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posted by martyb on Wednesday February 19 2020, @09:45PM   Printer-friendly
from the Do-these-trick-other-vendor's-systems? dept.

Hackers can trick a Tesla into accelerating by 50 miles per hour:

This demonstration from the cybersecurity firm McAfee is the latest indication that adversarial machine learning can potentially wreck autonomous driving systems, presenting a security challenge to those hoping to commercialize the technology.

Mobileye EyeQ3 camera systems read speed limit signs and feed that information into autonomous driving features like Tesla's automatic cruise control, said Steve Povolny and Shivangee Trivedi from McAfee's Advanced Threat Research team.

The researchers stuck a tiny and nearly imperceptible sticker on a speed limit sign. The camera read the sign as 85 instead of 35, and in testing, both the 2016 Tesla Model X and that year's Model S sped up 50 miles per hour.

This is the latest in an increasing mountain of research showing how machine-learning systems can be attacked and fooled in life-threatening situations.

[...] Tesla has since moved to proprietary cameras on newer models, and Mobileye EyeQ3 has released several new versions of its cameras that in preliminary testing were not susceptible to this exact attack.

There are still a sizable number of Tesla cars operating with the vulnerable hardware, Povolny said. He pointed out that Teslas with the first version of hardware cannot be upgraded to newer hardware.

"What we're trying to do is we're really trying to raise awareness for both consumers and vendors of the types of flaws that are possible," Povolny said "We are not trying to spread fear and say that if you drive this car, it will accelerate into through a barrier, or to sensationalize it."

So, it seems this is not so much that a particular adversarial attack was successful (and fixed), but that it was but one instance of a potentially huge set. Obligatory xkcd.


Original Submission

Previously:
Protecting Smart Machines From Smart Attacks
A New Clothing Line Confuses Automated License Plate Readers
A Simple Sticker Tricked Neural Networks Into Classifying Anything as a Toaster
3D Printed Turtles Fool Google Image Classification Algorithm
Slight Street Sign Modifications Can Completely Fool Machine Learning Algorithms

 
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  • (Score: 1, Interesting) by Anonymous Coward on Thursday February 20 2020, @01:51AM

    by Anonymous Coward on Thursday February 20 2020, @01:51AM (#960126)

    How about a missing sign? Years ago a friend was fooled by a stop sign where a vandal had turned the pole 90 deg (in top view) -- from his viewpoint the sign was edge-on so he didn't see it at all. He t-boned (at low speed) someone rolling properly along the cross street, thinking that they had the 2-way stop.

    My friend got the "failure to stop" ticket anyway, the cop didn't care if the sign was visible or not.

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