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Dataset for Botnet group activity with adaptive generator

This dataset represents activity data of bot group and normal activities in a binetflow file. The dataset is generated according to the simulation process of the CTU dataset by extracting activity patterns in each activity type. It is simulated with a modeling approach to producing a new dataset as...

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Detalles Bibliográficos
Autores principales: Hostiadi, Dandy Pramana, Ahmad, Tohari
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8417226/
https://www.ncbi.nlm.nih.gov/pubmed/34504920
http://dx.doi.org/10.1016/j.dib.2021.107334
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author Hostiadi, Dandy Pramana
Ahmad, Tohari
author_facet Hostiadi, Dandy Pramana
Ahmad, Tohari
author_sort Hostiadi, Dandy Pramana
collection PubMed
description This dataset represents activity data of bot group and normal activities in a binetflow file. The dataset is generated according to the simulation process of the CTU dataset by extracting activity patterns in each activity type. It is simulated with a modeling approach to producing a new dataset as botnet group activity data. Furthermore, it consists of 13 datasets with different bot group activity scenarios, each containing the number of bots and various activity types in net flows form whose total activity duration is 8 h. The presented dataset has 14 net flow features, and one activity label feature is used to mark either bot or normal activity. This dataset is useful for research in detecting a periodic bot group activity and its intensity and is correlated with each type of bot activity.
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spelling pubmed-84172262021-09-08 Dataset for Botnet group activity with adaptive generator Hostiadi, Dandy Pramana Ahmad, Tohari Data Brief Data Article This dataset represents activity data of bot group and normal activities in a binetflow file. The dataset is generated according to the simulation process of the CTU dataset by extracting activity patterns in each activity type. It is simulated with a modeling approach to producing a new dataset as botnet group activity data. Furthermore, it consists of 13 datasets with different bot group activity scenarios, each containing the number of bots and various activity types in net flows form whose total activity duration is 8 h. The presented dataset has 14 net flow features, and one activity label feature is used to mark either bot or normal activity. This dataset is useful for research in detecting a periodic bot group activity and its intensity and is correlated with each type of bot activity. Elsevier 2021-08-28 /pmc/articles/PMC8417226/ /pubmed/34504920 http://dx.doi.org/10.1016/j.dib.2021.107334 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Data Article
Hostiadi, Dandy Pramana
Ahmad, Tohari
Dataset for Botnet group activity with adaptive generator
title Dataset for Botnet group activity with adaptive generator
title_full Dataset for Botnet group activity with adaptive generator
title_fullStr Dataset for Botnet group activity with adaptive generator
title_full_unstemmed Dataset for Botnet group activity with adaptive generator
title_short Dataset for Botnet group activity with adaptive generator
title_sort dataset for botnet group activity with adaptive generator
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8417226/
https://www.ncbi.nlm.nih.gov/pubmed/34504920
http://dx.doi.org/10.1016/j.dib.2021.107334
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