ECE SEMINAR JIASI CHEN
Abstract As mixed reality systems become popular, new threats to their security and privacy arise, and it is important to understand these emerging threat models and their possible defenses. In […]
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Teer 203
Abstract
As mixed reality systems become popular, new threats to their security and privacy arise, and it is important to understand these emerging threat models and their possible defenses. In this talk, I will discuss recent and ongoing work on mixed reality security and streaming, focusing on three aspects. First, I will discuss system-level attacks arising from side channels such as sensors and hardware performance counters. Such side channels can be exploited to infer user behavior and interactions with mixed reality devices. Second, I will discuss application-level attacks arising in multi-user scenarios, where multiple users collaborate in a shared mixed reality experience. A subset of malicious users can exploit commercial mixed reality platforms to cause undesirable effects to other users. Finally, I will conclude with a discussion of how users can efficiently share 3D models with other, particularly in world-scale scenarios or where 3D Gaussian splat models are involved.
Bio
Jiasi Chen is an Associate Professor of Electrical Engineering and Computer Science at the University of Michigan, Ann Arbor. She was previously at the University of California, Riverside. She received her Ph.D. from Princeton University and her B.S. from Columbia University. Her research interests include multimedia systems, mobile computing, and augmented and virtual reality and its security. Her projects typically involve some combination of mathematical optimization combined with systems experimentation. She is a recipient of an NSF CAREER award and several industry awards including a Meta Faculty Research award on trustworthy AR/VR and an Adobe Research Data Science award.