DDoS Detection in SDN Switches using Support Vector Machine Classifier
- 10.2991/jimet-15.2015.63How to use a DOI?
- SDN Switches, Distributed Denial-of-Service (DDoS), Support Vector Machine (SVM), Genetic Algorithm (GA)
Compared with traditional network, Software Defined network (SDN) technology contains data plane, control plane and application plane. The control plane centralized controls multiple switches instead of only one switch. Therefore, SDN has more security requirements. The existing network security equipment already can no longer adapt to the environment of SDN. Distributed Denial-of-Service Attacks (DDoS) is one of the most major threats. DDoS detection is necessary for SDN switches. Support vector machine (SVM) classification technology is widely used in various fields. In this article, we will detect DDoS attacks using SVM optimized parameter c and g with cross validation-genetic algorithm (CV-GA). The experiments show that CV-GA-SVM classification performs better than others.
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Xue Li AU - Dongming Yuan AU - Hefei Hu AU - Jing Ran AU - Shulan Li PY - 2015/12 DA - 2015/12 TI - DDoS Detection in SDN Switches using Support Vector Machine Classifier BT - Proceedings of the 2015 Joint International Mechanical, Electronic and Information Technology Conference PB - Atlantis Press SP - 344 EP - 348 SN - 2352-538X UR - https://doi.org/10.2991/jimet-15.2015.63 DO - 10.2991/jimet-15.2015.63 ID - Li2015/12 ER -