CSR: Small: Collaborative Research: Multi-party Collaborative Data Access

CSR：小：协作研究：多方协作数据访问

• 批准号: 1527346
• 负责人: Krishna Kant
• 金额: $ 35.89万
• 依托单位: Temple University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-10-01 至 2020-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1527346&HistoricalAwards=false
• 关键词: CSR; Small; Collaborative; Research; Multi

As the richness and volume of data maintained by a wide variety of businesses and organizations increases, there is a growing need to derive useful information, not only from data owned by individual parties, but also across parties. The current data sharing practice is dominated by carefully negotiated, mostly secret, one-on-one agreements between organizations, and is seriously limited. It does not scale as the number of databases and organizations increase, cannot be formally analyzed for unintended information leaks or other violations, and may require unnecessary data exposure. This project explores a collaborative multi-party data sharing mechanism that allows safe and convenient sharing of databases in order to enable large-scale collaborative data analytics and knowledge extraction applications. Multi-party data sharing involves many challenges that the project attempts to address. First, it is necessary to have an intuitive specification of access control policies for data access across parties and an automated mechanism to translate those into a concise set of access rules while resolving conflicts, specification inadequacies, and other problems. Second, we need efficient and scalable implementation of allowed queries in spite of complex access restrictions. Third, it is necessary to handle both the traditional relational databases, its variants, and the emerging graph databases. Finally, we need mechanisms to efficiently check the integrity and completeness of the data supplied as answers. By addressing these challenges, the research hopes to establish the foundations of multiparty data sharing. Many of the formalizations in this research will exploit Satisfiability Modulo Theories (SMT) based methods for testing assertions and for resolving conflicts. With tremendous amount of data being generated by both cyber and cyberphysical systems, this project will help devise practical mechanisms to share data in a wide variety of scenarios and thereby accelerate the pace of data driven innovation applied to information systems serving the society.

随着各种各样的企业和组织所维持的数据的丰富性和数量的增加，不仅是从单个方拥有的数据，而且从各方拥有的数据中，越来越需要获得有用的信息。 当前的数据共享实践由组织之间经过精心谈判（大多是秘密的一对一协议）主导，并且受到严重限制。它不会随着数据库和组织数量的增加而扩展，无法正式分析意外信息泄漏或其他违规行为，并且可能需要不必要的数据曝光。 该项目探讨了一种协作多方数据共享机制，该机制允许安全和方便的数据库共享，以便实现大规模的协作数据分析和知识提取应用程序。多方数据共享涉及该项目试图解决的许多挑战。首先，有必要对跨各方的数据访问的访问控制策略进行直观的规范，并有一种自动化机制，以将这些访问转化为简洁的访问规则，同时解决冲突，规范不足之处和其他问题。其次，尽管有复杂的访问限制，我们仍需要有效且可扩展的允许查询实现。第三，有必要处理两个传统的关系数据库，其变体和新兴图形数据库。最后，我们需要机制来有效地检查提供的数据的完整性和完整性。 通过解决这些挑战，研究希望建立多方数据共享的基础。这项研究中的许多形式化都将利用基于可满足的模型理论（SMT）方法来测试断言和解决冲突。随着网络和网络物理系统的大量数据，该项目将有助于设计实用机制，以在各种情况下共享数据，从而加快应用于为社会服务的信息系统应用的数据驱动创新的步伐。