TWC: Small: Collaborative: Practical Security Protocols via Advanced Data Structures

TWC：小型：协作：通过高级数据结构实现实用安全协议

• 批准号: 1526950
• 负责人: Charalampos Papamanthou
• 金额: $ 16.66万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-15 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1526950&HistoricalAwards=false
• 关键词: TWC; Small; Collaborative; Practical; Security

Data structures have a prominent modern computational role, due to their wide applicability, such as in database querying, web searching, and social network analysis. This project focuses on the interplay of data structures with security protocols, examining two different paradigms: the security for data structures paradigm (SD) and the data structures for security paradigm (DS). The objectives of this project are, in the SD paradigm, to provide security and privacy both for data elements in data sets and also for the inter-relationships and distributions between such data elements, such as links between nodes in a social network, and, in the DS paradigm, to develop new data structures to improve the efficiency of algorithms for security and/or privacy applications. The project explores methods for achieving these objectives include algorithm design, theoretical analysis, rigorous proofs of security and correctness, and experimental validation of claims of practicality. This research focuses on the security and cybersecurity uses of three advanced data structures: tree structures, invertible Bloom filters and cascading tables. The project advances knowledge on (a) authenticated data structures and verifiable query execution within the SD paradigm, and (b) secure deduplication, searchable encryption, and privacy-preserving memory allocators within the DS paradigm.

数据结构具有突出的现代计算作用，由于其广泛的适用性，例如在数据库查询，Web搜索和社交网络分析中。该项目的重点是数据结构与安全协议的相互作用，研究两种不同的范式：数据结构范式（SD）和安全范式（DS）的数据结构。该项目的目标是，在SD范式，提供安全和隐私的数据集的数据元素，也为这些数据元素之间的相互关系和分布，如在社交网络中的节点之间的链接，并在DS范式，开发新的数据结构，以提高安全和/或隐私应用程序的算法的效率。该项目探索实现这些目标的方法，包括算法设计，理论分析，严格的安全性和正确性证明，以及对实用性要求的实验验证。本研究重点关注三种高级数据结构的安全和网络安全使用：树结构，可逆Bloom过滤器和级联表。该项目的进步知识（a）认证的数据结构和可验证的查询执行SD范式内，和（B）安全的重复数据删除，可搜索的加密，和隐私保护的内存分配DS范式内。