Privacy concerns from variances in spatial navigability in VR

• URL: http://arxiv.org/abs/2302.02525v1
• Date: Mon, 6 Feb 2023 01:48:59 GMT
• Title: Privacy concerns from variances in spatial navigability in VR
• Authors: Aryabrata Basu, Mohammad Jahed Murad Sunny, Jayasri Sai Nikitha Guthula
• Abstract summary: Current Virtual Reality (VR) input devices make it possible to navigate a virtual environment and record immersive, personalized data regarding the user's movement and specific behavioral habits. In this article, the authors propose to investigate Machine Learning driven learning algorithms that try to learn with human users co-operatively and can be used to countermand existing privacy concerns in VR.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Current Virtual Reality (VR) input devices make it possible to navigate a virtual environment and record immersive, personalized data regarding the user's movement and specific behavioral habits, which brings the question of the user's privacy concern to the forefront. In this article, the authors propose to investigate Machine Learning driven learning algorithms that try to learn with human users co-operatively and can be used to countermand existing privacy concerns in VR but could also be extended to Augmented Reality (AR) platforms.

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