EAGER: Designing Individualized Privacy and Security Systems

这个项目探讨了人格特征在多大程度上预测隐私和安全行为。在过去的十年里，由于在设计过程中考虑了人为因素，计算机的隐私和安全性得到了突飞猛进的提高。然而，之前提高隐私和安全系统可用性的工作只检查了“普通用户”的行为，这被认为只能产生局部最大值，因为没有人完全符合这一特征。因此，本项目正在研究在何种程度上可以通过使系统设计适应个体差异（例如，个性特征）而进一步改进。通过一系列调查和对照实验，研究人员正在发现这些人格特征如何预测某些隐私决策，以及与各种安全缓解措施的相互作用。例如，了解用户的个性特征可能会在社交网站上设置更合适的默认隐私设置，或者对该用户更明显的网络浏览器安全警告。研究人员的目标是最终设计出能够推断个性特征的系统，然后调整隐私和安全机制，从而产生与特定用户偏好最优一致的结果。

This project explores the extent to which personality traits predict privacy and security behaviors. Over the past decade, computer privacy and security have improved by leaps and bounds by considering human factors in the design process. However, previous work to improve the usability of privacy and security systems has only examined the behaviors of "average users," which is believed to only yield local maxima because no individual perfectly fits this profile. Therefore, this project is examining the extent to which additional improvements can be made by catering system designs to individual differences (e.g., in personality traits). Through a series of surveys and controlled experiments, researchers are discovering how these personality traits are predictive of certain privacy decisions, as well as interactions with various security mitigations. For instance, knowledge of a user's personality traits may result in more appropriate default privacy settings on a social networking website or web browser security warnings that are more salient to that user. The researchers' goal is to ultimately design systems that infer personality traits and then adjust privacy and security mechanisms so as to yield outcomes that are optimally aligned with a particular user's preferences.