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Botnet dataset with simultaneous attack activity
The proposed dataset shows characteristics of simultaneous botnet attack activities. Botnet network traffic has sequentially interconnected as formed as bidirectional network flow (binetflow), which is combined with normal activities. The dataset is generated from a simulation process by extracting...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9679537/ https://www.ncbi.nlm.nih.gov/pubmed/36426071 http://dx.doi.org/10.1016/j.dib.2022.108628 |
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author | Putra, Muhammad Aidiel Rachman Hostiadi, Dandy Pramana Ahmad, Tohari |
author_facet | Putra, Muhammad Aidiel Rachman Hostiadi, Dandy Pramana Ahmad, Tohari |
author_sort | Putra, Muhammad Aidiel Rachman |
collection | PubMed |
description | The proposed dataset shows characteristics of simultaneous botnet attack activities. Botnet network traffic has sequentially interconnected as formed as bidirectional network flow (binetflow), which is combined with normal activities. The dataset is generated from a simulation process by extracting botnet pattern behaviors taken from CTU-13 and NCC datasets. The extraction results are utilized as the basis for simulations to produce a new dataset with simultaneous botnet attack activities. The term “simultaneous attack activities” refers to an attack activity that involves multiple botnets and happens at the same time. The dataset contains several botnet types distributed over three detection sensors. Each dataset has 18 network header features with a total recording duration of 8 h. The bot attack spreads must be appropriately handled by efficient processing, also known as parallel computation detection. |
format | Online Article Text |
id | pubmed-9679537 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-96795372022-11-23 Botnet dataset with simultaneous attack activity Putra, Muhammad Aidiel Rachman Hostiadi, Dandy Pramana Ahmad, Tohari Data Brief Data Article The proposed dataset shows characteristics of simultaneous botnet attack activities. Botnet network traffic has sequentially interconnected as formed as bidirectional network flow (binetflow), which is combined with normal activities. The dataset is generated from a simulation process by extracting botnet pattern behaviors taken from CTU-13 and NCC datasets. The extraction results are utilized as the basis for simulations to produce a new dataset with simultaneous botnet attack activities. The term “simultaneous attack activities” refers to an attack activity that involves multiple botnets and happens at the same time. The dataset contains several botnet types distributed over three detection sensors. Each dataset has 18 network header features with a total recording duration of 8 h. The bot attack spreads must be appropriately handled by efficient processing, also known as parallel computation detection. Elsevier 2022-09-24 /pmc/articles/PMC9679537/ /pubmed/36426071 http://dx.doi.org/10.1016/j.dib.2022.108628 Text en © 2022 The Author(s). Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Putra, Muhammad Aidiel Rachman Hostiadi, Dandy Pramana Ahmad, Tohari Botnet dataset with simultaneous attack activity |
title | Botnet dataset with simultaneous attack activity |
title_full | Botnet dataset with simultaneous attack activity |
title_fullStr | Botnet dataset with simultaneous attack activity |
title_full_unstemmed | Botnet dataset with simultaneous attack activity |
title_short | Botnet dataset with simultaneous attack activity |
title_sort | botnet dataset with simultaneous attack activity |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9679537/ https://www.ncbi.nlm.nih.gov/pubmed/36426071 http://dx.doi.org/10.1016/j.dib.2022.108628 |
work_keys_str_mv | AT putramuhammadaidielrachman botnetdatasetwithsimultaneousattackactivity AT hostiadidandypramana botnetdatasetwithsimultaneousattackactivity AT ahmadtohari botnetdatasetwithsimultaneousattackactivity |