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CIS Seminar presents: ” Cyber-Physical Security Through the Lens of AI-Enabled Systems

March 25 at 3:30 PM - 4:30 PM

Cyber-physical systems (CPS), powered by emerging artificial intelligence (AI) technologies, have become integral to various critical domains such as the Internet of Things (IoTs), medical devices, and autonomous vehicles. A unique aspect of these systems lies in their interactions with the physical world, by perceiving environments through heterogeneous modalities (perception), processing digital data with intelligence algorithms (computing), and autonomously actuating controls that affect physical processes (actuation). While this intricate fusion of cyber and physical components has unlocked unprecedented capabilities, it has also introduced new security challenges. However, traditional security measures often fall short in addressing these multifaceted threats. Under this paradigm shift, I systematically explore and mitigate the threats inherent in AI-enabled cyber-physical systems. The research objectives are threefold: (1) investigating how the interplay of cyber and physical components opens up novel attack and defense vectors, (2) developing robust defense strategies grounded by physical laws and reasoning, and (3) benchmarking and theoretically analyzing security trade-offs from algorithmic, system-level, and human-centric perspectives. By bridging the gap between cyber and physical domains, my research enhances the resilience and trustworthiness of modern CPS while retaining system efficiency and usability.

Zhiyuan Yu

Computer Science at Washington University in St. Louis

Zhiyuan Yu is a final-year Ph.D. candidate in Computer Science at Washington University in St. Louis, specializing in the security and privacy of AI-enabled systems. His research focuses on bridging cyber and physical components in embodied AI to develop resilient defenses, across diverse domains like autonomous systems, medical imaging, and generative AI (GenAI) applications. His work has received the Distinguished Paper Award at USENIX Security 2024 and the Distinguished Artifact Award at USENIX Security 2023. Zhiyuan’s work has also won the 2024 Federal Trade Commission Voice Cloning Challenge. He has been named a Machine Learning and Systems Rising Star in 2024.

Details

Date:
March 25
Time:
3:30 PM - 4:30 PM
Event Tags:
Website:
https://www.cis.upenn.edu/events/

Organizer

Computer and Information Science
Phone
215-898-8560
Email
cherylh@cis.upenn.edu
View Organizer Website

Venue

Amy Gutmann Hall, Room 414
3333 Chestnut Street
Philadelphia, 19104 United States
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