Novel Classification Method Using Hybridization of Fuzzy Clustering and Neural Networks for Intrusion Detection
In this paper, the authors propose a hybrid classifier using fuzzy clustering and several neural networks has been proposed. With using the fuzzy C-means algorithm, training samples will be clustered and the inappropriate data will be detected and moved to another dataset (removed-dataset) and used differently in the classification phase. Also, in the proposed method using the membership degree of samples to the clusters, the class of samples will be changed to the fuzzy class.
Subscribe to the Cybersecurity Insider Newsletter
Strengthen your organization's IT security defenses by keeping abreast of the latest cybersecurity news, solutions, and best practices. Delivered Tuesdays and Thursdays