UAV Resilience Against Stealthy Attacks
Unmanned aerial vehicles (UAVs) depend on untrusted software components to automate dangerous or critical missions, making them a desirable target for attacks. Some work has been done to prevent an attacker who has either compromised a ground control station or parts of a UAV's software from sabotaging the vehicle, but not both. We present an architecture running a UAV software stack with runtime monitoring and seL4-based software isolation that prevents attackers from both exploiting software bugs and stealthy attacks. Our architecture retrofits legacy UAVs and secures the popular MAVLink protocol, making wide adoption possible.
Authors
- Gary T. Leavens (ORCID: https://orcid.org/0000-0003-3271-3921)
- Arthur Azevedo de Amorim (ORCID: https://orcid.org/0000-0001-9916-6614)
- Trevor Kann (ORCID: https://orcid.org/0009-0004-5197-2448)
- Max Taylor
- William L. Harrison (ORCID: https://orcid.org/0000-0002-3760-3556)
- Lance Joneckis
Institutions
- University of Central Florida (US)
- Idaho National Laboratory (US)
- Carnegie Mellon University (US)
Publication Details
- Published
- 2025-05-14
- DOI
- https://doi.org/10.1109/icuas65942.2025.11007915
- Citations
- 3
- Primary Topic
- Adversarial Robustness in Machine Learning
- Type
- article
- Field-Weighted Citation Impact
- 7.44