Hybrid Intrusion Detection System for DDoS Attacks. (3rd April 2016)

• Record Type: Journal Article
• Authors: Cepheli, Özge; Büyükçorak, Saliha; Karabulut Kurt, Güneş
• Other Names: Ceccarelli Andrea Academic Editor.
• Is Part Of: Journal of electrical and computer engineering. Volume 2016(2016)
• Publication Date: 2016-04-03
• Subjects: Computer engineering -- Periodicals; Electrical engineering -- Periodicals; 621.3905
• DOI: 10.1155/2016/1075648
• Languages: English
• ISSNs: 2090-0147

Abstract

Abstract : Distributed denial-of-service (DDoS) attacks are one of the major threats and possibly the hardest security problem for today's Internet. In this paper we propose a hybrid detection system, referred to as hybrid intrusion detection system (H-IDS), for detection of DDoS attacks. Our proposed detection system makes use of both anomaly-based and signature-based detection methods separately but in an integrated fashion and combines the outcomes of both detectors to enhance the overall detection accuracy. We apply two distinct datasets to our proposed system in order to test the detection performance of H-IDS and conclude that the proposed hybrid system gives better results than the systems based on nonhybrid detection.