NSF-Funded University of Oklahoma Research Targets New Wireless Privacy Threats

A researcher at the University of Oklahoma has received a $600,000 National Science Foundation (NSF) award to develop defenses against emerging wireless inference attacks, a class of eavesdropping techniques that exploit Wi-Fi signals to capture sensitive user information without the need for malware, cameras, or direct access to devices.

Dr. Song Fang, a professor in the School of Computer Science, will lead the project, “Revolutionizing Wireless Inference Attacks and Defenses via Channel Analysis and Manipulation.” The research will pioneer training-free detection methods and new countermeasures to protect users from adversaries capable of inferring keystrokes, conversations, and movements solely through variations in surrounding wireless signals.

“Wireless signals behave like invisible strings stretched throughout the environment,” Fang explained. “When someone types or speaks, those actions ‘strum’ the strings, creating subtle vibrations. An eavesdropper can ‘listen’ to those vibrations to infer what’s happening. Our work aims to make that impossible.”

Traditional defenses rely on prior training data to interpret signal changes—a limitation that reduces their real-world applicability. Fang’s training-free approach eliminates this requirement, enabling adaptive protection in new or dynamic environments.

The project also introduces wireless channel manipulation, a proactive defense that deliberately injects misleading fluctuations into wireless environments. By scrambling the signal “music” attackers depend on, this technique can cloak sensitive user activities without affecting normal device operations.

“This research represents a major shift in how we understand and defend against wireless-based privacy threats,” Fang said. “It lays the foundation for privacy-preserving technologies that can protect everyday users in an increasingly connected world.”

The NSF-funded project runs from October 2025 through September 2028 and supports the broader goal of advancing cybersecurity resilience at the intersection of wireless systems, privacy, and human activity recognition.

Read more: Newly funded research to develop defenses against wireless inference threats