OAK

Suspicious Flow Forwarding for Multiple Intrusion Detection Systems on Software-Defined Networks

Metadata Downloads
Abstract
In recent years, there have been an increasing number of attacks on networks, such as the distributed denial-of-service attack. However, the traditional network is not sufficiently flexible to control the huge amount of traffic that now passes through an intrusion detection system. With SDN, which separates control planes and data planes for programmability, elasticity, and simplicity, it becomes possible to force traffic to pass through an IDS by simply rerouting or mirroring traffic to an IDS. This article focuses on how to distribute traffic to multiple IDSs in order to increase the detection of network attacks and balance IDS loads. A clustering-based flow grouping scheme that distributes flows according to routing information and flow data rate is proposed. Through experiments with a virtualized testbed, we show that the proposed scheme detects network attacks more quickly and achieves a better balance of traffic loads on the IDSs.
Author(s)
Ha, TaejinYoon, SeunghyunRisdianto, Aris CahyadiKim, Jong WonLim, Hyuk
Issued Date
2016-12
Type
Article
DOI
10.1109/MNET.2016.1600106NM
URI
https://scholar.gist.ac.kr/handle/local/14001
Publisher
Institute of Electrical and Electronics Engineers
Citation
IEEE Network, v.30, no.6, pp.22 - 27
ISSN
0890-8044
Appears in Collections:
Department of AI Convergence > 1. Journal Articles
공개 및 라이선스
  • 공개 구분공개
파일 목록
  • 관련 파일이 존재하지 않습니다.

Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.