Tesla’s Autopilot Tricked By These Chinese Hackers With Only 3 Stickers On The Road

Jyotis - Apr 04, 2019


Tesla’s Autopilot Tricked By These Chinese Hackers With Only 3 Stickers On The Road

When replying to what Keen has found out, Tesla claimed that the issues mentioned above didn’t mean the real situations, as well as no Tesla’s customers ever faced any of these reported issues.

Citing from a statement of a cybersecurity research company, it stuck 3 small stickers on the road and succeeded in making Tesla’s Autopilot turn its pre-set course.

Tesla Autopilot

On March 30, Keen Labs, which was known for receiving the two rewards from Tesla’s bug bounty program, revealed that the company detected two ways to make the lane recognition feature of Autopilot give the wrong judge: They just need to change the physical surface of the road.

In the beginning, these Chinese hackers blurred the left lane line. The result came as a surprise: Tesla’s computer couldn't recognize the blurred line although such the situation was allegedly hard to happen in reality.

Dreamstime Xl 117686520

The reason why Tesla’s Autopilot could manage to handle the above situation without any obstacles was that the model is well-trained to realize some “abnormal lanes”. As such, Tesla cars can determine the exact lane directions even when they lack good lighting or move in severe weather conditions.

In the second experiment, Keen Labs arranged three small squares in the pavement to simulate merge strips and not much surprise, the car switched its initial course in the left lane. In other words, the self-driving car wrongly identified that a traffic lane was ahead.

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When replying to what Keen has found out, Tesla claimed that the issues mentioned above didn’t mean the real situations, as well as no Tesla’s customers ever faced any of these reported issues.

In an interview with Business Insider, a representative from Tesla said although Keen’s report wasn’t suitable for its bug-bounty program, the company still highly appreciated their contributions.

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