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CAESAR: Mixed Reality Search-and-Rescue Platform for Cognitive Attack Evaluation

Mingyu Zhu, Jiangong Chen, Yu Liu, Hillmer Chona, Zifan Zhou, Jianan Jiang, Jonathan E. Dodge, Feng Qian, Mahdi Imani, Tian Lan, Gang Tan, Bin Li · 2026 · arXiv (Cornell University)

DOI: 10.48550/arxiv.2610.27654 · cited by 0 works (OpenAlex) · open-access PDF

Chinese

混合现实(MR)通过密切将虚拟内容与物理环境相结合并支持实体化互动来实现沉浸式训练,在安全关键的协作任务中,如搜索和救援数据中,用户依赖于虚拟元素进行感知、协调和决策,使他们容易受到微妙地扭曲视觉反馈、虚拟内容或系统同步的认知攻击。虽然以前的MR安全研究已经检查了单个攻击机制,但评估通常在孤立或单个用户设置中进行,并且缺乏标准化协作测试床进行系统反对实验。在本文中,我们研究 CAESAR,一个终端多用户MR框架,用于在协作搜索和救援培训中对认知攻击的系统评估。CAESAR提供了一个模块化架构,将四类认知

Machine translation (Meta M2M100); the English original follows.

Abstract

Mixed Reality (MR) enables immersive training by tightly coupling virtual content with the physical environment and supporting embodied interaction. In safety-critical collaborative tasks such as search-and-rescue, however, users rely heavily on virtual elements for perception, coordination, and decision-making, making them vulnerable to cognitive attacks that subtly distort visual feedback, virtual content, or system synchronization. While prior MR security research has examined individual attack mechanisms, evaluations are typically conducted in isolated or single-user settings, and there is a lack of standardized collaborative testbeds for systematic adversarial experimentation. In this paper, we develop CAESAR, an end-to-end multi-user MR framework for systematic evaluation of cognitive attacks in collaborative search-and-rescue training. CAESAR features a modular architecture that integrates four classes of cognitive attacks within a synchronized collaborative scenario and incorporates a multimodal data collection pipeline that captures behavioral, performance, and subjective measures under adversarial conditions. We conduct a controlled user study with an in-depth analysis of the latency-based attack, demonstrating measurable effects on task performance and user behavior while characterizing users' subjective experience under adversarial conditions.

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Topics: Human–computer interaction, Computer science, Virtual reality, Task (project management), Adversarial system, Cognition

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