| Summary: | The <b>early intervention</b> of law enforcement authorities to <b>prevent</b> an impending terrorist attack is of utmost importance to ensuring <b>economic</b>, <b>financial</b>, and <b>social stability</b>. From our previously published research, the key individuals who play a vital role in terrorist organizations can be <b>timely revealed</b>. The problem now is to identify which <b>attack strategy</b> (<b>node removal</b>) is the most damaging to terrorist networks, making them <b>fragmented</b> and therefore, <b>unable to operate under real-world conditions</b>. We examine several <b>attack strategies</b> on <b>4 real terrorist networks</b>. Each node removal strategy is based on: (i) randomness (random node removal), (ii) high strength centrality, (iii) high betweenness centrality, (iv) high clustering coefficient centrality, (v) high <b>recalculated</b> strength centrality, (vi) high <b>recalculated</b> betweenness centrality, (vii) high <b>recalculated</b> clustering coefficient centrality. The damage of each attack strategy is evaluated in terms of <b>Interoperability</b>, which is defined based on the <b>size</b> of the <b>giant component</b>. We also examine a <b>greedy algorithm</b>, which removes the node corresponding to the maximal decrease of Interoperability at each step. Our analysis revealed that removing nodes based on high <b>recalculated</b> betweenness centrality is <b>the most harmful</b>. In this way, the Interoperability of the communication network drops dramatically, even if <b>only two</b> nodes are removed. This valuable insight can help law enforcement authorities in developing more effective <b>intervention strategies</b> for the <b>early prevention</b> of impending terrorist attacks. Results were obtained based on real data on <b>social ties</b> between terrorists (<b>physical face-to-face social interactions</b>).
|
|---|