A Fuzzy-Based Greedy Behaviour Attack Detection Approach in VANETs

Abstract

Vehicular Ad-Hoc Networks (VANETs) are susceptible to various types of attacks due to their characteristics. Among these threats, greedy behaviour attacks stand out, necessitating the update and adaptation of security measures to mitigate this evolving threat. While much of the existing literature on greedy behaviour attacks has focused on the CSMA/CD protocol, this paper shifts its focus to the Time Division Multiple Access (TDMA) protocol, specifically the Distributed Time Division Multiple Access (DTMAC) protocol. The aim is to uncover potential greedy actions that attackers could exploit. We carefully analyze the DTMAC protocol and identify four new greedy actions, revealing new vulnerabilities that have not been explored before. To prevent these newly discovered behaviours, we implement a new watchdog system that utilises fuzzy logic. This watchdog system acts as a robust defense mechanism, actively identifying potential attackers who display greedy actions within the DTMAC protocol. Extensive simulations using NS2 were carried out for validation and evaluation purposes. The outcomes of our experiments show outstanding performance metrics such as accuracy, precision, recall, and F1 score. These results highlight the effectiveness of our suggested watchdog-based method in identifying greedy behaviour attackers in the DTMAC protocol.

Keywords Vehicular Ad-Hoc Networks (VANETs), Greedy Behaviour Attacks, Distributed Time Division Multiple Access (DTMAC), Watchdog System, Fuzzy Logic Detection