Application Research Of DDoS Attack Detection And Defense Methods Based On SDN

With the development and use of virtualization technology,cloud computing and 5G technology,the scale and complexity of services in the network have also increased.SDN has been rapidly promoted and applied,and DDoS attack is one of the biggest threats in the field of network security.In recent years,The Internet of Things technology is developing rapidly,The demand for the number of IP addresses is increasing,IPv6 technology will become an inevitable trend in the future.Therefore,studying DDoS attack detection and defense based on the SDN architecture in the IPv6 environment,It is great of significance to the security of SDN architecture.This theies aims at DDoS attack detection under the SDN architecture,based on the idea of binary classification,DDoS attack detection model based on BP neural network is constructed.Analyzed the characteristics of DDoS attacks,combined with the characteristics of the SDN architecture,using the flow entry information of the OpenFlow switch in the SDN architecture,six feature vectors is constructed as input to the detection model.The data is collected in the SDN simulation environment realize to train of the DDoS attack detection model.The experimental results show that the DDoS attack detection model based on BP neural network can reach 99.5%in accuracy.And compared with the based of SVM attack detection model,the performance based on the BP neural network model is better.Secondly,DDoS attack defense under SDN architecture,analyzed the short of the DDoS attack traceability method in the traditional network environment,take advantage of the characteristics of the SDN architecture,a method is studied that is based on Packet in threshold.The algorithm bases on the results of DDoS attack detection.Combined the controller master the entire network topology information in the SDN architecture.That is to implement traceability for DDoS attack,and Compared with the classical traceability algorithm in the traditional network architecture,that is easy to debug and maintain.Finally,based on the traceability results,this theies introduces a defense method through flow table entry control to filter DDoS attack packets from the source.In order to verify the effectiveness of the researched DDoS attack detection and defense methods,the Mininet simulation platform,Open vSwitch and Floodlight controller is used to build SDN simulation environment.Normal background traffic and attack traffic are simulated to test DDoS attack detection and defense methods.The simulation results show that the study of DDoS attack and defense methods can effectively realize the detection,traceability and defense of DDoS attacks in the network.