Assessing Risk, Identifying and Analyzing Cybersecurity Threats to Automated Vehicles

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An introduction to the Mcity Threat Identification Model. It could help academic and industry researchers analyze the likelihood and severity of potential cybersecurity threats to automated vehicles.

Description:
Three hypothetical scenarios are defined in this document by University of Michigan researchers working with Mcity. They illustrate the breadth of the cybersecurity challenges that must be overcome before autonomous and connected vehicles can be widely adopted.

The Mcity Threat Identification Model outlines a framework for considering: the attacker's skill level and motivation; the vulnerable vehicle system components; the ways in which an attack could be achieved; and the repercussions, including for privacy, safety and financial loss.
Classification:
Connected and Automated Vehicles
Integration, Networking, and Communications
Product Lifecycle:
Pre-production: Research, Design, Development, Testing, and Tooling
Post-production: Service, Reuse, and Recycling
Resource Type:
Paper/Report
Institution:
Mcity, University of Michigan
Author & Title:
André Weimerskirch Lead, Mcity Cybersecurity Working Group Vice President, Cybersecurity, Lear Corporation Derrick Dominic Graduate Student Research Assistant, Robotics, University of Michigan
Date Developed:
Tuesday, January 16, 2018
Keywords:
automotive,autonomous,connected,technology,cybersecurity,infrastructure,mobility,safety,security,transportation,standards
Education Level:
Undergrad Students (13-14)
Undergrad Students (15-16)
Graduate Students
Audience:
Educators
General Public
Industry Professionals/Practitioners
Researcher
Students