Intrusion Detection System in Computer Network Using Hybrid Algorithms (SVM and ABC)

In recent years, the needs of the Internet are felt in lives of all people.Accordingly, many studies have been done on security in virtual environment. Oldtechnics such as firewalls, authentication and encryption could not provide Internetsecurity completely; So, Intrusion detection system is created as a new solution anda defense wall in cyber environment. Many studies were performed on differentalgorithms but the results show that using machine learning technics and swarmintelligence are very effective to reduce processing time and increase accuracy aswell. In this paper, hybrid SVM and ABC algorithms has been suggested to selectfeatures to enhance network intrusion detection and increase the accuracy ofresults. In this research, data analysis was undertaken using KDDcup99. Such thatbest features are selected by Support vector machine, then selected features arereplaced in the appropriate category based on artificial bee colony algorithm toreduce the search time, increase the amount of learning and improve theauthenticity of intrusion detection. The results show that the proposed algorithm candetect intruders accurately on network up to 99.71%.

Keywords:

Intrusion Detection System , Support Vector Machine , Classification , Bee colony Algorithm