  Activities of terrorist groups present a serious threat to the security and
well-being of the general public. Counterterrorism authorities aim to identify
and frustrate the plans of terrorist groups before they are put into action.
Whilst the activities of terrorist groups are likely to be hidden and
disguised, the members of such groups need to communicate and coordinate to
organise their activities. Such observable behaviour and communications data
can be utilised by the authorities to estimate the threat posed by a terrorist
group. However, to be credible, any such statistical model needs to fold in the
level of threat posed by each member of the group. Unlike in other benign forms
of social networks, considering the members of terrorist groups as exchangeable
gives an incomplete picture of the combined capacity of the group to do harm.
Here we develop a Bayesian integrating decision support system that can bring
together information relating to each of the members of a terrorist group as
well as the combined activities of the group.
