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.

从电子邮件到社交媒体系统的现代社交通信系统为用户提供了令人眼花缭乱的决策。此外，隐私和安全配置通常是隐藏和不透明的。因此，个人很难以与其偏好一致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不良设置和用户不确定性导致的模糊性或信息泄漏来找到虚假信息和网络钓鱼的攻击路线。相反，需要数据共享的社会有益行为也会受到阻碍。更好地理解偏好、行为和界面之间的关系有助于解决这些问题。通过了解个人偏好及其与员工行为的关系，可以保护防止网络钓鱼的业务利益。当偏好与对社会有益的数据行为发生冲突时，可以应用个性化干预。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游戏来识别个人风险，模糊性和信息偏好，通过建模个人偏好来应对这一挑战。实验游戏模拟竞争和合作的激励和策略，如在囚徒困境游戏。这些类型的游戏的吸引力在于，它们中的一个相对较小的子集可能有助于建模一组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，以便更好地与社交媒体系统中的真实通信任务保持一致。行为实验可以为游戏的预测价值提供新的证据，并验证它们在新环境中的使用。这些结果可能会改变人机交互，安全和隐私研究和设计的工作，通过隔离更简单的激励兼容的工具，模型用户的偏好和行为相关。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。