Modeling DDOS attacks in sdn and detection using random forest classifier

ABSTRACT

A Software-defined network paradigm provides flexibility and programmability to deal with the growing users of future networks. As a result of the centralized control attribute, it could be regarded as a single point of failure that is vulnerable to various forms of attacks, such as Distributed denial of service (DDOS) attacks. This study attempts to show a mathematical representation of DDOS attacks in SDN, together with how some five-tuple features contribute to the attacks. The studied features were used to detect DDOS using a random forest classifier. The result shows 96.3% detection accuracy and 96.45% precision.

KEYWORDS:

• SDN
• DDOS attacks
• detection
• random forest
• attack modelling

Acknowledgements

The authors would like to thank the referees, reviewers and editors for their valuable comments and their feedback for better improvement of this article.

Disclosure statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.