CRII: SaTC: Securing Smart Devices with AI-Powered mmWave Radar in New-Generation Wireless Networks

Principal Investigator: Tao Li

New-generation networking systems, such as 5G/6G cellular and future Wi-Fi networks, are envisioned to connect billions of heterogeneous smart devices and enable high-speed and low-latency communications using millimeter wave (mmWave) technologies. The high frequency and short wavelength bring extraordinary sensing resolution which has enabled promising applications such as autonomous driving, non-contact health monitoring, material detection, vibration sensing, etc. However, the research on security applications of mmWave sensing is still very much in its infancy. This project provides a comprehensive educational platform for curriculum development, graduate student training, undergraduate research engagement, and broadening the participation of women and underrepresented students in computing.

This project aims to develop, implement, and evaluate novel mmWave sensing techniques to secure smart devices such as smartphones, tablets, and laptops and the data therein in new-generation wireless networks. The project includes the following objectives:

• Developing mmLock, a user-leaving detection and identification system by analyzing the mmWave signal reflections from the user body to lock the lost/stolen device automatically and immediately against data theft when the user is unknowingly away from his/her device.
• Investigating mmUnlock, a liveness detection technique by checking consistency between the user’s head movements extracted from the vision and mmWave data for more secure face authentication in smart devices.
• Implementing and evaluate the performance, security, and usability of above systems with commercial off-the-shelf (COTS) mmWave radars.