EAGER: DCL: SaTC: Enabling Interdisciplinary Collaboration: Adapting Economic Games to Personalize Privacy and Security Nudges

EAGER：DCL：SaTC：实现跨学科合作：调整经济游戏以个性化隐私和安全推动

• 批准号: 2209507
• 负责人: Yan Chen
• 金额: $ 30万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2209507&HistoricalAwards=false
• 关键词: EAGER; DCL; SaTC; Enabling; Interdisciplinary

Modern social communication systems, ranging from email to social media systems, present a dizzying number of decisions for their users. Moreover, privacy and security configurations are often hidden and opaque. Thus it is hard for individuals to manage configurations and behaviors in ways that are consistent with their preferences. Bad actors or adversarial agents can take advantage of ambiguity or information leaks that result from poor settings and user uncertainty to find attack routes for disinformation and phishing. Conversely, socially beneficial behaviors that require data sharing are also hindered. A better understanding of the relationships among preferences, behaviors, and interfaces can help address these concerns. Business interests in preventing phishing can be preserved by understanding individual preferences and their relationship to employee behaviors. Personalized interventions can be applied when preferences conflict with socially beneficial data behaviors. This project synthesizes insights from behavioral economics and computing to promote information security.The project team seeks to tackle this challenge by modeling individual preferences through the use of decision- and game- theoretic economic games to identify individual risk, ambiguity, and information preferences. The experimental games simulate competing and cooperating incentives and strategies, such as in the Prisoner’s Dilemma game. The appeal of these types of games is that a comparatively small subset of them may be useful to model a set of preferences that are predictive of a broad range of real-world behaviors. The team is modifying these games to better align with real-world communication tasks in a social media system. Behavioral experiments can provide novel evidence of the predictive value of the games and validate their use in novel contexts. The results may transform work in human-computer interaction, security, and privacy research and design by isolating simpler incentive-compatible instruments that model user preferences and correlate well with behaviors. This connection enables novel interventions from personalized interfaces to personally or socially beneficial interventions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

现代社交通信系统，从电子邮件到社交媒体系统，为用户提供了令人眼花缭乱的决策，而且，隐私和安全配置通常是隐藏的和不透明的，因此个人很难以透明的方式管理配置和行为。不良行为者或敌对代理可以利用由于不良设置和用户不确定性而导致的模糊性或信息泄露来寻找虚假信息和离线网络钓鱼的攻击路线。需要数据共享的社会有益行为也会受到阻碍。了解偏好、行为和界面之间的关系有助于解决这些问题。当偏好与对社会有益的数据行为发生冲突时，可以通过了解个人偏好及其与员工行为的关系来维护防止网络钓鱼的商业利益。该项目综合了行为经济学和计算的见解，以促进信息安全。项目团队试图通过使用决策和博弈论经济博弈来对个人偏好进行建模，以识别个人风险、模糊性和信息偏好，从而应对这一挑战。游戏模拟竞争和合作激励和策略，例如在囚徒困境游戏中，此类游戏的吸引力在于，其中相对较小的子集可能有助于模拟一组可预测广泛的现实世界行为的偏好。该团队正在修改这些游戏，以更好地适应社交媒体系统中的现实世界通信任务。行为实验可以提供游戏预测价值的新证据，并验证它们在新环境中的使用。结果可能会改变人类的工作。计算机交互、安全和通过隔离更简单的激励兼容工具来进行隐私研究和设计，这些工具可以模拟用户偏好并与行为良好相关，这种联系使得从个性化界面到对个人或社会有益的干预措施等新颖的干预措施成为可能。该奖项是法定使命，并且通过使用评估被认为值得支持。基金会的智力价值和更广泛的影响审查标准。