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Texas A&M researchers develop system that prevents autonomous vehicle hacking

Texas A&M University researchers have developed an intelligent transportation system prototype designed to avoid collisions and prevent the hacking of autonomous vehicles.

Autonomous vehicles rely on sensors to provide information that controls them, and are also equipped with internet access for safety or infotainment applications, making them vulnerable to cyberattacks. This will only multiply as society transitions to self-driving vehicles in which hackers could gain control of the sensors, causing confusion and collisions. Securing autonomous vehicles is not the same as securing a communication network that connects desktop computers and smartphones to large geographical areas, due to the roles that the sensors and actuators play in the physical layer of the network.

Working in the Texas A&M’s Cyberphysical Systems Laboratory, Dr P R Kumar (below right), a professor in the Department of Electrical and Computer Engineering, along with graduate students Bharadwaj Satchidanandan and Woo-Hyun Ko, has applied the theory of ‘dynamic watermarking’ of sensors in autonomous vehicles to prevent malicious attacks.

In their research demonstrations, 10 cameras recorded the movement of the self-driving prototype vehicles. The vision sensors in the system received the images and accurately calculated the exact location and orientation of the vehicles. Then they transmitted this information to a server, which in turn controlled the vehicles. If the sensors are corrupted or hijacked by malicious agents through the internet, they can provide false information on vehicle location, resulting in collisions.

To fix this, Kumar and his team added a random private signal called a ‘watermark’ to the actuators. The presence of this watermark and its statistical properties were known to every node in the system, but its actual random values were not revealed.

When the measurements reported by the sensors did not have the right properties of this watermark, the actuators assumed that the sensors or their measurements had been tampered with somewhere along the line. With this new information, the researchers could predict a collision and showed that their technology could work in the lab, as the actuators in the vehicles halted themselves when the sensors were tampered with.

“This is an instance of the broader concern of security of cyberphysical systems. The increasing integration of critical physical infrastructures, such as the smart grid or automated transportation, with the cyber system of the internet, has led to such vulnerabilities,” said Kumar. “If these technologies are to be adopted by society, they will need to be protected against malicious attacks on sensors.”

May 30, 2017

Written by Adam Frost

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