III: Small: Collaborative Research: Suppressing Sensitive Aggregates over Hidden Web Databases, a Novel and Urgent Challenge

这个项目的目标是理解，评估，并有助于抑制隐藏数据库上的敏感聚合。隐藏数据库在Web上广泛流行，从政府机构的数据库、科学和卫生领域的数据库到商业领域的数据库。它们提供专有的类似表单的搜索接口，允许用户通过指定想要的元组的属性值来执行搜索查询，系统通过返回几个（例如，top-k）满意的元组来响应，这些元组由合适的排序函数排序。虽然隐藏数据库的所有者希望允许单独的搜索查询，但许多人也希望对隐藏数据库上的聚合保持一定程度的隐私。这对商业领域（例如，防止竞争对手获得战略优势）以及国土安全相关应用（例如，防止潜在的恐怖分子了解航班占用分布）都有影响。pi先前的工作开创了一种技术，即仅使用通过其专有前端发出的少量搜索查询，就能有效地获得隐藏数据库的近似聚合。这种强大而通用的技术也可能被对手用来获取敏感的聚合；因此，防御它们成为一项迫切的任务，需要立即予以注意。该项目研究了抑制敏感聚合的技术，同时为真正的搜索用户保持隐藏数据库的可用性。特别是，它探索了一个跨越隐藏数据库系统的所有三个组件的解决方案空间：(1)后端隐藏数据库，(2)查询处理模块，(3)前端搜索接口。该项目的智力价值是双重的：(1)问题新颖性：它开创了在隐藏数据库上抑制敏感聚合的信息隐私研究的新方向；(2)解决方案新颖性：它研究了跨越这三个组件的各种有前途的技术。这项研究的结果对国家的高等教育系统和高科技产业有更广泛的影响。该项目的部分内容将由德克萨斯大学阿灵顿分校和乔治华盛顿大学的学生作为高级班项目或个人研究项目进行。

The objective of this project is to understand, evaluate, and contribute towards the suppression of sensitive aggregates over hidden databases. Hidden databases are widely prevalent on the Web, ranging from databases of government agencies, databases that arise in scientific and health domains, to databases that occur in the commercial world. They provide proprietary form-like search interfaces that allow users to execute search queries by specifying desired attribute values of the sought-after tuple(s), and the system responds by returning a few (e.g., top-k) satisfying tuples sorted by a suitable ranking function.While owners of hidden databases would like to allow individual search queries, many also want to maintain a certain level of privacy for aggregates over their hidden databases. This has implications in the commercial domain (e.g., to prevent competitors from gaining strategic advantages) as well as in homeland-security related applications (e.g., to prevent potential terrorists from learning flight occupancy distributions). The PIs' prior work pioneered techniques to efficiently obtain approximate aggregates over hidden databases using only a small number of search queries issued via their proprietary front-end. Such powerful and versatile techniques may also be used by adversaries to obtain sensitive aggregates; thus defending against them becomes an urgent task requiring imminent attention. This project investigates techniques to suppress the sensitive aggregates while maintaining the usability of hidden databases for bona fide search users. In particular, it explores a solution space which spans all three components of a hidden database system: (1) the back-end hidden database, (2) the query processing module, and (3) the front-end search interface. The intellectual merit of the project is two-fold: (1) problem novelty: it initiates a new direction of research in information privacy of suppressing sensitive aggregates over hidden databases, and (2) solution novelty: it investigates a variety of promising techniques across the three components. The outcomes of this research have broader impacts on the nation's higher education system and high-tech industries. Parts of the project will be carried out by students of the University of Texas Arlington and George Washington University as advanced class projects or individual research projects.