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Traffic-sign recognition is one of the key tools required for autonomous vehicles. Thanks to road-sign standardization, this technology is well-suited to machine-learning and deep-learning processes that can identify images.

It runs into difficulties, however, when signs are intentionally defaced to trick algorithms into reading them differently. With a few strategically placed pieces of tape, a person can trick an algorithm into viewing a stop sign as if it were a 45 mile-per-hour speed limit sign, according to researchers. No serious incidents of this type have been identified outside of laboratory or test environments.

Bosch is using artificial intelligence to reduce the risk that hackers will be able to trick cars’ electronic systems into misinterpreting road signs. Such information could prove hazardous even in human-operated vehicles, where drivers might rely on information presented via their onboard systems.

The company, which develops vehicle components such as sensors and cameras for tasks including traffic-sign recognition is researching countermeasures.

The company has introduced an AI process that uses computer vision, where algorithms seek to emulate human visual-processing systems. The idea is to analyze an object from two different perspectives and compare them against each other.

The defense system  is based on the fact that this type of attack is designed to foil a particular element of the autonomous vehicle, in this case the neural network that is trained to identify images such as stop signs. The remedy involves the use of a separate system, computer vision, that wasn’t targeted by the malicious actors. The defense is only triggered by a deliberate attack, according to