Tech Briefs Magazine - November 2023 - 37

Sensors
Laser Attack Blinds Autonomous Vehicles, Deleting
Pedestrians and Confusing Cars
New research reveals that expertly timed lasers shined at an approaching LiDAR system
can create a blind spot in front of the vehicle large enough to completely hide moving
pedestrians and other obstacles.
University of Florida, Gainesville, FL
S
elf-driving cars, like the human drivers
that preceded them, need to see
what's around them to avoid obstacles
and drive safely.
The most sophisticated autonomous vehicles
typically use LiDAR, a spinning radar-type
device that acts as the eyes of the
car. LiDAR provides constant information
about the distance to objects so the car
can decide what actions are safe to take.
But these eyes, it turns out, can be tricked.
New research reveals that expertly
timed lasers shined at an approaching
LiDAR system can create a blind spot in
front of the vehicle large enough to completely
hide moving pedestrians and other
obstacles. The deleted data causes the
cars to think the road is safe to continue
moving along, endangering whatever
may be in the attack's blind spot.
This is the first time that LiDAR sensors
have been tricked into deleting data about
obstacles. The vulnerability was uncovered
by researchers from the University of
Florida, the University of Michigan, and
the University of Electro-Communications
in Japan. The scientists provide upgrades
that could eliminate this weakness
to protect people from malicious attacks.
The findings were presented at the 2023
USENIX Security Symposium and are publicly
available online.
LiDAR works by emitting laser light and
capturing the reflections to calculate distances,
much like how a bat's echolocation
uses sound echoes. The attack creates
fake reflections to scramble the sensor.
" We mimic the LiDAR reflections with
our laser to make the sensor discount
other reflections that are coming in from
genuine obstacles, " said Sara Rampazzi,
Professor of Computer and Information
Science and engineering, who led the
study. " The LiDAR is still receiving genuine
data from the obstacle, but the data
are automatically discarded because our
fake reflections are the only ones perceived
by the sensor. "
Tech Briefs, November 2023
LiDAR
Pedestrian
Spoofer
With the right timing, lasers shined at autonomous vehicles' LiDAR sensors can delete data about
obstacles like pedestrians. (Image: The researchers)
The scientists demonstrated the attack
on moving vehicles and robots with the attacker
placed about 15 feet away on the
side of the road. But in theory it could be
accomplished from farther away with upgraded
equipment.
The technology required is all fairly
basic, but the laser must be perfectly
timed to the LiDAR sensor and moving
vehicles must be carefully tracked to
keep the laser pointing in the right
direction.
" It's primarily a matter of synchronization
of the laser with the LiDAR device.
The information you need is usually
publicly available from the manufacturer, "
said S. Hrushikesh Bhupathiraj, a
doctoral student in Rampazzi's lab and
one of the lead authors of the study.
Using this technique, the scientists were
able to delete data for static obstacles and
moving pedestrians. They also demonstrated,
with real-world experiments, that
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the attack could follow a slow-moving vehicle
using basic camera tracking equipment.
In simulations of autonomous vehicle
decision making, this deletion of data
caused a car to continue accelerating toward
a pedestrian it could no longer see
instead of stopping as it should.
Updates to the LiDAR sensors or the
software that interprets the raw data
could address this vulnerability. For example,
manufacturers could teach the
software to look for the telltale signatures
of the spoofed reflections added by
the laser attack.
" Revealing this liability allows us to
build a more reliable system, " said Yulong
Cao, primary author of the study.
" In our paper, we demonstrate that previous
defense strategies aren't enough,
and we propose modifications that
should address this weakness. "
For more information, contact Eric
Hamilton at eric.hamilton@ufl.edu.
37

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