Combating DDoS Attack with Dynamic Detection of Anomalous Hosts in Software Defined Network
Rudong Zhao, Songjie Wei, Milin Ren · 2017 International Conference on Current Trends in Computer, Electrical, Electronics and Communication (CTCEEC) · 2017
This paper proposes a Distributed Denial of Service (DDoS) attack detection and defense system based on Software Defined Networks (SDN) architecture. The system is composed of a monitoring module, a detection module and a reaction module. The monitoring module is designed to raise alerts by analyzing Packet_In messages. It detects and reports anomalies to the detection module for further evaluation, which overcomes the disadvantages of slow response and large overhead of periodic trigger detection. The reaction module can trace back attack traffic flows to quickly and accurately identify malicious hosts. The use of a SDN controller brings in a global view of the network topology in the monitoring and detection procedures for the access layer switch and reduces the processing range. This paper extends the OpenFlow protocol so that a flow entry can record and track the flow path information, which improves the efficiency and accuracy of attack traffic traceability. Simulation experiments show that the proposed scheme has a relatively faster response to DDoS attack with less processing pressure imposed on the controller.