Real-time DDoS flooding attack detection in intelligent transportation systems. (July 2022) - Karthikeyan, H.; Usha, G.
Abstract: Integrated Intelligent Transportation System (IITS) is built by the emergence of the Internet of Vehicles (IoV) and the employment of the Internet of Things (IoT) in the transportation field for improving traffic efficiency, avoiding accidents, and improving the safety experience in driving. Large-scale networks, dynamic topology structure, uneven nodes distribution, and unlimited mobility are the characteristics of IITS. It increased the risk of a variety of attacks related to authentication, credentials, availability, privacy, routing, and legitimacy of data. Distributed Denial of Service (DDoS) flooding attack plays a vital role in impairing Road Side Units (RSU) of IITS and is capable of evading classical data filtering methods. In this paper, a novel DDoS flooding attack detection method is proposed for ensuring the security of IITS by employing reinforcement learning. The proposed framework is implemented by addressing the security requirements of ITS and overcoming the flaws of existing detection methods in advanced vehicular systems. In addition, the Q learning algorithm is designed along with the framework. Other attacks, in addition to DDoS flooding attacks, should be mitigated in the future to ensure a completely secure connection.