Securing Vehicular Ad-Hoc Networks Against Blackhole Attacks Using an Enhanced Trust Management Framework

Vehicular Ad-Hoc Networks (VANETs) are essential for Intelligent Transportation Systems, enabling vehicle-to-vehicle and vehicle-to-infrastructure communication to improve road safety and traffic efficiency.  However, VANETs are vulnerable to blackhole attacks, where malicious vehicles drop legitimate packets, disseminate false information, and provide misleading recommendations, thereby compromising network performance and trust.  This study proposes an Enhanced Trust Management Framework (ETMF) that integrates neighbour monitoring, local and global trust evaluation, and collaborative decision-making between vehicles and Road Side Units (RSUs) to mitigate blackhole attacks.  ETMF was implemented and evaluated using OMNeT++ 5.6.2, SUMO 1.8.0, and VEINS 5.2 in a realistic Abuja road network scenario comprising 50 vehicles, 5 RSUs, and 0–40 malicious nodes over a 600-second simulation period.  The framework was compared with TEAM and FIDS-HMM using metrics such as end-to-end delay, anomaly detection ratio, convergence rate, event detection ratio, content delivery ratio, packet loss ratio, and computational overhead.  Results showed that ETMF reduced end-to-end delay by up to 25%, improved anomaly detection by up to 8%, and increased detection rates by 2.06%–8.33% compared with FIDS-HMM under blackhole attack conditions.  ETMF also achieved faster network convergence while maintaining acceptable computational overhead.  These findings indicate that ETMF enhances trust management and blackhole attack mitigation in VANETs under realistic mobility conditions.  Future work will focus on improving convergence behaviour and event detection performance in larger and more densely populated vehicular networks.  Source code, simulation configurations, and parameter settings will be made publicly available upon publication.