评估风险：识别和分析自动驾驶汽车的网络安全威胁.pdf
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January 2018 1
Assessing Risk:
Identifying and Analyzing Cybersecurity
Threats to Automated Vehicles
INTRODUCTION
It’s no secret that developers of automated vehicles face a host of complex issues
to be solved before self-driving cars can hit the road en masse, from building the
necessary infrastructure and defining legal issues to safety testing and coping with the
vagaries of weather and urban environments. In addition, developers face huge risks if
they neglect the vital issue of cybersecurity in automated vehicles.
Driverless vehicles will be at least as vulnerable to all the existing security threats that
regularly disrupt our computer networks. That could include data thieves who want to
glean personal and finance information, spoofers who present incorrect information to
a vehicle, and denial-of-service attacks that move from shutting down computers to
shutting down cars.
Cybersecurity is an overlooked area of research in the development of driverless vehicles,
even though many threats and vulnerabilities exist, and more are likely to emerge as the
technology progresses to higher levels of automated mobility. Although no over-arching
solutions are obvious at this point, Mcity researchers have developed the first tool and
methodology for assessing cybersecurity risks in automated vehicles. This marks not only
Contents
1 Introduction
2 Understanding the
Vulnerabilities
3 Mcity Threat Identification
Model
6 A Changing Perspective
7 More Technology,
More Threats
8 Thinking Long-Term
10 Resources
ANDRÉ WEIMERSKIRCH
Lead, Mcity Cybersecurity
Working Group
Vice President, Cybersecurity,
Lear Corporation
DERRICK DOMINIC
Graduate Student Research Assistant,
Robotics, University of Michigan
CYBERSECURITY
Assessing Risk: Identifying and Analyzing Cybersecurity Threats to Automated Vehicles January 2018 2
an important step in solving these problems, but also presents a blueprint to effectively
identify and analyze cybersecurity threats and create effective approaches to make
automated vehicle systems safe and secure.
There are the new cybersecurity threats unique to automated vehicles, including hackers
who would try to take control over or shut-down a vehicle, criminals who could try to
ransom a vehicle or its passengers and thieves who would direct a self-driving car to
relocate itself to the local chop-shop.
Also, there are security threats to the wide-ranging networks that will connect with
automated vehicles, from financial networks that process tolls and parking payments
to roadway sensors, cameras and traffic signals to the electricity grid and our personal
home networks. Consider the seemingly nonthreatening convenience of an automated
car that gets within 15 minutes of your home and automatically turns on your furnace or
air conditioner, opens the garage and unlocks your front door. Any hacker who can breach
that vehicle system would be able to walk right in and burglarize your home.
Researchers affiliated with the University of Michigan’s Mcity connected and automated
vehicle center are finding that the complex and wide-ranging issue of cybersecurity
specific to automated vehicles and the infrastructure that will support them is just
beginning to be recognized, and will become more important as the development of
these vehicles progresses. Without robust, sophisticated, bullet-proof cybersecurity for
automated vehicles, systems and infrastructure, a viable, mass market for these vehicles
simply won’t come into being.
UNDERSTANDING THE VULNERABILITIES
The threats to automated vehicles can come through any of the systems that connect
to the vehicle’s sensors, communications applications, processors, and control systems,
as well as external inputs from other vehicles, roadways, infrastructure and mapping and
GPS data systems. In addition, the control systems of each vehicle for speed, steering
and braking are exposed to attacks.
Each individual automated application will require its own unique threat analysis that maps
its vulnerabilities and assesses the level of risk presented. New work by researchers
working with Mcity on adapting existing automotive threat models demonstrates how
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