A comparison of several intrusion detection methods using the NSL-KDD dataset
The increasing significance of cybersecurity underscores the critical necessity of addressing evolving methods of hackers. This research investigates the way to classify and predict cyber-attacks on the NSL-KDD dataset using intrusion detection methods the investigation contrasts the capabilities o...
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| Format: | Article |
| Language: | English |
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College of Computer and Information Technology – University of Wasit, Iraq
2024-06-01
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| Series: | Wasit Journal of Computer and Mathematics Science |
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| Online Access: | http://wjcm.uowasit.edu.iq/index.php/wjcm/article/view/251 |
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| author | hazem salim abdullah |
| author_facet | hazem salim abdullah |
| author_sort | hazem salim abdullah |
| collection | DOAJ |
| description |
The increasing significance of cybersecurity underscores the critical necessity of addressing evolving methods of hackers. This research investigates the way to classify and predict cyber-attacks on the NSL-KDD dataset using intrusion detection methods the investigation contrasts the capabilities of various algorithms, including RNN, MLP, CNN-LSTM, and ANN, in recognizing attacks. The results indicate that both MLP and RNN have the greatest efficiency and effectiveness for different time frames. these findings demonstrate the necessity of Constant evaluation and enhancement of intrusion detection systems in order to remain aware of the dynamic nature of the cyber threat landscape. Addressing cybersecurity issues necessitates a comprehensive approach that combines computational enhancements, human talent, organizational policies, and regulatory frameworks in order to create a powerful and stable cybersecurity system.
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| format | Article |
| id | doaj-art-5a55fbadca5e4a719be126f0672415bc |
| institution | Kabale University |
| issn | 2788-5879 2788-5887 |
| language | English |
| publishDate | 2024-06-01 |
| publisher | College of Computer and Information Technology – University of Wasit, Iraq |
| record_format | Article |
| series | Wasit Journal of Computer and Mathematics Science |
| spelling | doaj-art-5a55fbadca5e4a719be126f0672415bc2025-01-30T05:23:49ZengCollege of Computer and Information Technology – University of Wasit, IraqWasit Journal of Computer and Mathematics Science2788-58792788-58872024-06-013210.31185/wjcms.251A comparison of several intrusion detection methods using the NSL-KDD datasethazem salim abdullah0Directorate of Municipalities Nineveh Governorate, Mosul, IRAQ The increasing significance of cybersecurity underscores the critical necessity of addressing evolving methods of hackers. This research investigates the way to classify and predict cyber-attacks on the NSL-KDD dataset using intrusion detection methods the investigation contrasts the capabilities of various algorithms, including RNN, MLP, CNN-LSTM, and ANN, in recognizing attacks. The results indicate that both MLP and RNN have the greatest efficiency and effectiveness for different time frames. these findings demonstrate the necessity of Constant evaluation and enhancement of intrusion detection systems in order to remain aware of the dynamic nature of the cyber threat landscape. Addressing cybersecurity issues necessitates a comprehensive approach that combines computational enhancements, human talent, organizational policies, and regulatory frameworks in order to create a powerful and stable cybersecurity system. http://wjcm.uowasit.edu.iq/index.php/wjcm/article/view/251Cyber Securityintrusion detection systemDeep LearningMachine learning |
| spellingShingle | hazem salim abdullah A comparison of several intrusion detection methods using the NSL-KDD dataset Wasit Journal of Computer and Mathematics Science Cyber Security intrusion detection system Deep Learning Machine learning |
| title | A comparison of several intrusion detection methods using the NSL-KDD dataset |
| title_full | A comparison of several intrusion detection methods using the NSL-KDD dataset |
| title_fullStr | A comparison of several intrusion detection methods using the NSL-KDD dataset |
| title_full_unstemmed | A comparison of several intrusion detection methods using the NSL-KDD dataset |
| title_short | A comparison of several intrusion detection methods using the NSL-KDD dataset |
| title_sort | comparison of several intrusion detection methods using the nsl kdd dataset |
| topic | Cyber Security intrusion detection system Deep Learning Machine learning |
| url | http://wjcm.uowasit.edu.iq/index.php/wjcm/article/view/251 |
| work_keys_str_mv | AT hazemsalimabdullah acomparisonofseveralintrusiondetectionmethodsusingthenslkdddataset AT hazemsalimabdullah comparisonofseveralintrusiondetectionmethodsusingthenslkdddataset |