I am Professor of Data Science & Cybersecurity at Cardiff University. I am Director of Cardiff’s NCSC/EPSRC Academic Centre of Excellence in Cyber Security Research (ACE-CSR). I am also leading AI for cybersecurity research at Airbus DTO on a part-time secondment basis.

I have been involved in grants in worth in excess of £14m, leading large awards from EPSRC, ESRC and industry on the topic of cyber security analytics – the fusion of AI, Cybersecurity and Risk.

I am co-director of the WEFO-funded Data Innovation Accelerator (DIA) – a £3.75m investment in upskilling SMEs in South Wales to develop innovative AI-driven products and services.

My research outcomes, which include ~ 80 academic peer-reviewed articles – stemming from funded research projects worth over £14 million, are organised and disseminated via two research units:

The Airbus Centre of Excellence in Cyber Security Analytics, within which I am the director. The centre works across industry, academia and government to provide a focus for cyber security analytics in the UK. Cyber security is a priority research area at Cardiff University, supported with strategic investment. Since 2012 we have established an interdisciplinary research team of technical and social researchers. Our collaborative projects have received more than £5m in funding from UK Research Councils (EPSRC, ESRC), Welsh Government (Endeavr Wales) and Industry (Airbus).

The Social Data Science Lab, within which I am a director and the computational lead. The Lab’s core funding comes from a £450k ESRC grant and it forms part of the £64m ‘Big Data Network’. Core funding runs between 2017 and 2020, during which time the Lab will host 3 post-doctoral researchers and 9 PhD students, all studying topics related to Risk, Safety & Human/Cybersecurity.

Current Research:

– measuring risk to cyber security using applied machine learning for network security and anomaly detection.

– risk to human security from online social networks. Text classification & statistical modelling spread of cyber hate, social tension and disruptive language on Twitter.

– identifying offline disruptive events (e.g crime, protests) using online opinion mining and topic detection.

ACM Keywords: Security and Protection; Data mining; Machine learning; Human-centered computing; Modeling structured, textual and multimedia data.