Botnet Detection Using a Feed-Forward Backpropagation Artificial Neural Network
Botnet represent a critical threat to computer networks because their behavior allows hackers to take control of many computers simultaneously. Botnets take over the device of their victim and performs malicious activities on its system. Although many solutions have been developed to address the det...
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| Format: | Conference or Workshop Item |
| Language: | English |
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Springer
2019
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| Online Access: | http://umpir.ump.edu.my/id/eprint/22501/ http://umpir.ump.edu.my/id/eprint/22501/1/Botnet%20Detection%20Using%20a%20Feed-Forward1.pdf |
| _version_ | 1848821612134006784 |
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| author | Ahmed, Abdulghani Ali |
| author_facet | Ahmed, Abdulghani Ali |
| author_sort | Ahmed, Abdulghani Ali |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Botnet represent a critical threat to computer networks because their behavior allows hackers to take control of many computers simultaneously. Botnets take over the device of their victim and performs malicious activities on its system. Although many solutions have been developed to address the detection of Botnet in real time, these solutions are still prone to several problems that may critically affect the efficiency and capability of identifying and preventing Botnet attacks. The current work proposes a technique to detect Botnet attacks using a feed-forward backpropagation artificial neural network. The proposed technique aims to detect Botnet zero-day attack in real time. This technique applies a backpropagation algorithm to the CTU-13 dataset to train and evaluate the Botnet detection classifier. It is implemented and tested in various neural network designs with different hidden layers. Results demonstrate that the proposed technique is promising in terms of accuracy and efficiency of Botnet detection. |
| first_indexed | 2025-11-15T02:28:07Z |
| format | Conference or Workshop Item |
| id | ump-22501 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T02:28:07Z |
| publishDate | 2019 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-225012021-05-10T03:23:00Z http://umpir.ump.edu.my/id/eprint/22501/ Botnet Detection Using a Feed-Forward Backpropagation Artificial Neural Network Ahmed, Abdulghani Ali QA75 Electronic computers. Computer science Botnet represent a critical threat to computer networks because their behavior allows hackers to take control of many computers simultaneously. Botnets take over the device of their victim and performs malicious activities on its system. Although many solutions have been developed to address the detection of Botnet in real time, these solutions are still prone to several problems that may critically affect the efficiency and capability of identifying and preventing Botnet attacks. The current work proposes a technique to detect Botnet attacks using a feed-forward backpropagation artificial neural network. The proposed technique aims to detect Botnet zero-day attack in real time. This technique applies a backpropagation algorithm to the CTU-13 dataset to train and evaluate the Botnet detection classifier. It is implemented and tested in various neural network designs with different hidden layers. Results demonstrate that the proposed technique is promising in terms of accuracy and efficiency of Botnet detection. Springer 2019 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/22501/1/Botnet%20Detection%20Using%20a%20Feed-Forward1.pdf Ahmed, Abdulghani Ali (2019) Botnet Detection Using a Feed-Forward Backpropagation Artificial Neural Network. In: Computational Intelligence in Information Systems: Proceedings of the Computational Intelligence in Information Systems Conference (CIIS 2018) , 16-18 November 2018 , Brunei. pp. 24-35., 888. ISBN 978-3-030-03302-6 (Published) https://doi.org/10.1007/978-3-030-03302-6_3 |
| spellingShingle | QA75 Electronic computers. Computer science Ahmed, Abdulghani Ali Botnet Detection Using a Feed-Forward Backpropagation Artificial Neural Network |
| title | Botnet Detection Using a Feed-Forward Backpropagation Artificial Neural Network |
| title_full | Botnet Detection Using a Feed-Forward Backpropagation Artificial Neural Network |
| title_fullStr | Botnet Detection Using a Feed-Forward Backpropagation Artificial Neural Network |
| title_full_unstemmed | Botnet Detection Using a Feed-Forward Backpropagation Artificial Neural Network |
| title_short | Botnet Detection Using a Feed-Forward Backpropagation Artificial Neural Network |
| title_sort | botnet detection using a feed-forward backpropagation artificial neural network |
| topic | QA75 Electronic computers. Computer science |
| url | http://umpir.ump.edu.my/id/eprint/22501/ http://umpir.ump.edu.my/id/eprint/22501/ http://umpir.ump.edu.my/id/eprint/22501/1/Botnet%20Detection%20Using%20a%20Feed-Forward1.pdf |