The Security-Utility Trade-off for Iris Authentication and Eye Animation for Social Virtual Avatars

Abstract

The gaze behavior of virtual avatars is critical to social presence and perceived eye contact during social interactions in Virtual Reality. Virtual Reality headsets are being designed with integrated eye tracking to enable compelling virtual social interactions. This paper shows that the near infra-red cameras used in eye tracking capture eye images that contain iris patterns of the user. Because iris patterns are a gold standard biometric, the current technology places the user's biometric identity at risk. Our first contribution is an optical defocus based hardware solution to remove the iris biometric from the stream of eye tracking images. We characterize the performance of this solution with different internal parameters. Our second contribution is a psychophysical experiment with a same-different task that investigates the sensitivity of users to a virtual avatar's eye movements when this solution is applied. By deriving detection threshold values, our findings provide a range of defocus parameters where the change in eye movements would go unnoticed in a conversational setting. Our third contribution is a perceptual study to determine the impact of defocus parameters on the perceived eye contact, attentiveness, naturalness, and truthfulness of the avatar. Thus, if a user wishes to protect their iris biometric, our approach provides a solution that balances biometric protection while preventing their conversation partner from perceiving a difference in the user's virtual avatar. This work is the first to develop secure eye tracking configurations for VR/AR/XR applications and motivates future work in the area.

SoK: Data Privacy in Virtual Reality

“…Method. From the 68 selected studies, we identified 5 studies that proposed a VR information flow [37], [84], [25], [137], [46] and 21 with an explicit discussion or proposal for VR defense and (predominantly) threat models [28], [116], [26], [37], [84], [64], [55], [27], [29], [65], [56], [123], [42], [58], [113], [30], [134], [112], [95], [67], [6]. Two researchers extracted, discussed, and combined the associated artifacts, resulting in a holistic VR information flow that frames our threat and defense models.…”

“…The collected studies discussing or proposing threat models consider application developers [26], [84], [64], [55], [27], [29], [65], [56], [123], [42], [113], [30], [67], servers [30], [84], [6], content creators [37], [84], device manufacturers [116], [84], other users [112], [134], [95], and hackers 1 [37], [123], [58] as the attackers in VR, or rely on general privacy threat models like Lindunn [31], [60], [28], [64]. Based on these studies, we adopt a more comprehensive and pervasive privacy-centered attacker classification specific to VR that encompasses the privacy repercussions of the above threat models.…”

Digital body, identity and privacy in social virtual reality: A systematic review

“…In response to the problems mentioned above, we hope to find corresponding protection mechanisms or potential countermeasures in the literature. While 13 papers (Gavrilova and Yampolskiy, 2010;Boukhris et al, 2011;Mohamed and Yampolskiy, 2012;Yampolskiy et al, 2012;Bader and Ben Amara, 2014a;Bader and Ben Amara, 2014b;Bader and Ben Amara, 2016;Bader and Ben Amara, 2017;Falchuk et al, 2018;Pfeuffer et al, 2019;John et al, 2020;Lake, 2020) have explicitly addressed one or several identity and privacy issues and proposed corresponding protection mechanisms, works that have presented techniques or design guidelines that provide potential solutions in the area of virtual reality are also included and analyzed. Based on their characteristics and objectives, we have subdivided them into the following categories.…”

“…On the other hand, instead of seeking to improve the performance of authentication, John et al (2020) implemented and evaluated a hardware-based eye-tracking defocus configuration that prevents biometric leaking during eye animation and iris authentication. Their evaluations reveal the security-utility trade-off between iris authentication and eye animation performance and suggest two different defocus configurations for each preference.…”

“…However, most current methods still require specific scenarios or tasks, and the way forward should be continuous authentication of users regardless of the environment and their activities. Additionally, research such as John et al (2020) that considers the trade-off between the use of biometrics and potential privacy breaches deserves more attention.…”