Title: Intelligent hybrid detection and mitigation of Distributed Denial of Service Attacks in SDN

Author(s): Douglas Omuro Makori1, Seckin Ari2

Affiliation: 1Department of computer engineering Sakarya University Turkey

2Associate Professor Department of Computer Engineering Sakarya University Turkey

 DOI : https://dx.doi.org/10.18535/ijecs/v6i12.01


             


Abstract

Distributed denial of service attacks are a becoming a norm in today’s networked information systems. They were there, they are here and will continue being here because of the dynamic nature and difficulty in detecting the myriad types of DDoS attacks. They are even becoming more complicated by the coming of age of internet of things with so many devices being connected to the internet. Software defined networking is a new unexplored field so it might be given more attention by hackers because of the “cool” tag as a result of that propose a mechanism for detecting DDoS attacks in software networks through the use of machine learning support vector machines for detecting the DDoS attacks we also use entropy counter to be able to mitigate the DDoS attack by installing flow rules in Openflow switches to block the source of the flooding in the network


License: This work is licensed under a Creative Commons Attribution 4.0 International License.

 

Website: http://www.ijecs.in

e-ISSN:  2319-724

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