A Lightweight Mitigation Approach against a New Inundation Attack in RPL-Based IoT Networks

Internet of Things (IoT) networks are being widely deployed for a broad range of critical applications. Without effective security support, such a trend would open the doors to notable security challenges. Due to their inherent constrained characteristics, IoT networks are highly vulnerable to the adverse impacts of a wide scope of IoT attacks. Among these, flooding attacks would cause great damage given the limited computational and energy capacity of IoT devices. However, IETF-standardized IoT routing protocols, such as the IPv6 Routing Protocol for Low Power and Lossy Networks (RPL), have no relevant security-provision mechanism. Different variants of the flooding attack can be easily initiated in RPL networks to exhaust network resources and degrade overall network performance. In this paper, a novel variant referred to as the Destination Information Object Flooding (DIOF) attack is introduced. The DIOF attack involves an internal malicious node disseminating falsified information to instigate excessive transmissions of DIO control messages. The results of the experimental evaluation demonstrated the significant adverse impact of DIOF attacks on control overhead and energy consumption, which increased by more than 500% and 210%, respectively. A reduction of more than 32% in Packet Delivery Ratio (PDR) and an increase of more than 192% in latency were also experienced. These were more evident in cases in which the malicious node was in close proximity to the sink node. To effectively address the DIOF attack, we propose a new lightweight approach based on a collaborative and distributed security scheme referred to as DIOF-Secure RPL (DSRPL). It provides an effective solution, enhancing RPL network resilience against DIOF attacks with only simple in-protocol modifications. As the experimental results indicated, DSRPL guaranteed responsive detection and mitigation of the DIOF attacks in a matter of a few seconds. Compared to RPL attack scenarios, it also succeeded in reducing network overhead and energy consumption by more than 80% while maintaining QoS performance at satisfactory levels.