Socio-technical Automotive Security Design Patterns: Applying a Stakeholder-Based Approach to Securing Self-Driving Vehicles
Year: 2024
Type: conference-paper
Abstract: Broadening the scope and the sophistication of onboard and outward facing communication is a key enabling technology for autonomous vehicles. With these communication advances come increased automotive cybersecurity vulnerabilities that may be exacerbated by a broader range of stakeholders who interact with the vehicles. Stakeholders include the consumer using the vehicle, the technicians working on the car, vendors for third-party devices, and the engineers designing the software. As such, the autonomous vehicle has become a quintessential socio-technical system, one that integrates people, technology, and other systems, all of which operate interactively with technical and social dependencies. As a complement to the increasing volume of research and techniques that address technical solutions to automotive cybersecurity (e.g., intrusion detection, encryption schemes, etc.), we broaden the range of stakeholders who can contribute human-based prevention solutions. Specifically, by integrating crime theory-based prevention and human behavior with technical strategies, this paper presents a collection of reusable socio-technical design patterns to address automotive cybersecurity.
Authors: Nick Polanco, Betty H. C. Cheng
Institution: Michigan State University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4403935784