Vehicular ad hoc networks (VANETs) facilitate vehicles to broadcast beacon messages to ensure road safety. The rogue nodes in VANETs broadcast malicious information leading to potential hazards, including the collision of vehicles. Previous researchers used either cryptography, trust values, or past vehicle data to detect rogue nodes, but they suffer from high processing delay, overhead, and false-positive rate (FPR). We propose fog-based rogue nodes detection (F-RouND), a fog computing scheme, which dynamically creates a fog utilizing the on-board units (OBUs) of all vehicles in the region for rogue nodes detection. The novelty of F-RouND lies in providing low processing delays and FPR at high vehicle densities. The performance of our F-RouND framework was carried out with simulations using OMNET++ and SUMO simulators. Results show that F-RouND ensures 45% lower processing delays, 12% lower overhead, and 36% lower FPR at high vehicle densities compared to existing rogue nodes detection schemes.
翻译:甚小孔网的无赖节点播放了可能导致潜在危险,包括车辆碰撞的恶意信息。以前的研究人员使用加密、信任值或以往的车辆数据来探测无赖节点,但他们受到高处理延迟、高管理费和假阳性率(FPR)的影响。我们建议进行雾基无赖节点探测(F-RouND),这是一种雾计算办法,它动态地利用该区域所有车辆的机载单位(OBU)制造雾,进行无赖节点探测。F-RouND的新颖之处在于提供低处理延迟和高车辆密度的FPR。我们的F-RouND框架在使用OMNET++和SUMO模拟器进行模拟,结果显示F-RouND确保高车辆密度的FPR比现有的无赖节点探测办法低45%、低12%和低36%。