CAREER: The Value of Privacy

职业：隐私的价值

• 批准号: 1254169
• 负责人: Adam Wierman
• 金额: $ 54.2万
• 依托单位: California Institute of Technology
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-06-01 至 2018-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1254169&HistoricalAwards=false
• 关键词: CAREER; Value; Privacy

This project takes a new approach to problems involving sensitive data, by focusing on rigorous mathematical modeling and characterization of the value of private information. By focusing on quantifying the loss incurred by affected individuals when their information is used -- and quantifying the attendant benefits of such use -- the approaches advanced by this work enable concrete reasoning about the relative risks and rewards of a wide variety of potential computations on sensitive data. Specifically, this work has four main technical thrusts. The first is the development of new models and definitions, enabling privacy considerations to be incorporated into agent utility functions. The second is analysis of the feasibility and costs of eliciting sensitive information, in light of these models. The third focus is on enabling more sophisticated computations in settings where individuals value their privacy. Finally, more complex settings incorporate the interests of additional actors.One of the goals of this project is not only to develop a science of the value of private information, but to build bridges between computer science and economics that will enable such work. Further, the models and algorithms developed by this project could inform future regulation regarding the use, exchange, and monetization of sensitive data. The project supports and is supported by a wide variety of educational goals, including significant research involvement of students at a range of stages, development of a course series with a substantial research component, and assessment of a pedagogical technique created to facilitate meaningful engagement with research literature.

这个项目采用了一种新的方法来解决涉及敏感数据的问题，重点是对私人信息的价值进行严格的数学建模和表征。通过侧重于量化受影响的个人在使用其信息时所遭受的损失--以及量化这种使用带来的好处--这项工作提出的方法使人们能够具体推理对敏感数据进行各种潜在计算的相对风险和回报。具体地说，这项工作有四个主要的技术推动力。首先是开发新的模型和定义，使隐私考虑因素能够纳入代理实用程序功能。第二是根据这些模型对获取敏感信息的可行性和成本进行分析。第三个重点是在个人重视隐私的环境中实现更复杂的计算。最后，更复杂的环境包含了更多参与者的利益。这个项目的目标之一不仅是发展一门关于私人信息价值的科学，而且在计算机科学和经济学之间建立桥梁，从而使这项工作成为可能。此外，该项目开发的模型和算法可以为未来有关敏感数据的使用、交换和货币化的监管提供信息。该项目支持并得到各种教育目标的支持，包括让学生在不同阶段大量参与研究，开发具有大量研究内容的系列课程，以及评估为促进有意义地接触研究文献而创建的教学技术。