Open AccessSvm Implementation for Ddos Attacks in Software Defined Networks
Author(s) -
Sugandhi Midha,
Gaganjot Kaur
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.a8166.1110120
Subject(s) - denial of service attack , computer science , support vector machine , network security , software defined networking , software , computer network , computer security , application layer ddos attack , data mining , artificial intelligence , the internet , operating system
Software Defined Network (SDN) is making software interaction with the network. SDN has made the network flexible and dynamic and also enabled the abstraction feature of applications and services. As the network is independent of any of the devices like in traditional networks there exist routers, hubs, and switches that is why it is preferable these days. Being more preferably used it has become more vulnerable in terms of security. The more common attacks that corrupt the network and hinders the efficiency are distributed denial-of-service (DDOS) attacks. DDOS is an attack that in general leads to exhaust of the network resources in turn stopping the controller. Detection of DDOS attacks requires a classification technique that provides accurate and efficient decision making. As per the analysis Support Vector Machine (SVM), the classifier technique detects more accurately and precisely the attacks. This paper produces a better approach to detecting attacks using SVM classifiers in terms of detection rate and elapsed time of the attack and it also predicts the various types of distributed denial of service attacks that have corrupted the network.