A hybrid meta-heuristic algorithm to detect malicious activity based on dynamic VANET environmental information

VANET has the characteristics of self-organisation, rapid topology changes, and frequent link disconnection that perhaps lead to challenging issues. In order to mitigate these issues, a highly effective technology is required; therefore, this work has adopted a Hybrid Firefly Optimisation Algorithm (FOA) and a Whale Optimisation Algorithm (WOA) i.e., named as HFWOA-VANET. The HFWOA-VANET has the features of both meta-heuristic algorithms and is implemented for enhancing the performance of VANET. This process is mainly based on consideration of Quality of Service (QoS) parameters of each vehicle. Therefore, the performance of vehicles can be determined, which enables better service in VANET platform. The implementation of this work is done on NS2 platform and the obtained results are analysed for ensuring the performance of the proposed model. Moreover, the performance of the model is compared with the existing technology; therefore, the proposed model can be ensured as a more effective technique than the existing technique in terms of performance metrics.