A statistical approach for enhancing security in VANETs with efficient rogue node detection using fog computing

Rogue nodes broadcasting false information in beacon messages may lead to catastrophic consequences Vehicular Ad Hoc Networks (VANETs). Previous researchers used cryptography, trust scores, or past vehicle data detect rogue nodes; however, these methods suffer from high processing delay, overhead, and False–Positive Rate (FPR). We propose herein Greenshield's traffic model–based fog computing scheme called Fog–based Node Detection (F–RouND), which dynamically utilizes the On–Board Units (OBUs) of all vehicles region for node detection. aim reduce delays FPR detecting at densities. The performance F–RouND framework was evaluated via simulations. Results show that ensures 45% lower delays, 12% 36% urban scenario than existing detection schemes even when number increases by up 40% region.