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

随着由各种各样的企业和组织维护的数据的丰富性和量的增加，不仅需要从单个方拥有的数据中，而且需要从跨各方拥有的数据中获得有用的信息。 目前的数据共享实践主要是由组织之间经过仔细谈判达成的，大多是秘密的一对一协议，并且受到严重限制。它不能随着数据库和组织数量的增加而扩展，不能正式分析意外的信息泄漏或其他违规行为，并且可能需要不必要的数据暴露。 该项目探索了一种多方协作的数据共享机制，允许安全方便地共享数据库，以实现大规模的协作数据分析和知识提取应用。多方数据共享涉及该项目试图解决的许多挑战。首先，需要有一个直观的访问控制策略规范，用于跨各方的数据访问，并有一个自动化的机制将其转换为一组简洁的访问规则，同时解决冲突，规范不足和其他问题。第二，我们需要有效的和可扩展的实现允许的查询，尽管复杂的访问限制。第三，需要处理传统的关系数据库及其变体和新兴的图形数据库。最后，我们需要有效地检查作为答案提供的数据的完整性和完整性的机制。 通过应对这些挑战，该研究希望为多方数据共享奠定基础。在这项研究中的许多形式化将利用基于可满足性模理论（SMT）的方法来测试断言和解决冲突。由于网络和网络物理系统产生了大量数据，该项目将有助于设计实用的机制，在各种场景中共享数据，从而加快应用于服务社会的信息系统的数据驱动创新的步伐。

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.