Data science techniques have an important role to play in the next generation of cyber-security defences. Inside a typical enterprise computer network, a number of high-volume data sources are available which could aid the discovery and prevention of cyber-attacks and network misuse. At Imperial, our interests are in developing statistical, probability model-based techniques for identifying illegitimate network activity using these data sources. This talk will give an overview of some different statistical approaches to analysing cyber data, ranging from micro-level models of activity occurring on individual graph edges up to representations of the full network graph.
Dr Nick Heard (Imperial College London, UK)
Nick Heard is Reader in Statistics in the Department of Mathematics, Imperial College London, and visiting researcher at the Heilbronn Institute for Mathematical Research, in partnership with GCHQ UK. His research interests are in statistical cyber-security, computational Bayesian inference, changepoint detection and meta-analysis.
More information can be found here: https://www.turing.ac.uk/events/statistics-cyber-security