Driverless vehicle security: Challenges and future research opportunities

As self-driving vehicles become increasingly popular, new generations of attackers will seek to exploit vulnerabilities introduced by the technologies that underpin such vehicles for a range of motivations (e.g. curiosity, criminally-motivated, financially-motivated and state-sponsored). For example, vulnerabilities in self-driving vehicles may be exploited to be used in terrorist attacks such as driving into places of mass gatherings (i.e. using driverless vehicles as weapons to cause death or serious bodily injury). This survey presents a categorized summary of security methodologies developed to secure sensing, positioning, vision, and network technologies that can be equipped in driverless-vehicles. These technologies have the potential to benefit their security from tailored machine learning models. Future research opportunities are also identified. (C) 2018 Elsevier B.V. All rights reserved.