Mizanur Rahman
University of Alabama, AL·Engineering·Early-career
Self-driving cars, drones and other autonomous systems need to know exactly where they are and what time it is. Most get this from satellite navigation signals, which can be disrupted by accidental interference, reflections off buildings, or deliberate jamming and spoofing (faking signals to mislead a receiver).
- Fields
Engineering
Computer Science
- Topics
autonomous systems
autonomous vehicles
cyber-resilient navigation
- Grants
- 1 known grant, through May 2029
What they work on
- Assess the cyber threats facing integrated positioning and navigation systems that combine satellite navigation (GNSS), inertial and perception sensors, using a threat-modeling approach.
- Model self-learning cyber attacks, such as jamming and spoofing, on autonomous navigation to support navigation solutions that are secure by design.
- Develop a suite of algorithms that detect cyber attacks under uncertainty at three levels: the raw signal, the sensor fusion, and the final navigation solution.
- Build a secure navigation solution for contested environments through deep fusion of GNSS, inertial and perception sensor data.
- Create a game-based learning platform that introduces K-12 students to cybersecurity and STEM careers, and engage engineering students in cross-disciplinary research.
More about the research
When the position is wrong, a vehicle on a rescue, firefighting or transport mission can fail or crash.
Why it matters
Reliable positioning is what lets autonomous vehicles, drones and robots carry out transportation, search-and-rescue, surveillance, mapping and firefighting missions safely. Methods to detect jamming and spoofing, and to keep navigating through them, could make these systems harder to attack. That would help protect the safety and mobility benefits that autonomous ground vehicles are expected to bring. The project also aims to help train a larger cybersecurity workforce.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Qi Chen
University of California-Irvine, CA·Computer Science·Early-career
Develop system-to-AI and AI-to-system mapping methods that generate physical-layer attacks on autonomous vehicle AI while keeping them physically realizable and semantically equivalent across diverse real system designs.
Zejian Zhou
University of Wyoming, WY·Engineering
Model complex autonomous systems as multi-agent systems in which a disrupted component becomes an irrational agent, either passive (an accidental fault) or active (adversarial, such as a cyber-attack).
Sayan Mitra
University of Illinois Urbana-Champaign, IL·Computer Science
Develop refinement algorithms that synthesize perception contracts, machine-checkable bounds on how wrong an AI perception module can be, together with the operating design domains in which they hold, for pipelines that fuse camera and inertial sensor data.
The school
University of Alabama: 22 labs on PI Pages, $221M a year on research, 235 research doctorates a year.
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