Controller-Targeted DDoS Attack Detection and Mitigation in Software-Defined Internet of Vehicles (SD-IoV)

Software-defined networking (SDN) is an emerging technology that decouples the control plane from the data plane, offering flexibility, central control, and programmability. It is beneficial for Internet of Vehicles (IoV) networks, which integrate Internet of Things (loT) and Vehicular Ad Hoc Network (VANET) to implement Intelligent Transportation Systems (ITS). By utilizing an SDN controller, IoV networks can benefit from centralized control and improved manageability. The integration of SDN and IoV, namely, the Software-Defined Internet of Vehicles (SD- IoV) has been a promising solution for future communication. However, the central controller exposes a single point of failure vulnerable to Distributed Denial of Service (DDo
$S$
) attacks. A DDoS attacker makes the SDN controller a clear target by flooding massive packet-in messages. To this end, we propose an efficient and lightweight attack detection and mitigation scheme in the SDN controller. To achieve this, a detection module using entropy and flow rate to identify attack traffic behavior, and a mitigation module by analyzing payload lengths is designed. Then, we applied an adaptive threshold computation for all parameter values. Finally, simulation has been conducted using SUMO, Mininet-WiFi, and Scapy. Simulation results reveal the effectiveness of the proposed scheme in terms of detection time, accuracy, mitigation efficiency, controller load, and link bandwidth consumption compared with existing works.