The defence and security programme at The Alan Turing Institute is at the cutting edge of data science research, working in close collaboration with the Ministry of Defence, GCHQ, Dstl, and Joint Forces Command. The long-term projects in this programme – understanding conflict in high-risk populations, revolutionising data analytics with AI, and prototyping innovative cloud-based security software – are providing vital insights and developments to the defence and security community.
This long-term work has recently been bolstered by the announcement of a number of shorter, strategically important projects supported by funding from GCHQ. Each up to six months in duration, these projects aim to demonstrate immediate, meaningful impact, and address the key challenges that frame the defence and security programme. These challenges range from preventing and responding to urban security threats and improving cyber security, to understanding complex social systems through data and building privacy and trust in intelligent computing.
Dr Mark Briers, director of the defence and security programme, comments, “We have developed a comprehensive and complementary programme of research that draws across the breadth of data science, and the strengths of our university partners.”
These six new diverse projects are being led by world-leading researchers with expertise across a broad range of disciplines including computer science, machine learning, computational linguistics, mathematics, cryptography, international relations, and criminology.
Many of the problems being tackled in these projects have specific relevance not just to the defence and security community, but also to people’s everyday lives. With increasing amounts of sensitive data being available about all of us, and the proliferation of cloud-based computing, advances in defence and security technology are becoming more and more essential to our personal safety and privacy.
Dr Briers adds, “These projects are expected to yield academic impact through publications, and real-world impact through software, which will be released for use and further development.”
The following are short summaries of the individual projects’ focuses, but for more detail please visit each project’s dedicated page.
Understanding online hacking forums
Using natural language processing to understand online hacker communities and predict which members are likely to commit cybercrime.
Adversarial machine learning
Studying how systems trained with machine learning can be affected by manipulated data, such as faked biometrics and hidden malware.
Evaluating homomorphic encryption
Exploring different ways of encrypting sensitive data that can allow for secure, outsourced computation in the cloud.
Computational modelling of civil wars
Simulating and modelling civil conflicts in a data-driven way, to understand the dynamics of these events.
Scalable topological data analysis
Developing software that enables meaningful conclusions to be drawn from the shape of massive, noisy, and potentially incomplete datasets.
Mean field games for cyber security
Implementing models of strategic decision-making in very large populations of small, randomly interacting agents, to analyse cyber-security threats such as botnets.