用联合分析量化监控等风险因素对攻击者动机的影响，提升生物识别系统评估的实用性。
A Human-Centered Risk Evaluation of Biometric Systems Using Conjoint Analysis
- 通过联合分析建模攻击者动机与环境因素的关系
- 结合误接受率与攻击概率计算风险值，支持跨场景比较
- 基于600名日本受访者数据验证方法有效性，适合安全决策者
生物识别系统虽便捷，但其安全性受认证算法和部署环境影响。现有风险评估方法难以纳入攻击者动机这一关键因素，导致评价不完整。本文提出一种以人为中心的风险评估框架，利用联合分析量化监视摄像头等风险因素对攻击者动机的影响。该框架综合误接受率（FAR）与攻击概率计算风险值，支持不同应用场景的全面比较。通过对600名日本参与者开展调查，验证了方法的有效性，揭示了安全措施如何影响攻击者动机。该方法有助于决策者在保障可用性的前提下，定制化提升生物识别系统的安全性。
原文摘要 · Abstract (English)
Biometric recognition systems, known for their convenience, are widely adopted across various fields. However, their security faces risks depending on the authentication algorithm and deployment environment. Current risk assessment methods faces significant challenges in incorporating the crucial factor of attacker's motivation, leading to incomplete evaluations. This paper presents a novel human-centered risk evaluation framework using conjoint analysis to quantify the impact of risk factors, such as surveillance cameras, on attacker's motivation. Our framework calculates risk values incorporating the False Acceptance Rate (FAR) and attack probability, allowing comprehensive comparisons across use cases. A survey of 600 Japanese participants demonstrates our method's effectiveness, showing how security measures influence attacker's motivation. This approach helps decision-makers customize biometric systems to enhance security while maintaining usability.
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