"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."
Statistics Data Literacy
söndag 30 september 2018
Statistics in cyber-security
Dr Nick Heard, Imperial College London - Artificial Intelligence Videos
"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."
"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."
