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CAREER:Information Theoretic Methods for Private Information Retrieval and Search in Distributed Storage Systems

职业：分布式存储系统中隐私信息检索和搜索的信息论方法

基本信息

批准号：
1817635
负责人：
Salim El Rouayheb
金额：
$ 62.4万
依托单位：
Rutgers University New Brunswick
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-09-01 至 2023-02-28
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1817635&HistoricalAwards=false
关键词：
CAREER Information Theoretic Methods Private

项目摘要

The recent data revolution is driving many aspects of modern societal and economic progress. Most of this massive data is now stored in the cloud to enable easy access for a myriad of users who wish to share information including, for example, photos, videos, publications, opinions, and scientific data. Unfortunately, this has come at the expense of the user's privacy whose online activity can be used to profile him/her, making large parts of the population an easy target for discrimination and possible persecution. This research aims at addressing the privacy challenge of data in the cloud by focusing on the problem of Private Information Retrieval (PIR) and Search in distributed storage systems (DSSs). PIR schemes enable users to query data without revealing information about the queries and hence their personal preferences, tendencies, health, or other traits.Classical information theoretic PIR schemes require data to be replicated, which is not a scalable solution given the exponential growth of data. This research aims at creating a unified framework for studying coding schemes that, in addition to providing data reliability, cater to the need of private queries. The focus of the proposed research is on (i) explicit constructions of codes and PIR schemes that address practical and important aspects of distributed storage, such as storage cost, network communication cost, disk reads, latency and computations; (ii) explicit constructions of codes and schemes for private keyword search; (iii) characterization of the fundamental limits and tradeoffs between reliability, privacy and the different system overheads; (iv) testing software implementations of the schemes on real genomic and social science data. The project also incorporates several educational and outreach efforts, including the development of new publicly accessible online content on information theory, security, and privacy in distributed storage systems as well as pre-college outreach through the Global Leaders Program at the PI's institution.

最近的数据革命正在推动现代社会和经济进步的许多方面。现在，大部分海量数据都存储在云中，以便无数希望共享信息（包括照片、视频、出版物、观点和科学数据）的用户可以轻松访问。不幸的是，这是以牺牲用户的隐私为代价的，用户的在线活动可被用来描述他/她，使很大一部分人很容易成为歧视和可能迫害的目标。本研究旨在通过关注分布式存储系统（DSS）中的隐私信息检索（PIR）和搜索问题来解决云中数据的隐私挑战。 PIR 方案使用户能够查询数据，而无需透露有关查询的信息，从而避免透露他们的个人偏好、倾向、健康状况或其他特征。经典信息论 PIR 方案需要复制数据，考虑到数据的指数级增长，这不是一个可扩展的解决方案。本研究旨在创建一个统一的框架来研究编码方案，除了提供数据可靠性外，还可以满足私有查询的需求。拟议研究的重点是（i）显式构建代码和 PIR 方案，解决分布式存储的实际和重要方面，例如存储成本、网络通信成本、磁盘读取、延迟和计算； (ii) 明确构建私有关键词搜索的代码和方案； (iii) 基本限制的特征以及可靠性、隐私性和不同系统开销之间的权衡； (iv) 在真实基因组和社会科学数据上测试该方案的软件实现。该项目还包括多项教育和推广工作，包括开发关于分布式存储系统中的信息论、安全和隐私的新的可公开访问的在线内容，以及通过 PI 机构的全球领导者计划进行大学预科推广。