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FICS researchers discovered three vulnerabilities in thermal cameras that could cause drones or autonomous vehicles to miss real obstacles or detect ones that aren’t there

Thermal camera image of a group of people, with color-coded surface temperatures and numeric temperature readings displayed above each person’s head.

As thermal cameras become commonplace on autonomous drones and vehicles, FICS researcher is working to make sure they can’t be maliciously tricked into “seeing” things that aren’t there. 

Work by FICS researcher Dr. Sara Rampazzi, Ph.D., and her research group reveals that thermal-based perception systems may be far less reliable and secure than previously assumed, especially for safety‑critical tasks like obstacle avoidance in autonomous robots and aerial drones.  

Thermal cameras “see” in conditions where normal cameras fail (night, fog, smoke, rain) by detecting heat differences rather than visible light.  These sensors help machines identify people, animals and obstacles when visibility is poor.

Dr. Sara Rampazzi is an assistant professor in the Department of Computer & Information Science & Engineering, known as CISE. The work was presented at the 2026 Network and Distributed System Security Symposium by her Ph.D. student Sri Hrushikesh Varma Bhupathiraju.

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