DDoS Attack Detection Based on Entropy and SVM Algorithm
In response to the vulnerability of Software Defined Network (SDN) to Distributed Denial of Service (DDoS) attacks, a DDoS attack detection method based on entropy and Support Vector Machine (SVM) algorithm is proposed. When detecting the entropy value of flow information in the network, if the entropy value cannot be determined, the required feature values are parsed from the Packet-In event, and then SVM algorithm is used to classify and predict the DDoS attack status. Mininet simulator and RYU controller are applied to establish a model for simulation detection. The result shows that the detection accuracy is high and the real-time resistance to DDoS attacks is good.
万方数据
维普
