休闲vrauth:一种设计框架,连接虚拟现实中行为认证的重点和休闲交互。

IF 6.5
GuanYu Ye, BoYu Gao, Huawei Tu
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引用次数: 0

摘要

当前虚拟现实(VR)中的行为认证系统需要在任务执行过程中持续集中交互——这一假设经常与现实世界的两个因素不相容:(1)物理限制(例如,手/眼活动受限);(2)心理障碍(例如,任务切换疲劳或在场破坏)。为了解决这种注意力差距,我们提出了一个设计框架,在基于行为的VR认证(casual - vrauth)中连接集中和随意的交互。基于该框架,我们设计了一个使用改进的球-隧道任务(沿着圆形路径推进球)的身份验证原型,支持三种交互模式:基线触摸和两种无需眼睛的选项(悬停/点击)。实验结果表明,我们的框架有效地指导了具有不同交互参与水平(触摸>悬停>点击)的认证系统的设计,以适应需要随意交互的场景(例如,多任务或无眼睛操作)。此外,我们发现减少互动参与可以增强对模仿攻击的抵抗力,同时减少多任务处理或无眼环境下的认知工作量和错误率。但是,这种方法会影响不同算法(包括InceptionTime、FCN、ResNet、CNN、MLP和MCDCNN)下交互行为的平均分类精度。值得注意的是,适度减少交互参与度可以提高认证速度,而过度减少则可能反过来减慢认证速度。总的来说,我们的工作为VR认证建立了一个新的设计范例,支持随意的交互,并为平衡可用性和安全性提供了有价值的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Casual-VRAuth: A Design Framework Bridging Focused and Casual Interactions for Behavioral Authentication in Virtual Reality.

Current behavioral authentication systems in Virtual Reality (VR) require sustained focused interaction during task execution - an assumption frequently incompatible with real-world constraints across two factors: (1) physical limitations (e.g., restricted hand/eye mobility), and (2) psychological barriers (e.g., task-switching fatigue or break-in-presence). To address this attentional gap, we propose a design framework bridging focused and casual interactions in behavior-based VR authentication (Casual-VRAuth). Based on this framework, we designed an authentication prototype using a modified ball-and-tunnel task (propelling a ball along a circular path), supporting three interaction modes: baseline Touch, and two eyes-free options (Hover/Tapping). Experimental results demonstrate that our framework effectively guides the design of authentication systems with varying interaction engagement levels (Touch >Hover >Tapping) to accommodate scenarios requiring casual interaction (e.g., multitasking or eyes-free operation). Furthermore, we revealed that reducing interaction engagement enhances resistance to mimicry attacks while decreasing cognitive workload and error rates in multitasking or eyes-free environments. However, this approach compromises the average classification accuracy of Interaction behavior under different algorithms (including InceptionTime, FCN, ResNet, CNN, MLP, and MCDCNN). Notably, moderate reduction of interaction engagement enhances authentication speed, while excessive reduction may conversely slow it down. Overall, our work establishes a novel design paradigm for VR authentication that supports casual interactions and offers valuable insights into balancing usability and security.

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