Hybrid Intrusion Detection System for DDoS Attacks


Cepheli O., Buyukcorak S., Karabulut Kurt G. Z.

JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING, 2016 (Journal Indexed in ESCI) identifier identifier

  • Publication Type: Article / Article
  • Publication Date: 2016
  • Doi Number: 10.1155/2016/1075648
  • Title of Journal : JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING

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.