CAREER: mmDrone: Protecting Drone-Integrated IoT Systems with Advanced mmWave Sensing

Drones are increasingly integrated with Internet-of-Things (IoT) systems to support mission-critical applications such as infrastructure monitoring, emergency response, and smart transportation. However, this integration also introduces significant security and safety risks. Malicious or hijacked drones can be exploited for conducting surveillance, bringing disruptions to wireless communications, or carrying out physical attacks on critical infrastructure, all posing a major threat to public safety, economic stability, and national security. The project's novelties are the use of millimeter-wave (mmWave) sensing as a unified, scalable, and cost-effective foundation to detect, authenticate, and assess drones, as well as to secure their communications within IoT eco-systems. The project's broader significance and importance are its potential to strengthen the resilience of critical infrastructure, contribute to national defense, and advance trustworthy deployment of emerging drone technologies. In addition, the project supports education and workforce development by engaging a diverse group of students, integrating research outcomes into curriculum development, and releasing open resources that benefit the broader research community and society. The investigator is designing, prototyping, and evaluating mmWave-powered security mechanisms for drone-integrated IoT systems using commodity and deployable radar platforms. The research is organized into four integrated thrusts. Thrust 1 develops mmDrone-Surv, a cutting-edge mmWave framework for extended-range drone detection and tracking. Thrust 2 designs mmDrone-Auth, an advanced drone authentication system utilizing hardware fingerprinting. Thrust 3 seeks to build mmDrone-Scale, a novel solution for accurate remote measurement of drone payloads. Thrust 4 proposes mmDrone-Key, an innovative scheme that uses mmWave sensing dynamics to establish secure keys between legitimate drones and IoT devices. The project also includes a comprehensive prototyping, validation, and evaluation plan to evaluate and ensure the effectiveness of the proposed solutions. The outcomes will advance the state of the art in wireless sensing-based security and provide foundational tools and insights for securing next-generation drone-integrated IoT systems. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. NSF Award ID: 2542688 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT,01003031DB NSF RESEARCH & RELATED ACTIVIT,01002930DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Dianqi Han | Institution: University of Texas at Arlington, ARLINGTON, TX | Award Amount: $341,039 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2542688 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2542688.html