A Feature Selection Approach Based On Hybridizing Flower Pollination Algorithm With Particle Swarm Optimization For Enhancing The Performance Of Ipv6 Intrusion Detection System
The proposed approach is evaluated using the “ICMPv6 dataset on different attacks”. The experimental results show that the first proposed approach achieved the best classification accuracy, i.e., 97.96% in terms of the number of features, and it reduced the number of features from 19 to 10 features....
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| Format: | Thesis |
| Language: | English |
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2023
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| Online Access: | http://eprints.usm.my/63003/ |
| _version_ | 1846218636341018624 |
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| author | Al Ghuraibawi, Adnan Hasan Bdair |
| author_facet | Al Ghuraibawi, Adnan Hasan Bdair |
| author_sort | Al Ghuraibawi, Adnan Hasan Bdair |
| description | The proposed approach is evaluated using the “ICMPv6 dataset on different attacks”. The experimental results show that the first proposed approach achieved the best classification accuracy, i.e., 97.96% in terms of the number of features, and it reduced the number of features from 19 to 10 features. In addition, the experimental findings demonstrate that the second proposed strategy achieved the best classification accuracy, i.e., 97.99% in terms of the number of characteristics. It reduced the number of features from 19 to 8 features. Finally, the experimental results showed that the third proposed approach achieved the best classification accuracy, i.e., 97.01% in terms of the number of features. It reduced the number of features from 19 to 4 features. |
| first_indexed | 2025-10-17T08:54:55Z |
| format | Thesis |
| id | usm-63003 |
| institution | Universiti Sains Malaysia |
| language | English |
| last_indexed | 2025-10-17T08:54:55Z |
| publishDate | 2023 |
| record_format | eprints |
| spelling | usm-630032025-10-16T07:40:46Z http://eprints.usm.my/63003/ A Feature Selection Approach Based On Hybridizing Flower Pollination Algorithm With Particle Swarm Optimization For Enhancing The Performance Of Ipv6 Intrusion Detection System Al Ghuraibawi, Adnan Hasan Bdair QA75.5-76.95 Electronic computers. Computer science The proposed approach is evaluated using the “ICMPv6 dataset on different attacks”. The experimental results show that the first proposed approach achieved the best classification accuracy, i.e., 97.96% in terms of the number of features, and it reduced the number of features from 19 to 10 features. In addition, the experimental findings demonstrate that the second proposed strategy achieved the best classification accuracy, i.e., 97.99% in terms of the number of characteristics. It reduced the number of features from 19 to 8 features. Finally, the experimental results showed that the third proposed approach achieved the best classification accuracy, i.e., 97.01% in terms of the number of features. It reduced the number of features from 19 to 4 features. 2023-12 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/63003/1/Pages%20from%20ADNAN%20HASAN%20BDAIR%20AL%20GHURAIBAWI%20-%20TESIS.pdf Al Ghuraibawi, Adnan Hasan Bdair (2023) A Feature Selection Approach Based On Hybridizing Flower Pollination Algorithm With Particle Swarm Optimization For Enhancing The Performance Of Ipv6 Intrusion Detection System. PhD thesis, Universiti Sains Malaysia. |
| spellingShingle | QA75.5-76.95 Electronic computers. Computer science Al Ghuraibawi, Adnan Hasan Bdair A Feature Selection Approach Based On Hybridizing Flower Pollination Algorithm With Particle Swarm Optimization For Enhancing The Performance Of Ipv6 Intrusion Detection System |
| title | A Feature Selection Approach Based On Hybridizing Flower Pollination Algorithm With Particle Swarm Optimization For Enhancing The Performance Of Ipv6 Intrusion Detection System |
| title_full | A Feature Selection Approach Based On Hybridizing Flower Pollination Algorithm With Particle Swarm Optimization For Enhancing The Performance Of Ipv6 Intrusion Detection System |
| title_fullStr | A Feature Selection Approach Based On Hybridizing Flower Pollination Algorithm With Particle Swarm Optimization For Enhancing The Performance Of Ipv6 Intrusion Detection System |
| title_full_unstemmed | A Feature Selection Approach Based On Hybridizing Flower Pollination Algorithm With Particle Swarm Optimization For Enhancing The Performance Of Ipv6 Intrusion Detection System |
| title_short | A Feature Selection Approach Based On Hybridizing Flower Pollination Algorithm With Particle Swarm Optimization For Enhancing The Performance Of Ipv6 Intrusion Detection System |
| title_sort | feature selection approach based on hybridizing flower pollination algorithm with particle swarm optimization for enhancing the performance of ipv6 intrusion detection system |
| topic | QA75.5-76.95 Electronic computers. Computer science |
| url | http://eprints.usm.my/63003/ |
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