International Congress on Multidisciplinary Natural Sciences and Engineering, ICOMNAS 2021, Ankara, Turkey, 1 - 02 December 2021, pp.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.