Travel: Student Travel Grant for 2022 Boston Differential Privacy Summer School

旅行：2022 年波士顿差异隐私暑期学校学生旅行补助金

• 批准号: 2227905
• 负责人: Adam Smith
• 金额: $ 1.5万
• 依托单位: Trustees of Boston University
• 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: 2022-06-01 至 2023-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2227905&HistoricalAwards=false
• 关键词: Travel; Student; Grant; 2022; Boston

The widespread use of sensitive personal information to train data-driven systems raises myriad challenges relating to privacy. One central question is the extent to which the outputs of a system—summary statistics, decisions, machine learning models, and more—reveal individual-level information. Differential privacy has emerged as a central concept in addressing this question. There is a broad and still growing body of research on differential privacy, as well as a number of deployed differentially private systems in industry and government.This award will provide travel grants for US-based students to attend the Differential Privacy summer school to be held in Boston, MA, June 6-10, 2022, partly co-located with the Symposium on the Foundations of Responsible Computing (FORC 2022), also held in Boston. The DP summer school will introduce students to a range of cutting-edge topics in the theory and applications of differential privacy. These include short courses on differentially private statistical inference, the issues arising in practical deployments at national scale, synthetic data generation, and algorithms for private processing of distributed data. There will also be guest lectures on connections between privacy and other fields, notably law and policy. Students will have the opportunity to work closely with each other, professionals in the field, and the faculty on the short-course topics via in-class interactions and problem-solving sessions. The summer school will provide a unique opportunity to graduate students to learn the state of the art in an important and rapidly developing field.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.

广泛使用敏感的个人信息来培训数据驱动系统的宽度增加了与隐私有关的无数挑战。一个核心问题是系统的输出（符号统计信息，决策，机器学习模型等）的程度。差异隐私已成为解决这个问题的中心概念。关于差异隐私的研究仍有广泛而又不断增长的研究，以及许多部署在行业和政府中的部署不同的私人系统。该奖项将为我们的基于美国的学生提供的旅行赠款，以参加2022年6月6日至10日在马萨诸塞州波士顿举行的差异隐私暑期学校，部分与负责任的计算机上的基础（同时是202222），该基础与bast of Cyc 2022222。 DP暑期学校将向学生介绍差异隐私理论和应用的一系列尖端主题。这些包括有关私人统计学不同的简短课程，国家规模上的实际部署，合成数据生成和用于私人处理分布式数据的算法的问题。关于隐私与其他领域之间的联系，尤其是法律和政策，还将有嘉宾讲座。学生将有机会通过课堂上的互动和解决问题的会议，相互紧密合作，现场专业人士以及短课主题的教师。暑期学校将为研究生提供一个独特的机会，以在重要且迅速发展的领域学习最新技术。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子优点和更广泛的影响评估标准通过评估而被认为是珍贵的支持。