Location: Jabara Hall, Room 260

Talk By: Mengfei (Angela) Ren, a PhD candidate from the University of Texas

Abstract
In recent years, we have witnessed the proliferation of the Internet of Things (IoT) devices widely adopted by various areas, such as home automation, healthcare, industry and smart vehicles. Globally, Zigbee is one of the most popular IoT wireless standards used by millions of devices and customers like Amazon, Samsung, IKEA, Xiaomi, and so on. This rapid global market growth of Zigbee also incentivizes cybercriminal attacks. Therefore, it is necessary and practical to detect security issues in the Zigbee protocol. In this talk, I will present the current state-of-the-art security analysis solutions for the Zigbee protocol. Then I will introduce my research work on fuzz testing of Zigbee protocol implementations. This includes a device-agnostic fuzzing framework of Zigbee protocol implementation and an intelligent Zigbee protocol fuzzing solution via constraint-field dependency inference. Finally, I will present some ideas for my future work on multiple field mutation for fuzzing and silent memory detection in the Zigbee protocol using advanced software testing techniques.

Bio
Mengfei (Angela) Ren is currently a Ph.D. ABD in the Department of Computer Science and Engineering at the University of Texas at Arlington. She is advised by Dr. Jeff Lei at UT Arlington and Dr. Jiang Ming at Tulane University. Her research interests lie at the intersection of cybersecurity and software engineering. Her Ph.D. thesis focuses on combining practical software testing techniques to detect security vulnerabilities in IoT wireless protocols. Her work has detected several critical vulnerabilities in a mainstream Zigbee protocol stack. She was the recipient of UTA CSE Cyneta Networks Outstanding Graduate GTA.