Nirnimesh Ghose
University of Nebraska-Lincoln, NE·Computer Science
Farms, drones and everyday gadgets increasingly rely on wireless devices. Each device must prove it is genuine before it can be trusted.
- Fields
Computer Science
Engineering
- Topics
cybersecurity
wireless security
Internet of Things
- Grants
- 2 known grants, through Jun 2028
What they work on
- Develop scalable trust-establishment methods for farm wireless nodes that use chirp spread spectrum (CSS) modulation, a long-range, low-power radio technique used in agricultural IoT.
- Create soil-adaptive trust-establishment methods for underground IoT sensors, and use soil-assisted techniques to establish trust among above-ground farm devices at scale.
- Make radio fingerprinting, which identifies devices from hardware imperfections in their signals, robust to changing wireless channels and receiver hardware flaws by combining deep learning with signal processing.
- Improve the resilience of radio fingerprinting against white-box attackers who know how the system works, using deep learning and signal processing methods.
More about the research
Ordinary passwords and encryption are hard to scale across thousands of cheap sensors, and they can be bypassed. This research builds security into the radio signals themselves. It covers two areas: establishing trust among devices on connected farms, and identifying devices by the subtle physical quirks in their signals.
Why it matters
Securing farm sensor networks could protect agricultural operations that depend on connected devices from attacks that harm productivity and profitability. More reliable radio fingerprinting could help authenticate IoT devices and drones from their signals alone. This gives operators of critical wireless systems another layer of protection that is difficult to fake.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Somali Chaterji
Purdue University, IN·Computer Science·Early-career
Develop on-device machine learning analytics for farm sensors that adapt to each device's computing power, changing network conditions and competition from co-located applications.
Guevara Noubir
Northeastern University, MA·Engineering
Analyze threats to spectrum sharing from adversaries who use software-defined radios and machine learning to evade detection, including colluding transmitters.
Jiawei Yuan
University of Massachusetts-Dartmouth, MA·Computer Science
Design and build an integrated, extensible research platform for securely combining AI with unmanned aerial vehicles (drones). The platform is meant to support studies that find weaknesses and test defenses.
The school
University of Nebraska-Lincoln: 17 labs on PI Pages, $657M a year on research, 261 research doctorates a year.
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