Eliciting Security & Privacy-Informed Sharing Techniques for Multi-User Augmented Reality

要旨

The HCI community has explored new interaction designs for collaborative AR interfaces in terms of usability and feasibility; however, security & privacy (S&P) are often not considered in the design process and left to S&P professionals. To produce interaction proposals with S&P in mind, we extend the user-driven elicitation method with a scenario-based approach that incorporates a threat model involving access control in multi-user AR. We conducted an elicitation study in two conditions, pairing AR/AR experts in one condition and AR/S&P experts in the other, to investigate the impact of each pairing. We contribute a set of expert-elicited interactions for sharing AR content enhanced with access control provisions, analyze the benefits and tradeoffs of pairing AR and S&P experts, and present recommendations for designing future multi-user AR interactions that better balance competing design goals of usability, feasibility, and S&P in collaborative AR.

著者
Shwetha Rajaram
University of Michigan, Ann Arbor, Michigan, United States
Chen Chen
University of Michigan, Ann Arbor, Michigan, United States
Franziska Roesner
University of Washington, Seattle, Washington, United States
Michael Nebeling
University of Michigan, Ann Arbor, Michigan, United States
論文URL

https://doi.org/10.1145/3544548.3581089

動画

会議: CHI 2023

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)

セッション: Collaboration in Mixed Realities

Hall D
6 件の発表
2023-04-26 20:10:00
2023-04-26 21:35:00