Abstract
Unsupervised fuzzy c-means clustering (FCM) algorithm is applied to intrusion detection so that intrusion detection system can directly deal with unlabeled original network data. Because particle swarm optimization (PSO) algorithm is easy to implement global optimum, FCM algorithm is improved based on particle swarm algorithm, in order to address the deficiencies that FCM is easy to fall into local optimum when applied to intrusion detection system. The unsupervised clustering result is further association amended and the accuracy and adaption of the intrusion detection system is improved.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.