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.

该项目通过专注于严格的数学建模和私人信息价值表征来采用涉及敏感数据的问题的新方法。通过专注于量化受影响个体的信息所致的损失并量化这种工作的伴随益处 - 这项工作提出的方法可以使有关敏感数据的各种潜在计算的相对风险和奖励的具体推理。具体来说，这项工作具有四个主要的技术推力。首先是开发新模型和定义，使您可以将隐私注意事项纳入代理实用功能。第二个是根据这些模型来分析引起敏感信息的可行性和成本。第三个重点是在个人重视隐私的设置中实现更复杂的计算。最后，更复杂的环境结合了其他参与者的利益。该项目的目标之一不仅是为了开发私人信息价值的科学，而且是在计算机科学与经济学之间建立桥梁，以实现此类工作。此外，该项目开发的模型和算法可能会为有关敏感数据的使用，交换和货币化的未来法规提供信息。该项目支持并得到各种教育目标的支持，包括在一系列阶段的学生参与，开发具有大量研究组成部分的课程系列以及评估旨在促进有意义地参与研究文献的教学技术。