Situational crime prevention for automotive cybersecurity

Abstract

The increase in number and types of various stakeholders interacting with self-driving vehicles expands the relevant automotive cybersecurity attack vectors that can be compromised. Furthermore, given the prominent role that human behavior plays in the lifetime of a vehicle, social and human-based factors must be considered in tandem with the technical factors when addressing cybersecurity. A focus on informing and enabling stakeholders and their corresponding actions promotes security of the vehicle through a human-focused and technology-enabled approach. Example stakeholders include the consumer operating the vehicle, the technicians working on the car, and the engineers designing the software. Strategies can be applied in both a social and technical manner to increase preventative security measures for autonomous vehicles by leveraging theoretical foundations from the criminology domain. In this work we harness a criminology theory approach to crime prevention, where we synergistically combine cybercrime theory, human factors, and technical solutions to develop a cybercrime prevention framework that accounts for a range of stakeholders relevant to an autonomous vehicle domain.