Comparative analysis of whale and Harris Hawks optimization for feature selection in intrusion detection
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Abstract
This research paper explores the efficacy of two nature-inspired optimization algorithms, the whale optimization algorithm (WOA) and Harris Hawks optimization (HHO), for feature selection in the context of intrusion detection and prevention systems (IDPS). Leveraging the NSL-KDD dataset as a benchmark, our study employs Python for implementation and uses decision tree (DT) as the classification model. The objective is to assess the impact of the HHO and WOA optimization techniques on the performance of IDPS through feature selection. The WOA and HHO techniques were able to lessen the features from 40 to 16 and 13, respectively. Results indicate that DT integrated with HHO achieves an impressive accuracy of…
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149
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- FWCI
- 63.30
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Authors
4Topics & keywords
Keywords
- Whale
- Feature selection
- Intrusion detection system
- Selection (genetic algorithm)
- Computer science
- Artificial intelligence
- Feature (linguistics)
- Intrusion
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