Towards a Unified Bayesian Model for Cyber Security

  • Mark Briers | The Alan Turing Institute

With the realisation that Cyber attacks present a significant risk to an organisation’s reputation, efficiency, and profitability, there has been an increase in the instrumentation of networks; from collecting netflow data at routers, to host-based agents collecting detailed process information. To spot the potential threats within a Cyber environment, a large community of researchers have produced many exciting innovations, aligned with such data. Much of this research has been focused around “data driven” techniques, and does not often fuse data from multiple sources. Moreover, incorporation of threat actors’ behaviours and motivations (as specified by Cyber security experts) is often non-existent. In this talk, I will present an initial unified Bayesian model for Cyber security, which allows explicit incorporation of expert knowledge, and provides a natural probabilistic framework for the fusion of multiple data sources.

Speaker Details
Programme Director, Mark Briers
Mark Briers is the Programme Director for security at The Alan Turing Institute, the UK’s national centre for data science and artificial intelligence. He has worked in the defence sector for over 16 years, directing research programmes in the area of statistical data analysis. He completed his PhD in 2007 at Cambridge University where he developed Sequential Monte Carlo based techniques for state-space filtering and smoothing. He is an Honorary Senior Lecturer at Imperial College London, and an elected member of Council at the Royal Statistical Society. His current research interests include scalable Bayesian inference, sequential inference, and anomaly detection, applied in a cyber security context.

Series: Microsoft Research Talks