An efficient anomaly intrusion detection method with evolutionary kernel neural network random weights
Internet security requirements are increasing due to the growth of internet usage. One of the most efficient approaches used to secure the usage of the internet from internal and external intruders is Intrusion Detection System (IDS). Considering that using a combination of ANN and EA can produce an...
| मुख्य लेखकों: | , , , |
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| स्वरूप: | लेख |
| भाषा: | English |
| प्रकाशित: |
Little Lion Scientific
2020
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| ऑनलाइन पहुंच: | http://psasir.upm.edu.my/id/eprint/87818/1/ABSTRACT.pdf |
| _version_ | 1825952416093175808 |
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| author | Sarvari, Samira Mohd Sani, Nor Fazlida Mohd Hanapi, Zurina Abdullah @ Selimun, Mohd Taufik |
| author_facet | Sarvari, Samira Mohd Sani, Nor Fazlida Mohd Hanapi, Zurina Abdullah @ Selimun, Mohd Taufik |
| author_sort | Sarvari, Samira |
| collection | UPM |
| description | Internet security requirements are increasing due to the growth of internet usage. One of the most efficient approaches used to secure the usage of the internet from internal and external intruders is Intrusion Detection System (IDS). Considering that using a combination of ANN and EA can produce an advanced technique to
develop an efficient anomaly detection approach for IDS, several types of research have used ENN algorithms to detect the attacks. To enhance the efficiency of anomaly-based detection in terms of accuracy of classification, in this paper, the evolutionary kernel neural network random weight is proposed. This model is applied to the NSLKDD dataset, an improvement of the KDD Cup'99. The proposed method achieved 99.24% accuracy which shows that the novel algorithm suggested is more superior to existing ones as it provides the optimal overall efficiency. |
| first_indexed | 2024-03-06T10:44:18Z |
| format | Article |
| id | upm.eprints-87818 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T10:44:18Z |
| publishDate | 2020 |
| publisher | Little Lion Scientific |
| record_format | dspace |
| spelling | upm.eprints-878182022-06-14T06:31:06Z http://psasir.upm.edu.my/id/eprint/87818/ An efficient anomaly intrusion detection method with evolutionary kernel neural network random weights Sarvari, Samira Mohd Sani, Nor Fazlida Mohd Hanapi, Zurina Abdullah @ Selimun, Mohd Taufik Internet security requirements are increasing due to the growth of internet usage. One of the most efficient approaches used to secure the usage of the internet from internal and external intruders is Intrusion Detection System (IDS). Considering that using a combination of ANN and EA can produce an advanced technique to develop an efficient anomaly detection approach for IDS, several types of research have used ENN algorithms to detect the attacks. To enhance the efficiency of anomaly-based detection in terms of accuracy of classification, in this paper, the evolutionary kernel neural network random weight is proposed. This model is applied to the NSLKDD dataset, an improvement of the KDD Cup'99. The proposed method achieved 99.24% accuracy which shows that the novel algorithm suggested is more superior to existing ones as it provides the optimal overall efficiency. Little Lion Scientific 2020 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/87818/1/ABSTRACT.pdf Sarvari, Samira and Mohd Sani, Nor Fazlida and Mohd Hanapi, Zurina and Abdullah @ Selimun, Mohd Taufik (2020) An efficient anomaly intrusion detection method with evolutionary kernel neural network random weights. Journal of Theoretical and Applied Information Technology, 98 (7). 963 - 976. ISSN 1992-8645; ESSN: 1817-3195 http://www.jatit.org/volumes/ninetyeight7.php |
| spellingShingle | Sarvari, Samira Mohd Sani, Nor Fazlida Mohd Hanapi, Zurina Abdullah @ Selimun, Mohd Taufik An efficient anomaly intrusion detection method with evolutionary kernel neural network random weights |
| title | An efficient anomaly intrusion detection method with evolutionary kernel neural network random weights |
| title_full | An efficient anomaly intrusion detection method with evolutionary kernel neural network random weights |
| title_fullStr | An efficient anomaly intrusion detection method with evolutionary kernel neural network random weights |
| title_full_unstemmed | An efficient anomaly intrusion detection method with evolutionary kernel neural network random weights |
| title_short | An efficient anomaly intrusion detection method with evolutionary kernel neural network random weights |
| title_sort | efficient anomaly intrusion detection method with evolutionary kernel neural network random weights |
| url | http://psasir.upm.edu.my/id/eprint/87818/1/ABSTRACT.pdf |
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