research challenge in file fragment classification of textual 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 five textual file formats: Binary file format for Word 97–Word 2003, Microsoft Word open XML format, portable document format, rich text file, and standard text document. This dataset contains the file fragments in three different languages: English, Persian, and Chinese. For each pair of file format and language, 1500 file fragments are provided. So, the dataset of file fragments contains 22,500 file fragments. |
format | Online Article Text |
id | pubmed-6907108 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-69071082019-12-20 Dataset for file fragment classification of textual file formats Mansouri Hanis, Fatemeh Teimouri, Mehdi BMC Res Notes Data Note OBJECTIVES: Classification of textual file formats is a topic of interest in network forensics. There are a few publicly available datasets of files with textual formats. Therewith, there is no public dataset for file fragments of textual file formats. So, a big research challenge in file fragment classification of textual 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 five textual file formats: Binary file format for Word 97–Word 2003, Microsoft Word open XML format, portable document format, rich text file, and standard text document. This dataset contains the file fragments in three different languages: English, Persian, and Chinese. For each pair of file format and language, 1500 file fragments are provided. So, the dataset of file fragments contains 22,500 file fragments. BioMed Central 2019-12-11 /pmc/articles/PMC6907108/ /pubmed/31829258 http://dx.doi.org/10.1186/s13104-019-4837-4 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Data Note Mansouri Hanis, Fatemeh Teimouri, Mehdi Dataset for file fragment classification of textual file formats |
title | Dataset for file fragment classification of textual file formats |
title_full | Dataset for file fragment classification of textual file formats |
title_fullStr | Dataset for file fragment classification of textual file formats |
title_full_unstemmed | Dataset for file fragment classification of textual file formats |
title_short | Dataset for file fragment classification of textual file formats |
title_sort | dataset for file fragment classification of textual file formats |
topic | Data Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6907108/ https://www.ncbi.nlm.nih.gov/pubmed/31829258 http://dx.doi.org/10.1186/s13104-019-4837-4 |
work_keys_str_mv | AT mansourihanisfatemeh datasetforfilefragmentclassificationoftextualfileformats AT teimourimehdi datasetforfilefragmentclassificationoftextualfileformats |