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Autori principali: Baldoni, Sara, Benhamadi, Salim, Chiariotti, Federico, Zorzi, Michele, Battisti, Federica
Natura: Preprint
Pubblicazione: 2025
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Accesso online:https://arxiv.org/abs/2501.16326
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author Baldoni, Sara
Benhamadi, Salim
Chiariotti, Federico
Zorzi, Michele
Battisti, Federica
author_facet Baldoni, Sara
Benhamadi, Salim
Chiariotti, Federico
Zorzi, Michele
Battisti, Federica
contents With the unprecedented diffusion of virtual reality, the number of application scenarios is continuously growing. As commercial and gaming applications become pervasive, the need for the secure and convenient identification of users, often overlooked by the research in immersive media, is becoming more and more pressing. Networked scenarios such as Cloud gaming or cooperative virtual training and teleoperation require both a user-friendly and streamlined experience and user privacy and security. In this work, we investigate the possibility of identifying users from their movement patterns and data traffic traces while playing four commercial games, using a publicly available dataset. If, on the one hand, this paves the way for easy identification and automatic customization of the virtual reality content, it also represents a serious threat to users' privacy due to network analysis-based fingerprinting. Based on this, we analyze the threats and opportunities for virtual reality users' security and privacy.
format Preprint
id arxiv_https___arxiv_org_abs_2501_16326
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Movement- and Traffic-based User Identification in Commercial Virtual Reality Applications: Threats and Opportunities
Baldoni, Sara
Benhamadi, Salim
Chiariotti, Federico
Zorzi, Michele
Battisti, Federica
Multimedia
With the unprecedented diffusion of virtual reality, the number of application scenarios is continuously growing. As commercial and gaming applications become pervasive, the need for the secure and convenient identification of users, often overlooked by the research in immersive media, is becoming more and more pressing. Networked scenarios such as Cloud gaming or cooperative virtual training and teleoperation require both a user-friendly and streamlined experience and user privacy and security. In this work, we investigate the possibility of identifying users from their movement patterns and data traffic traces while playing four commercial games, using a publicly available dataset. If, on the one hand, this paves the way for easy identification and automatic customization of the virtual reality content, it also represents a serious threat to users' privacy due to network analysis-based fingerprinting. Based on this, we analyze the threats and opportunities for virtual reality users' security and privacy.
title Movement- and Traffic-based User Identification in Commercial Virtual Reality Applications: Threats and Opportunities
topic Multimedia
url https://arxiv.org/abs/2501.16326