| Abstrakt: |
Software Defined Networks is an emerging technology in modern technological manageable, dynamic, low-priced and adaptable environment, however these network are vulnerable to attack specially Distributed Denial of Service attack, the main objective of this research is to detect and mitigated these attack by using machine learning (support vector machine algorithm), two scenarios for topology connected using Vm-ware program-mininet, two types of sdn controllers were used, the most important noteworthy is that in normal traffic operation pox controller connects better than ryu controller for the same data set and topolpogy, whereas ryu makes more progress in throughput when the network is exposed to ddos attack, while if we measure round trip time ryu is better than pox in normal operation but in ddos attack pox is better, the percentage value for the throughput for pox controller in normal traffic is 93% & for ryu 87%, while in attack traffic ryu 87% in pox 35%, the round trip time in attack traffic is 94% for pox controller while for ryu is 8.7% so ryu is better in attack traffic which is one of the most important finding in this research. [ABSTRACT FROM AUTHOR] |
