• VISHNUPRIYA C
• CHANDINI C S
• SUMI NAUSHAD
• VAIDEHI S JAYAN
• SHAMIN S

Distributed Denial of Service(DDoS) attack is considered as one of the foremost complicated vulnerability threats in the Cyber Physical System. Detection and mitigation of such attacks in an efficient manner with better accuracy is the challenging need of the hour. In this paper, we proposed a model to detect the real time DDoS attack in the network and to block such assaults from entering the Software Defined Networking. The model displays the details of the system from which malicious packets have been sent and hence we can block that IP address from sending further packets to the destination host. So that the normal traffic and other network devices are not get affected and continues their service. And also it includes a provision to detect various categories of attacks in a log file. On passing a log file to the model it detects the types of attack as well as the count of the various detected attacks. The evaluation is done by using KDD 99 dataset, which is widely used for the detection of DDoS attack, using Naïve Bayes and Decision tree classifier. The performance of the model is found to be 98% accurate with less space and time complexity. This model is regarded as the par excellence of computer and network security fields.

CPS,DDoS,SDN

"DDoSNET: AN EFFICIENT DDoS ATTACK DETECTION AND MITIGATION MODEL IN THE SOFTWARE DEFINED NETWORKING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 6, page no.a465-a469, June-2021, Available :http://www.jetir.org/papers/JETIR2106059.pdf

"DDoSNET: AN EFFICIENT DDoS ATTACK DETECTION AND MITIGATION MODEL IN THE SOFTWARE DEFINED NETWORKING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 6, page no. ppa465-a469, June-2021, Available at : http://www.jetir.org/papers/JETIR2106059.pdf