Detecting Threats in Temporal Networks

Crime in the modern world is characterised by large networks of criminals operating
across national borders and transacting via multiple communication channels.
These networks are both evolving temporally (as the relationship between
individuals changes) and are multi-layered (for example, communications, goods,
money), making analysis complex. In addition these networks are characterised by
a sparse structure, often with key players only loosely connected to the main
network in order to reduce the likelihood of detection.
Patterns of communication within the network over time can expose the different
types of activity by members. It is also possible to identify when individuals are
becoming isolated, which may indicate they are in danger. There is a need to
rapidly identify threats to life.
The aim of the project is to better understand how and when changes in patterns of
communication within the network can be indicative of threats to life or imminent
major criminal operation.
To do this we will develop techniques to identify unusual activity in the network.
These include temporal changes in key elements of the network structure such as
communities and the relationship between individual nodes and the community
compared to the normal rate of change (evolution) in the network. Because these
networks are fundamentally complex, achieving these goals will extend current
network science.