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

III：小型：协作研究：抑制隐藏 Web 数据库上的敏感聚合：一项新颖而紧迫的挑战

• 批准号: 0915834
• 负责人: Nan Zhang
• 金额: $ 23.08万
• 依托单位: George Washington University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2014-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0915834&HistoricalAwards=false
• 关键词: III; Small; Collaborative; Research; Suppressing

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.

该项目的目标是了解、评估和促进抑制隐藏数据库上的敏感聚集。隐藏的数据库在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，到商业世界的数据库。它们提供专有的类似表单的搜索界面，允许用户通过指定受欢迎的元组(S)的所需属性值来执行搜索查询，而系统的响应是返回几个(例如，top-k)满足按适当排名函数排序的元组。虽然隐藏数据库的所有者希望允许单独的搜索查询，但许多人也希望对其隐藏数据库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)以及与国土安全相关的应用(例如，防止潜在恐怖分子了解航班占有率分布)具有影响。PI之前的工作开创了仅使用通过其专有前端发布的少量搜索查询来高效地获取隐藏数据库上的近似聚合的技术。这种强大而多才多艺的技术也可能被对手用来获取敏感的聚集体；因此，防御它们成为一项紧迫的任务，需要立即注意。该项目研究如何抑制敏感聚集，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，和(3)前端搜索界面。该项目的智力价值有两个方面：(1)问题新颖性：它开启了抑制隐藏数据库上的敏感聚合的信息隐私研究的新方向，以及(2)解决方案新颖性：它研究了这三个组件中各种有前途的技术。这项研究的结果对中国的高等教育系统和高科技产业产生了更广泛的影响。该项目的一部分将由德克萨斯大学阿灵顿大学和乔治华盛顿大学的学生作为高级课堂项目或个人研究项目进行。