CAREER: Safeguarding Smart Homes: A Foundation for Building User Privacy-Enhancing IoT Systems

People are increasingly deploying Internet of Things (IoT) devices to enable smart home automation. Unfortunately, network traffic data generated by these devices can contain sensitive information that may be exposed through malicious artificial intelligence (AI)-based privacy attacks. Current defense approaches do not adequately consider these emerging “smart” attacks. This project aims to address challenges in understanding and defending against these new AI-based attacks through a data-driven, privacy-friendly IoT management framework that enables people to understand and manage the leakage of in-home information. This project will investigate new techniques for enhancing smart home user privacy. Specifically, this project will (1) develop new AI-based privacy attack models to better understand privacy vulnerabilities; (2) build novel, low-cost, and distributed traffic reshaping approaches to safeguard user privacy; and (3) design new AI-based optimization methods for adapting the reshaping profiles to mirror real-world user behavior, further safeguarding privacy. The outcomes of this project will serve as a foundation for building IoT systems that enable people to have greater control over data collection and sharing. The three technical innovations being pursued will be prototyped and validated through real-world experiments in mock smart homes, as well as within industry collaborators’ laboratories. The specific outcomes of the research will include a family of algorithms, mechanisms, and prototypes that will advance the state-of-the-art in strengthening IoT security and privacy for smart homes, an area that has received relatively little attention, despite the rapidly growing smart home market. This project will also develop IoT cybersecurity summer workshops for Colorado public middle/high school teachers, with a recruitment emphasis on districts with significant populations of Black, Brown, and Indigenous People of Color. Hands-on course modules developed on IoT systems, cybersecurity, and AI will be used to train K-12, undergraduate, and graduate students. This project will also conduct computer science outreach events at local elementary, middle, and high schools to guide the next generation of IoT cybersecurity and AI researchers. 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.