2020 BRN Discussion, page-28591

http://venturebeat.com/2021/02/22/eu-report-warns-that-ai-makes-autonomous-vehicles-highly-vulnerable-to-attack/
http://www.enisa.europa.eu/news/enisa-news/cybersecurity-challenges-in-the-uptake-of-artificial-intelligence-in-autonomous-driving#:~:text=A%20new%20report%20by%20ENISA,State%2C%20so%20do%20its%20vulnerabilities.
http://www.enisa.europa.eu/publications/enisa-jrc-cybersecurity-challenges-in-the-uptake-of-artificial-intelligence-in-autonomous-driving
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Autonomous vehicles are "highly vulnerable" to attacks, including those led by adversarial machine learning systems, according to a new European Union Agency for Cybersecurity report. The EU agency specifically mentions how an attacker could manipulate image recognition in AVs to make them mislabel pedestrians, potentially striking them in crosswalks, for example.

More:

• These types of adversarial attacks would also fool motion planning and decision-making algorithms and other systems. The study also mentions "back-end malicious activity" and sensor attacks using "beams of light."
• A widely cited study from 2017, for instance, showed that researchers could trick an AV to misidentify a stop sign as a speed limit sign by placing a sticker over it. Tencent researchers conducted a similar study in 2019, using stickers to make Tesla’s Autopilot system enter the wrong lane.
• As a result, the EU agency says car manufacturers should move toward creating machine learning systems to counteract attacks and mitigate security risks. It also urges businesses and policymakers to foster a "security culture" in the auto supply chain.
• It concludes: "AI systems should be designed, implemented, and deployed by teams where the automotive domain expert, the ML expert, and the cybersecurity expert collaborate.”

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