Moody Alhanaya, Khalil Hamdi Ateyeh Al-Shqeerat*
Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3709-3724, 2023, DOI:10.32604/iasc.2023.036856
Abstract The increasing number of security holes in the Internet of Things (IoT) networks creates a question about the reliability of existing network intrusion detection systems. This problem has led to the developing of a research area focused on improving network-based intrusion detection system (NIDS) technologies. According to the analysis of different businesses, most researchers focus on improving the classification results of NIDS datasets by combining machine learning and feature reduction techniques. However, these techniques are not suitable for every type of network. In light of this, whether the optimal algorithm and feature reduction techniques can be generalized across various datasets… More >
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