Security and Privacy for Extended Reality Systems: Attacks and threat models
-- Augmented Reality, virtual worlds, immersive computing, threat model, cybersecurity...--
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Synopsis:
AR/VR devices promise a new era of immersive computing, where our everyday experience is augmented with helpful information (Augmented Reality), or where we are immersed in fully virtual worlds (Virtual Reality). These systems fuse the physical world and the virtual world through computing resources to provide these immersive experiences rendered on the user's headset. As a result, it allows new opportunities for attackers to compromise the security and privacy of users that are not well understood. Towards understanding the security and privacy challenges in these systems, this talk presents a number of recent attacks we developed on AR/VR systems. One threat model exploits the shared computing resources used by multiple applications on a headset to extract information through side channels; we show attacks that spy on user activity or compromise privacy. Another threat model exploits the shared state among multiple users in a multi-user application, allowing malicious users to inject compromised information or to recover information they are not allowed to access. Other threat models include those that interfere with applications and cause the virtual model to become out of sync with the physical world, causing user motion sickness or bypassing safety guardrails. I will conclude with a discussion of potential defenses and ways to build more secure AR/VR experiences.
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- Date: 11 Jun 2025
- Time: 01:00 AM UTC to 02:30 AM UTC
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- Co-sponsored by Vishnu S. Pendyala, SJSU
- Starts 16 May 2025 07:00 AM UTC
- Ends 10 June 2025 07:00 AM UTC
- No Admission Charge
Speakers
Dr. Vishnu S. Pendyala of San Jose State University
Biography:
Vishnu S. Pendyala, PhD, is a faculty member in Applied Data Science and an Academic Senator with San Jose State University, current chair of the Santa Clara Valley Chapters of IEEE Computer and Computational Intelligence Societies, Area 4 Coordinator for Region 6, and a Distinguished Contributor of the IEEE Computer Society. As a past ACM Distinguished Speaker, researcher, and industry expert, he gave nearly 100 talks and tutorial sessions in various forums such as faculty development programs, the 12th IEEE GHTC, IEEE ANTS, 12th IACC, 10th ICMC, IUCEE, 12th ACM IKDD CODS and 30th COMAD to audiences at venues such as Stanford University, Google, University of Bolton, Computer History Museum, Universidad de Ingeniería y Tecnología, Lima, Peru, IIIT Hyderabad, KREA, IIT Jodhpur, University of Hyderabad, IIT Indore, IIIT Bhubaneswar. Some of these talks are available on YouTube and IEEE.tv. He is a senior member of the IEEE and ACM. He has over two decades of experience in the software industry in the Silicon Valley, USA. His book, “Veracity of Big Data,” is available in several libraries, including those of MIT, Stanford, CMU, the US Congress and internationally. Two other books on machine learning and software development that he edited are also well-received and found place in the US Library of Congress and other reputed libraries. Dr. Pendyala taught a one-week course sponsored by the Ministry of Human Resource Development (MHRD), Government of India, under the GIAN program in 2017 to Computer Science faculty from all over the country and delivered the keynote in a similar program sponsored by AICTE, Government of India in 2022. Dr. Pendyala served on a US government's National Science Foundation (NSF) proposal review panel in 2023. He received the Ramanujan memorial gold medal and a shield for his college at the State Math Olympiad. He also played an active role in the Computer Society of India and was the Program Secretary for its annual national convention.
Address:One Washington Sq, San Jose State University, San Jose, New Jersey, United States, 95192-0250
Prof. Nael Abu-Ghazaleh
Security and Privacy for Extended Reality Systems: Attacks and threat models
Biography:
Nael Abu-Ghazaleh is a Professor in the Computer Science and Engineering as well as the Electrical and Computer Engineering Departments at the University of California, Riverside. His research is in architecture and system security, high-performance computing, and systems and security for Machine Learning. He has published over 250 papers in these areas, several of which have been recognized with best paper awards or nominations. His offensive security research has resulted in the discovery of several new attacks on CPUs and GPUs that have been disclosed to companies including Intel, AMD, ARM, Apple, Microsoft, Google, and Nvidia, and resulted in patches and modifications to products, and coverage from technical news outlets. He is a member of the Micro Hall of Fame, an ACM distinguished member, and an IEEE distinguished speaker.
