Privacy Equilibrium: Balancing Privacy Needs in Dynamic Multi-User Augmented Reality Scenarios
summary
Proposes Privacy Equilibrium, a constrained-optimization framework that computes per-user AR sensing permissions to maximize UX while minimizing privacy risk and implements a simulation and analysis toolkit that runs scenarios (hospital, office) and a heuristic optimization that starts with full permissions and iteratively restricts sensors to maximize privacy gain for minimal UX loss until thresholds. Dashboard shows tradeoffs on a Pareto frontier visualization. Simulation plus walkthroughs with security/privacy researchers find the optimization approach reduces UX/privacy tradeoffs more than ownership- or world-driven rules.
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chapters (7)
- 0:00Introduction
- 0:49AR privacy challenges
- 3:37Negotiation strategies
- 5:04Optimization approach
- 6:29Toolkit visualization
- 8:36Future research questions
- 9:48Q&A session
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