SDN based security using cognitive algorithm against DDOS

The internet and communication industry continue to develop new technologies rapidly, which has caused a boom in smart and networking device manufacturing. With new trends, operators are constantly battling towards deploying multiple systems to cater for the need of all users. The higher bandwidth utilization and flexibility demanded new networking solutions which paved way for Software Defined Network (SDN). SDN is centralized platform which works with other technologies such as Network Function Virtualization (NFV) to offer reliable, flexible and centrally controllable network solutions. It offers remote access control with logical design of the system, security and resource management. Traditional and new developing networks despite their advantages present numerous security challenges. With growing users worldwide, bandwidth related security risks such as Distributed Denial of Service (DDOS) are of grave concern. This encourages towards reliable and rapid response solutions such as Cognitive Algorithms (CA) which can adapt to a threat in real time environment. This dissertation proposes the use of CA to deploy security and mitigation measures against potential DDOS flooding attack to avoid network failure and memory depletion in SDN. The experiment done in proof of concept (PoC) provided proof of greater network resource utilization by limiting the attack while mitigation policies are implemented. It also shows that CA can adapt to growing and evolving network attack strength to counter as much as possible without the intervention of the operator. The work for future solutions based on CA and Artificial Intelligence (AI) for security have been established.

Grantor dc:publisher.institution

Department of Electrical Engineering

Year dc:date.issued

2018

Author dc:creator

• Faizan, Shah Ali

Advisor dc:contributor.advisor

• Mwangama, Joyce

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/11427/29880

OAI identifier oai:identifier

oai:open.uct.ac.za:11427/29880