Abstract:

As the Internet of Vehicles matures and becomes widely used,the security challenges that come with it are increasing.Vehicular networks and smart cars are classic applications of inter-connected systems.Smart vehicles not only have networks connecting their internal components,but also are connected to the outside world by roadside units and other vehicles.In some cases,the internal and external network packets pass through the same hardware and are merely isolated by software defined rules.Any misconfiguration opens a window for the hackers to intrude into vehicles’ internal components,which can lead to disastrous outcomes.In this paper,we define two covert attacks in the context of cruise control and propose a novel intrusion detection and compensation method to disclose and respond to such attacks.First,we employ a neural network identifier in the IDS engine to estimate the system output dynamically and compare it with the ACC output.If any anomaly is detected,an embedded compensation controller kicks in and takes over the control of the system.We conducted extensive experiments in the MATLAB to evaluate the effectiveness of the proposed scheme in a simulated environment.

Key words: internet of vehicles, adaptive cruise control, intrusion detection system, neural network, cyber physical systems, software defined network, vehicular ad-hoc networks