Tesla Tech System's Vulnerability to Hackers Revealed!

Aug 09, 2016 10:50 AM EDT | Jomar Teves

The researchers who are in charge of hacking Tesla have described on how they made the sensors of Tesla enable a car to hit an object that is in its path at the Def Con hacker conference.

While showing the video of a demonstration on Tesla S model attack, Chen Yan, one of the researchers have said that "Normally the car will not move. However, when we jam the sensor it moves."

"It hit me", he added. This made the audience laugh with delight.

But it is vital for most people to know that the demonstration that was shown did not imitate the conditions in the real-world today. These researchers have been focusing on the cars that were sometimes motionless but have very much expensive equipment and components.

They have quoted that the "sky wasn't falling".

However, the result of the experiment has created theories about the possibility of creating a certain device that could mess with the sensors of the cars near him.

Members of the research group are Chen Yan who is a Ph.D. student at Zhejiang University, Jianhao Liu who is a senior security consultant at Qihoo 360, and WenyuanXu who is a professor at Zhejiang University and also the University of South Carolina, these people and institution have offered different findings for the research.

The group has presented discovered new ways for "quieting" sensors which are used to conceal hurdles in the path of the car, "spoofing" the sensors to make a certain object looks like it is nearer than it actually is and the last is "jamming". As Yan described, it reduces the sensor useless as it's "overwhelmed by noise."

"This is definitely interesting and good work," the principal scientist at Security Innovations, Jonathan Petit who have also shown his own research about deceiving autonomous vehicles said to Wired about the Tesla hackers. "They need to do a bit more work to see if it would actually collide with an object. You can't yet say the Autopilot doesn't work.", he added.

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