Organised crime is one of the greatest threats to the UK’s national security. The role of the National Crime Agency (NCA) is to protect the public by disrupting and bringing to justice those serious and organised criminals who present the highest risk to the UK. The NCA is focused on countering child sexual exploitation, modern slavery, illegal firearms, cyber crime and money laundering: put simply, all organised crime other than terrorism. This project has been co-defined with and will be co-supervised by the NCA.
NCA officers do exist in each of the NCA’s areas of focus that are adept at identifying hallmarks of specific illegal activities. However, the volumes of data is growing exponentially. There is therefore a need to work with these experts to automate the processing of the data, learn what these hallmarks are and then search the data for instances worthy of further human analysis. The need is growing for such data-driven intelligence.
This data-driven prioritisation of human effort has been the subject of ongoing collaboration between the NCA and the University of Liverpool in the context of countering Child Sexual Exploitation. In this context, the primary challenge is that there are far too many criminals to arrest them all. It is therefore of paramount importance to arrest those who present the greatest threat to the public. That work has made apparent that it is important that the algorithms need to be scalable, accurate and transparent. Current work is therefore focused on the use of a distributed implementation of a Sequential Monte Carlo (SMC) sampler, an algorithm that can be configured to meet these three desiderata. Alternative algorithms, e.g., Deep Learning, logistic regression or random forests, cannot do so. The aim is therefore to dramatically outperform such existing algorithms.
The focus of this studentship will be on tailoring the SMC sampler to be well suited to the data pertinent to some of the NCA’s other priorities. The specific priorities are to be agreed, but in all cases, collaboration with the NCA will focus on access to data and experts as well as the integration of algorithms into the NCA’s systems.
Given the nature of the data and applications involved, to be eligible, applicants must be able and willing to undergo the vetting procedures necessary to work at NCA premises.
This project is part of the EPSRC Funded CDT in Distributed Algorithms: The What, How and where of Next-Generation Data Science. https://www.liverpool.ac.uk/research/research-themes/digital/cdt-distributed-algorithms/
The University of Liverpool is working in partnership with the STFC Hartree Centre and other industrial partners from the manufacturing, defence and security sectors to provide a 4 year innovative PhD training course that will equip over 60 students with the essential skills needed to become future leaders in data science, be it in academia or industry.
Every project within the centre is offered in collaboration with an Industrial partner who as well as providing co-supervision will also offer the unique opportunity for students to access state of the art computing platforms, work on real world problems, benchmarking and data. Our graduates will gain unparalleled experiences working across academic disciplines in highly sought-after topic areas, answering industry need.
As well as learning from academic and industrial world leaders, the centre has a dedicated programme of interdisciplinary research training including the opportunity to undertake modules at the global pinnacle of Data science teaching. A large number of events and training sessions are undertaken as a cohort of PhD students, allowing you to build personal and professional relationships that we hope will lead to research collaboration either now or in your future.
The learning nurtured at this centre will be based upon anticipation of the hardware recourses arriving on desks of students after they graduate, rather than the hardware available today.