E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm
Due to the increased usage of the Internet of Things and heterogeneous distributed devices, the development of effective and reliable intrusion detection systems (IDS) has become more critical. The massive volume of data with various dimensions and security features, on the other hand, can influence...
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| Format: | Article |
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Saba Publishing
2022
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| _version_ | 1796984009655320576 |
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| author | Bouke, Mohamed Aly Abdullah, Azizol ALshatebi, Sameer Hamoud Abdullah, Mohd Taufik |
| author_facet | Bouke, Mohamed Aly Abdullah, Azizol ALshatebi, Sameer Hamoud Abdullah, Mohd Taufik |
| author_sort | Bouke, Mohamed Aly |
| collection | UPM |
| description | Due to the increased usage of the Internet of Things and heterogeneous distributed devices, the development of effective and reliable intrusion detection systems (IDS) has become more critical. The massive volume of data with various dimensions and security features, on the other hand, can influence detection accuracy and raise the computation complexity of these systems. Fortunately, Artificial Intelligence (AI) has recently attracted a lot of attention, and it is now a principal component of these systems. This work presents an enhanced intelligent intrusion detection model (E2IDS) to detect state of the art known cyberattacks. The model design is Decision Tree (DT) algorithm-based, with an approach to data balancing since the data set used is highly unbalanced and one more approach for feature selection. Furthermore, accuracy, recall and F-score are selected as the performance evaluation metrics. The experimental results show that our E2IDS not only overcomes the benchmark work but also reduces the complexity of the computing process. |
| first_indexed | 2024-03-06T11:14:29Z |
| format | Article |
| id | upm.eprints-101031 |
| institution | Universiti Putra Malaysia |
| last_indexed | 2024-03-06T11:14:29Z |
| publishDate | 2022 |
| publisher | Saba Publishing |
| record_format | dspace |
| spelling | upm.eprints-1010312023-06-19T06:20:12Z http://psasir.upm.edu.my/id/eprint/101031/ E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm Bouke, Mohamed Aly Abdullah, Azizol ALshatebi, Sameer Hamoud Abdullah, Mohd Taufik Due to the increased usage of the Internet of Things and heterogeneous distributed devices, the development of effective and reliable intrusion detection systems (IDS) has become more critical. The massive volume of data with various dimensions and security features, on the other hand, can influence detection accuracy and raise the computation complexity of these systems. Fortunately, Artificial Intelligence (AI) has recently attracted a lot of attention, and it is now a principal component of these systems. This work presents an enhanced intelligent intrusion detection model (E2IDS) to detect state of the art known cyberattacks. The model design is Decision Tree (DT) algorithm-based, with an approach to data balancing since the data set used is highly unbalanced and one more approach for feature selection. Furthermore, accuracy, recall and F-score are selected as the performance evaluation metrics. The experimental results show that our E2IDS not only overcomes the benchmark work but also reduces the complexity of the computing process. Saba Publishing 2022-06-30 Article PeerReviewed Bouke, Mohamed Aly and Abdullah, Azizol and ALshatebi, Sameer Hamoud and Abdullah, Mohd Taufik (2022) E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm. Journal of Applied Artificial Intelligence, 3 (1). pp. 1-16. ISSN 2709-5908 https://www.sabapub.com/index.php/jaai/article/view/450 10.48185/jaai.v3i1.450 |
| spellingShingle | Bouke, Mohamed Aly Abdullah, Azizol ALshatebi, Sameer Hamoud Abdullah, Mohd Taufik E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm |
| title | E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm |
| title_full | E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm |
| title_fullStr | E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm |
| title_full_unstemmed | E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm |
| title_short | E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm |
| title_sort | e2ids an enhanced intelligent intrusion detection system based on decision tree algorithm |
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