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Details of Grant 

EPSRC Reference: EP/M013561/1
Title: Practical Data-intensive Secure Computation: a Data Structural Approach
Principal Investigator: Dong, Professor C
Other Investigators:
Researcher Co-Investigators:
Project Partners:
University of Maryland
Department: Computer and Information Sciences
Organisation: University of Strathclyde
Scheme: Standard Research
Starts: 01 January 2016 Ends: 31 March 2016 Value (£): 377,537
EPSRC Research Topic Classifications:
Fundamentals of Computing Information & Knowledge Mgmt
EPSRC Industrial Sector Classifications:
Information Technologies
Related Grants:
Panel History:
Panel DatePanel NameOutcome
02 Dec 2014 EPSRC ICT Prioritisation Panel - Dec 2014 Deferred
27 Jan 2015 EPSRC ICT Prioritisation Panel - Jan 2015 Announced
Summary on Grant Application Form
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.
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