A novel approach to minimize the Black Hole attacks in Vehicular IoT Networks

Vehicular Ad-hoc IoT Networks (VA-IOT) have gained significant attention due to their ability to enable the distributed data transmission between vehicles to vehicle. However, VA-IOT are susceptible to various security threats, including the Black Hole attack. With Black Hole attacks, an intruder or malicious node attracts the internet traffic by broadcasting fake messages and drops all the received packets, which can significantly impact the network's performance. To mitigate, this paper presents an new mechanism to minimize the Black Hole attack on VANETs by combining two techniques: a trust management system and an intrusion detection system. The proposed approach involves assigning trust values to each vehicle based on their past behavior and routing packets through only trusted nodes. Additionally, an intrusion detection system is used to identify malicious nodes that violate the trust threshold and to take appropriate measures. The performance of the proposed approach is outperformed in terms of achievable end-to-end throughput and minimized network delays.