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Alan Turing Institute. MOD & others to tackle challenges from cyber security to civil conflict

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Alan Turing Institute. MOD & others to tackle challenges from cyber security to civil conflict

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"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."

The individual projects focus on:

  • Understanding online hacking forums – Using natural language processing to understand online hacker communities and predict which members are likely to commit cyber crime.
  • 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

Added: 3rd March 2018


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