Guangjing Wang
University of South Florida, FL·Computer Science
Phones, cars and other wireless devices increasingly rely on radio signals to know where they are and what is around them. That makes those signals a target.
- Fields
Computer Science
Engineering
- Topics
wireless security
integrated sensing and communication
zero trust
- Grants
- 2 known grants, through Feb 2029
What they work on
- Design a secure authentication framework to verify transmitters and receivers in integrated sensing and communication (ISAC) systems, where a single radio signal both senses and carries data, under zero-trust assumptions.
- Create tools for confidential wireless channels that hide sensitive information even from an eavesdropper who knows the encoding keys.
- Develop privacy-preserving data transmission for ISAC using neural networks and the information bottleneck, then validate it on an open-source software platform and a hardware testbed.
- Determine whether, and under what conditions, attackers can spoof Wi-Fi localization in dense urban areas without disrupting legitimate Wi-Fi, by analyzing the factors behind attack success.
- Probe how Geolocation APIs could leak information about access-point databases and positioning algorithms, and build defenses that let a device detect location spoofing.
More about the research
An attacker can listen in to learn a user's location, or fake signals to feed a device false information. This work asks how such attacks can succeed and how to defend against them. One project covers Wi-Fi-based positioning. The other covers next-generation wireless systems that use one signal both to sense the environment and to carry data.
Why it matters
Many apps and services trust the location and sensing data that wireless signals provide. Defenses against spoofing and eavesdropping could help keep mobile apps from receiving fake positions. They could also protect users' location privacy and make future 5G-and-beyond networks safer for uses such as digital twins. Phone users, app developers and wireless network operators would benefit.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Tianyu Zhang
University of Iowa, IA·Engineering
Develop machine-learning methods that predict wireless channel conditions and interference on the factory floor, so 5G/6G radio resources can adapt in real time.
Nirnimesh Ghose
University of Nebraska-Lincoln, NE·Computer Science
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.
Rose Qingyang Hu
Virginia Polytechnic Institute and State University, VA·Engineering
Reconstruct how wireless signal energy varies with position and direction by combining sparse channel state information measurements with 3D environment layouts rebuilt from images, using radiance-field-inspired models and array signal processing.
The school
University of South Florida: 20 labs on PI Pages, $522M a year on research, 305 research doctorates a year.
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