Collaboration in Mixed-Reality

Collaborative Mixed-Reality (CMR) applications are gaining interest in a wide range of areas including games, social interaction, design and health-care. To date, the vast majority of published work has focused on display technology advancements, software, collaboration architectures and applications. However, the potential security concerns that affect collaborative platforms have received limited research attention. In this position paper, we investigate the challenges posed by cyber-security threats to CMR systems. We focus on how typical network architectures facilitating CMR and how their vulnerabilities can be exploited by attackers, and discuss the degree of potential social, monetary impacts, psychological and other harms that may result from such exploits. The main purpose of this paper is to provoke a discussion on CMR security concerns. We highlight insights from a cyber-security threat modelling perspective and also propose potential directions for research and development toward better mitigation strategies. We present a simple, systematic approach to understanding a CMR attack surface through an abstraction-based reasoning framework to identify potential attack vectors. Using this framework, security analysts, engineers, designers and users alike (stakeholders) can identify potential Indicators of Exposures (IoE) and Indicators of Compromise (IoC). Our framework allows stakeholders to reduce their CMR attack surface as well understand how Intrusion Detection System (IDS) approaches can be adopted for CMR systems. To demonstrate the validity to our framework, we illustrate several CMR attack surfaces through a set of use-cases. Finally, we also present a discussion on future directions this line of research should take.

Augmented and Virtual Reality provide unique capabilities for Mixed Reality collaboration. This paper explores how different combinations of virtual awareness cues can provide users with valuable information about their collaborator's attention and actions. In a user study (n = 32, 16 pairs), we compared different combinations of three cues: Field-of-View (FoV) frustum, Eye-gaze ray, and Head-gaze ray against a baseline condition showing only virtual representations of each collaborator's head and hands. Through a collaborative object finding and placing task, the results showed that awareness cues significantly improved user performance, usability, and subjective preferences, with the combination of the FoV frustum and the Head-gaze ray being best. This work establishes the feasibility of room-scale MR collaboration and the utility of providing virtual awareness cues.