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Practical Data-intensive Secure Computation: a Data Structural Approach

实用数据密集型安全计算：数据结构方法

基本信息

批准号：
EP/M013561/1
负责人：
Changyu Dong
金额：
$ 48.11万
依托单位：
University of Strathclyde
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2016
资助国家：
英国
起止时间：
2016 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FM013561%2F1
关键词：
Practical Data intensive Secure Computation

项目摘要

In the past a few year, we have seen a dramatic increase in the scale and financial damage caused by cyber attacks. A survey commissioned by the government's Department for Business, Innovations and Skills (BIS) found that 93% of large businesses and 87% of smaller businesses suffered security breaches during 2013. An estimation from IDC says that companies around the world will spend $364 billion for dealing with data breaches in 2014. Data security is of paramount importance for most organisations. Compounding the problem, changes in computing -- particularly the booming of Cloud computing and collaborative data analysis -- has added another layer of complexity to the security landscape. Secure computation has the potential to completely reshape the cybersecruity landscape, but this will happen only if we can make it practical. Despite significant improvements recently, secure computation is still orders of magnitude slower than computation in the clear. Even with the latest technology, running the killer apps, which are often data-intensive, in secure computation is still a mission impossible. To make secure computation practical, we propose this groundbreaking data structural approach.In computer science, there are two fundamental approaches to improve performance of computation: by using a better algorithm, or by using a proper data structure. In secure computation, we have seen many improvements through the algorithmic approach. But surprisingly, data structures have been largely overlooked in the past. Recently, we have found ample evidence in our own and also others' research that data structures can be a key efficiency and scalability booster of secure computation. Based on the evidence, we believe the situation is sure to change: with data playing the central role and driving the computation, data structural design will become an indispensable part of secure computation. It is time to systematically investigate the design of data structures and accompanied protocols in the context of secure computation. Our proposed research will make scientific advances by investigating both data structures and cryptography. The starting point will be comprehensive case-by-case studies. Then the focus will be solving more complex problems by composition and to make data structures generic across multiple secure computation frameworks. Eventually we will draw design principles to guide future design practice.

在过去的几年里，我们看到网络攻击的规模和造成的经济损失急剧增加。政府商业、创新和技能部(BIS)委托进行的一项调查发现，93%的大企业和87%的小企业在2013年遭遇了安全漏洞。IDC的一项估计显示，2014年全球公司将花费3640亿美元处理数据泄露问题。对于大多数组织来说，数据安全至关重要。使问题雪上加霜的是，计算的变化--特别是云计算和协作数据分析的蓬勃发展--给安全格局增加了另一层复杂性。安全计算有可能彻底重塑网络安全格局，但这只有在我们能够使其变得实用的情况下才会发生。尽管最近有了重大改进，但安全计算仍然比明文计算慢了几个数量级。即使有了最新的技术，在安全计算中运行往往是数据密集型的杀手级应用程序仍然是一项不可能完成的任务。为了使安全计算变得实用，我们提出了这种突破性的数据结构方法。在计算机科学中，有两种基本方法来提高计算性能：使用更好的算法，或使用适当的数据结构。在安全计算方面，我们已经看到了通过算法方法的许多改进。但令人惊讶的是，数据结构在过去很大程度上被忽视了。最近，我们在自己和其他人的研究中发现了大量证据，表明数据结构可以成为安全计算的关键效率和可伸缩性推进器。基于证据，我们相信这种情况肯定会改变：随着数据发挥核心作用并推动计算，数据结构设计将成为安全计算不可或缺的一部分。现在是时候在安全计算的背景下系统地研究数据结构和伴随协议的设计了。我们提出的研究将通过研究数据结构和密码学来取得科学进展。起点将是全面的个案研究。然后，重点将是通过组合来解决更复杂的问题，并使数据结构在多个安全计算框架中通用。最终，我们将得出设计原则来指导未来的设计实践。

项目成果

期刊论文数量（4）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Information Flow Control with Minimal Tag Disclosure

DOI：
10.1145/2896387.2896402
发表时间：
2016-03
期刊：
Proceedings of the International Conference on Internet of things and Cloud Computing
影响因子：
0
作者：
Hajoon Ko;Jatinder Singh;Thomas Pasquier;Changyu Dong;D. Eyers;J. Bacon
通讯作者：
Hajoon Ko;Jatinder Singh;Thomas Pasquier;Changyu Dong;D. Eyers;J. Bacon

Efficient Delegated Private Set Intersection on Outsourced Private Datasets