Math models will disrupt, detect terror networks: Study

A mathematical model can disrupt flow of information in a terrorist organization using minimal resources, a new research has revealed.

The Society of Industrial and Applied Mathematics (SIAM) has published a paper in the journal where authors Anthony Bonato, Dieter Mitsche, and Pawel Pralat say that the structure of terror networks can be compared to hierarchical organization in companies and certain online social networks where information flows in one direction from a source to the consumers and are known as hierarchical social networks or directed acyclic graphs (DAGs).

In a terrorist network, the leaders forward plans down to the foot soldiers where usually only one messenger receives the message for the plan to be executed. Disruption of such flow of information will intercept messages in a terror network.

The authors proposed a generalized stochastic model for the flow and disruption of information, based on a two-player outdoor game called 'Seepage', where players depicting agents attempt to block the movement of another player, an intruder, from a source node to a sink. The intruder pits against the greens, who form a directed acyclic graph, with one source (the top of the volcano) and many sinks representing the lake. 'Seepage' represents the amount of contamination and the 'green number' relates to the number of agents required to halt it.

Pralat vouched for special kinds of DAGs which can be used to model the disruption of terrorist cells. Partially ordered sets (a special kind of DAG) are often used in mathematics to analyze ordering, sequencing or arrangement of distinct objects which can block all routes from the maximal to the minimal nodes by killing a subset of agents in a terror network.

Pralat explained that the authors considered two extreme profiles, one is where every agent has about the same number of connections and the second profile is power law, where only some agents have many connections. Power law DAGs will have many more low-degree nodes and a few with high degrees as compared to regular DAGs where each level will have nodes with about the same out-degree (number of outgoing edges emanating from a node).

The authors have discovered that Seepage is a more realistic model of counterterrorism, as the agents do not necessarily act all at once, but over time.