Akademik Veri Yönetim Sistemi
International Congress on Multidisciplinary Natural Sciences and Engineering, ICOMNAS 2021, Ankara, Türkiye, 1 - 02 Aralık 2021, ss.90
Computer
networks are facing an increasing number of threats. Therefore, establishing
and maintaining a secure computing environment is very important. Researchers
use variety of methods to ensure the security of networked systems with
anomaly-based intrusion detection systems (IDS). Data classification is one of
the main problems of these anomaly-based detection. Artificial bee colony
algorithm is an effective optimization algorithm that models foraging behavior
of bees in nature. In this paper, an artificial bee colony algorithm based,
semi-supervised intrusion detection method is proposed to optimize the cluster
centers and identify the best clustering solutions. Experimental studies are
carried out on different sub-sets of KDD Cup 99 database to evaluate the
performance of the proposed method. Test results show that the proposed
algorithm can be used as a model for anomaly-based intrusion detection system.