An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA
Network intrusion detection is an essential component of contemporary cybersecurity strategies, and the development of efficient techniques to accurately identify malicious activities has become a priority. This study investigates the performance of various conventional machine learning algorithms,...
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Semarak Ilmu Publishing
2025
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Online Access: | http://ir.unimas.my/id/eprint/45194/1/ARASETV44_N1_PP225_238%20%28dragged%29.pdf http://ir.unimas.my/id/eprint/45194/ https://semarakilmu.com.my/journals/index.php/applied_sciences_eng_tech/index https://doi.org/10.37934/araset.44.1.225238 |
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my.unimas.ir.451942024-07-09T06:44:54Z http://ir.unimas.my/id/eprint/45194/ An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA Hui, Bian Chiew, Kang Leng QA75 Electronic computers. Computer science T Technology (General) Network intrusion detection is an essential component of contemporary cybersecurity strategies, and the development of efficient techniques to accurately identify malicious activities has become a priority. This study investigates the performance of various conventional machine learning algorithms, including decision trees, naive Bayes, naive Bayes trees, random forest, random trees, MLP, and SVM, in detecting network intrusions using binary and multi-classification approaches. Furthermore, the study proposes a deep learning method, CNN-LSTM-SA, which consistently outperforms conventional machine learning techniques in terms of precision, recall, F1 score, and overall accuracy for network intrusion detection. Specifically, the proposed method combines CNN and LSTM with SA in machine learning theory to extract more optimized, strongly correlated features. The proposed method is evaluated using the benchmark NSL-KDD database. The results indicate that the CNN-LSTM-SA method holds great potential in enhancing the efficacy of network intrusion detection systems. Semarak Ilmu Publishing 2025 Article PeerReviewed text en http://ir.unimas.my/id/eprint/45194/1/ARASETV44_N1_PP225_238%20%28dragged%29.pdf Hui, Bian and Chiew, Kang Leng (2025) An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA. Journal of Advanced Research in Applied Sciences and Engineering Technology, 44 (1). pp. 225-238. ISSN 2462 - 1943 https://semarakilmu.com.my/journals/index.php/applied_sciences_eng_tech/index https://doi.org/10.37934/araset.44.1.225238 |
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QA75 Electronic computers. Computer science T Technology (General) Hui, Bian Chiew, Kang Leng An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA |
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Network intrusion detection is an essential component of contemporary cybersecurity strategies, and the development of efficient techniques to accurately identify malicious activities has become a priority. This study investigates the performance of various conventional machine learning algorithms, including decision trees, naive Bayes, naive Bayes trees, random forest, random trees, MLP, and SVM, in detecting network intrusions using binary and multi-classification approaches. Furthermore, the study proposes a deep learning method, CNN-LSTM-SA, which consistently outperforms conventional machine learning techniques in terms of precision, recall, F1 score, and overall accuracy for network intrusion detection. Specifically, the proposed method combines CNN and LSTM with SA in machine learning theory to extract more optimized, strongly correlated features. The proposed method is evaluated using the benchmark NSL-KDD database. The results indicate that the CNN-LSTM-SA method holds great potential in enhancing the efficacy of network intrusion detection systems. |
format |
Article |
author |
Hui, Bian Chiew, Kang Leng |
author_facet |
Hui, Bian Chiew, Kang Leng |
author_sort |
Hui, Bian |
title |
An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA |
title_short |
An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA |
title_full |
An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA |
title_fullStr |
An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA |
title_full_unstemmed |
An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA |
title_sort |
improved network intrusion detection method based on cnn-lstm-sa |
publisher |
Semarak Ilmu Publishing |
publishDate |
2025 |
url |
http://ir.unimas.my/id/eprint/45194/1/ARASETV44_N1_PP225_238%20%28dragged%29.pdf http://ir.unimas.my/id/eprint/45194/ https://semarakilmu.com.my/journals/index.php/applied_sciences_eng_tech/index https://doi.org/10.37934/araset.44.1.225238 |
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1806430296094015488 |
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13.18916 |