Abstract
In order to improve network intrusion detection precision, this paper proposed a network intrusion detection model based on simultaneous selecting features and parameters of support vector machine (SVM) by particle swarm optimization (PSO) algorithm. Firstly, the features and parameters of SVM are coded to particle, and then the PSO is used to find the optimal features and SVM parameters by collaboration among particles, lastly, the performance of the model was tested by KDD Cup 99 data. Compared with other network models, the proposed model has reduced input features for SVM and has significantly improved the detection precision of network intrusion. DOI : http://dx.doi.org/10.11591/telkomnika.v12i2.3826
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: TELKOMNIKA Indonesian Journal of Electrical Engineering
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.