Abstract
Intrusion detection is very important to ensure the security of information systems. Neural networks aided by metaheuristic algorithms have been shown to be an alternative for intrusion detection. However, the current methods require much time for the training of the neural networks. In this paper, we propose a beetle antennae search (BAS) algorithm based neural network for efficient intrusion detection. In order to highlight the superiority of the algorithm, we conduct numerical experiments with a simple neural network based on the KDD CUP 99 dataset, which show that the proposed method is effective.
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