Information Technology Research (ITR): Sensitive Information in a Wired World

信息技术研究 (ITR)：有线世界中的敏感信息

• 批准号: 0331548
• 负责人: Joan Feigenbaum
• 金额: --
• 依托单位: Yale University
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-10-01 至 2010-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0331548&HistoricalAwards=false
• 关键词: Information; Technology; Research; ITR; Sensitive

Increasing use of computers and networks in business, government,recreation, and almost all aspects of daily life has led to aproliferation of sensitive data (i.e., data that, if used improperly,can harm data subjects or other relevant parties), and concern aboutthe ownership, control, privacy, and accuracy of these data has becomea top priority. Despite significant technical accomplishments in relevant research fields (e.g., cryptology and security, databasesystems, and data mining), there is no comprehensive, end-to-endtechnological infrastructure for handling sensitive data over the entire course of their lifetime, nor is there even widespread socialagreement about the rights and responsibilities of major stakeholdersin our data-intensive, networked world.This project is a multi-institutional, multi-disciplinary, multi-modalproject that looks comprehensively at sensitive data in a networkedworld. There are two main academic centers of activity (Yale andStanford), three smaller-scale academic participants (StevensInstitute of Technology, NYU, and the University of New Mexico), andsubstantial participation by non-academic partners, includingtechnology companies, (IBM, HP, and Microsoft), representatives ofuser communities (Citigroup, NIH, Yale Center for Medical Informatics,the Census Bureau, and the Secret Service), and DC-based policyorganizations (The Center for Democracy and Technology and TheElectronic Privacy Information Center).A major technical theme of the project is privacy-preserving datamining, and, more generally, techniques for meeting the potentiallyconflicting goals of respecting individual rights and allowing lawenforcement and other legitimate organizations to collect and minemassive data sets. Other technical agenda items include (1)accessibility and reliability of distributed data (2) operating onencrypted databases, (3) remote control of data, (4) repelling hostiledata, and (5) auditability of data-management systems. Because thesetechnical goals are affected by lack of agreement about the meaningsof basic terms, most notably "privacy," a major goal of the project isthe development of a conceptual framework for the study of rights,responsibilities, and public policies focused on sensitive-datahandling. This part of the project incorporates the notion of"contextual integrity," which considers both the context and thecontent of data sets in assessing sensitivity.Projected outcomes of the project include a next generation oftechnology for handling sensitive information that is qualitativelybetter than the current generation's and an effective conceptualframework for policy making and philosophical inquiry into the rightsand responsibilities of data subjects, data owners, and data users.

计算机和网络在商业，政府，娱乐中的使用增加以及日常生活的几乎所有方面都导致敏感数据（即，如果使用不当，可以损害数据主体或其他相关方），并担心这些数据的所有权，控制，控制和准确性。 尽管在相关研究领域（例如密码和安全性，数据库系统和数据挖掘）中取得了重大的技术成就，但在整个生命周期内都没有全面的，端到端技术基础架构来处理敏感数据，也没有广泛的社交范围，即使我们的数据依赖于我们的数据，我们的数据 - 依赖于我们的数据 - 依赖于我们的数据，这些企业是依据的，这些企业是依据的，即依赖于我们的数据。多学科的多模态对象，对网络世界中的敏感数据进行全面查看。 有两个主要的活动中心（Yale andStanford），三个较小规模的学术参与者（纽约大学史蒂文森·史蒂文汀斯特理工学院和新墨西哥大学），以及非学术伙伴的参与，包括技术伙伴，包括技术公司（包括IBM，HP，HP和Microsfornitive of Cunipers forcerserice forserities forsigrips，NIH YIH，YIH YIH，YIH YIH YIH，YIH YIH，局和特勤局）和基于DC的政策组织（民主技术中心以及电子隐私信息中心）。该项目的主要技术主题是保护隐私的数据进行数据进行，并且更广泛地是实现尊重个人权利并允许遵守律师事务和其他合法组织和其他合法组织的潜在目标的技术，可以集中和其他数据集合。 其他技术议程项目包括（1）分布式数据的可访问性和可靠性（2）操作OnCenepted数据库，（3）数据遥控器，（4）排斥HostileData，以及（5）数据管理系统的可审核性。 由于对基本术语的含义缺乏同意的影响，因此该项目的主要目标是该项目的主要目标是开发概念框架，以研究概念框架，以研究权利，责任和关注敏感性datahandling的公共政策。 该项目的这一部分融合了“上下文完整性”的概念，该概念在评估敏感性时都考虑了数据集的上下文和数据集。该项目的预期包括处理敏感信息的下一代技术，这些信息比当前一代和有效的概念概念化概念概念化概念概念概念和哲学概念和哲学概念和哲学概念和哲学概念和哲学概念和哲学概念和哲学概念和哲学概念的数据，并将其概念化。