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

该项目的目标是了解，评估，并有助于抑制隐藏数据库的敏感聚合。隐藏数据库在Web上广泛流行，从政府机构的数据库，科学和健康领域的数据库到商业世界中的数据库。它们提供专有的类似表单的搜索接口，其允许用户通过指定所寻求的元组的期望属性值来执行搜索查询，并且系统通过返回一些（例如，虽然隐藏数据库的所有者希望允许单独的搜索查询，但许多人还希望在其隐藏数据库上为聚合保持一定程度的隐私。这在商业领域具有影响（例如，以防止竞争者获得战略优势）以及在国土安全相关的应用中（例如，以防止潜在的恐怖分子学习航班占用分布）。PI之前的工作开创了一种技术，可以通过其专有的前端仅使用少量的搜索查询来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得敏感的聚合物;因此，防御它们成为一项紧迫的任务，需要立即注意。这个项目研究的技术，以抑制敏感的聚集，同时保持真实的搜索用户的隐藏数据库的可用性。特别是，它探索了一个解决方案空间，它跨越了隐藏数据库系统的所有三个组件：（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）问题新奇：它启动了一个新的信息隐私研究方向，即抑制隐藏数据库上的敏感聚合，以及（2）解决方案新奇：它调查了三个组成部分中各种有前途的技术。这项研究的成果对国家的高等教育系统和高科技产业产生了更广泛的影响。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.