TR-DSR: A Trusted and Reputation-based Protocol for Securing Data Transmission in the Internet of Vehicle Things (IoVT) against Black Hole Attacks

Abstract

Ensuring the secure dissemination of authenticated data in the Internet of Vehicle Things (IoVT) is vital due to the critical role of Intelligent Transport Systems (ITS). These systems operate in environments characterized by dynamic vehicles, open and shared communication channels, self-organized and distributed networks, and a lack of centralized infrastructure. Such conditions make the IoVT susceptible to various security threats, including both internal and external attacks. Among internal threats, the black hole attack poses a significant challenge by dropping incoming packets intended for forwarding, thereby disrupting normal operations and degrading system performance. To mitigate this issue, this study introduces a Trusted and Reputation-based Dynamic Source Routing (TR-DSR) protocol. The TR-DSR protocol aims to enhance secure data transmission by identifying and eliminating malicious vehicles involved in black hole attacks while ensuring authentication among communicating vehicles. Advanced techniques, including Q-learning and Multi-Agent Systems (MAS), are integrated into TR-DSR to strengthen its security capabilities. The proposed protocol's performance has been evaluated through simulations using various metrics and compared with existing approaches. The results demonstrate the superiority of the TR-DSR protocol, emphasizing its effectiveness in addressing security challenges within the IoVT.