EAGER: SaTC: Early-Stage Interdisciplinary Collaboration: Econometrically Inferring and Using Individual Privacy Preferences
EAGER: SaTC: Early-Stage Interdisciplinary Collaboration: Econometrically Inferring and Using Individual Privacy Preferences
批准号:
1915813
负责人:
Denis Nekipelov
金额:
$29.96万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-06-01 至 2023-05-31
中文摘要
许多在线平台使用经济机制来估计将消费者和企业与产品和服务相匹配的最佳方式。有效的匹配可能需要使用个人消费者数据,但这样做可能会侵犯消费者的隐私。这个项目将使用正式的隐私概念来分析个人信息在机制设计中的使用。该项目的目标是开发工具,以了解收集和使用个人数据的价值和成本,并提供机制,允许设计者建立系统,在效用和隐私之间做出有意义和众所周知的权衡。该项目结合了机制设计和计量经济学的研究,为隐私提供了一个新的视角。该项目将开发使用计量经济学的想法来揭示个人的具体隐私偏好和聚合分布的方法,并将这些偏好与包括差异隐私在内的正式隐私模型联系起来。揭示的个人隐私偏好,或分发的集合,然后可以用于设计基于用户个人隐私偏好的具体和有意义的隐私和效用权衡机制。更广泛的目标是将抽象的隐私保障转化为具体的工具,将隐私偏好纳入其中,以最大化消费者效用和商业决策。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
Many online platforms use economic mechanisms to estimate the best ways to match consumers and businesses with products and services. Effective matches may require using personal consumer data but doing so may intrude on consumers' privacy. This project will use formal concepts of privacy to analyze the use of personal information in mechanism design. The goal is to develop tools for understanding the value and cost of collecting and using personal data, and provide mechanisms that allow designers to build systems that make meaningful and well understood tradeoffs between utility and privacy.The project combines research on mechanism design and econometrics to provide a new perspective on privacy. The project will develop methods that use ideas from econometrics to reveal concrete privacy preferences for individuals and aggregate distributions, and connect those preferences to formal privacy models, including differential privacy. The revealed privacy preferences for individuals, or aggregate for distributions, can then be used to design mechanisms with concrete and meaningful privacy and utility tradeoffs based on users' individual privacy preferences. The broader goal is to transform abstract privacy guarantees into concrete tools for incorporating privacy preferences to maximize consumer utility as well as business decisions.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.
期刊论文(2)
专著(0)
科研奖励(0)
会议论文
DOI:
--
发表时间:
2019-10
期刊:
影响因子:
--
作者:
[Lingxiao Wang;Bargav Jayaraman;David Evans;Quanquan Gu]
通讯作者:
Lingxiao Wang;Bargav Jayaraman;David Evans;Quanquan Gu
DOI:
--
发表时间:
2022
期刊:
Proceedings on Privacy Enhancing Technologies
影响因子:
--
作者:
[Suri, Anshuman, Evans, David]
通讯作者:
Evans, David
Convergence Accelerator Phase I (RAISE): Unpacking the Technology Career Path
-
批准号:1936956
-
项目类别:Standard Grant
-
资助金额:$73.53万
-
财政年份:2019
-
负责人:Denis Nekipelov
-
依托单位:
AF: Medium: Collaborative Research: Econometric Inference and Algorithmic Learning in Games
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批准号:1563708
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项目类别:Continuing Grant
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资助金额:$44.55万
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财政年份:2016
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负责人:Denis Nekipelov
-
依托单位:
ICES: Large: Collaborative Research: Towards Realistic Mechanisms: statistics, inference, and approximation in simple Bayes-Nash implementation
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批准号:1449239
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项目类别:Standard Grant
-
资助金额:$13.84万
-
财政年份:2014
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负责人:Denis Nekipelov
-
依托单位:
ICES: Large: Collaborative Research: Towards Realistic Mechanisms: statistics, inference, and approximation in simple Bayes-Nash implementation
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批准号:1101706
-
项目类别:Standard Grant
-
资助金额:$32.56万
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财政年份:2011
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负责人:Denis Nekipelov
-
依托单位:
Statistical Properties of Numerical Derivatives and Algorithms
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批准号:1025035
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项目类别:Standard Grant
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资助金额:$13.72万
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财政年份:2010
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负责人:Denis Nekipelov
-
依托单位:
海外基金