2020
DOI: 10.3837/tiis.2020.02.013
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A Nature-inspired Multiple Kernel Extreme Learning Machine Model for Intrusion Detection

Abstract: The application of machine learning (ML) in intrusion detection has attracted much attention with the rapid growth of information security threat. As an efficient multi-label classifier, kernel extreme learning machine (KELM) has been gradually used in intrusion detection system. However, the performance of KELM heavily relies on the kernel selection. In this paper, a novel multiple kernel extreme learning machine (MKELM) model combining the ReliefF with nature-inspired methods is proposed for intrusion detect… Show more

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Cited by 3 publications
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