LoGD-ai: An Efficient Network Intrusion Detection System Using a Soft Voting-Based Ensemble Learner
Isaac Agyapong,
Samuel Boateng,
Isaac Prempeh
et al.
Abstract:Network attacks detection is still a difficult task because of the large data volumes needed for training a cutting-edge machine learning algorithms to unearth network invasions. Recently, a number of data mining methods have been put out for network intrusion detection. Meanwhile, each of them encounters certain difficulties resulting from the sophisticated nature of threats the existing models cannot detect. The NSL-KDD dataset containing four different form of attacks was employed in this paper. In this pap… Show more
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