k-Fragility Maximization Problem to Attack Robust Terrorist Networks

This paper investigates the shaping operation problem introduced by Callahan et al., namely the k-fragility maximization problem (k-FMP), whose goal is to find a subset of personals within a terrorist group such that the regeneration capability of the residual group without the personals is minimized. To improve the impact of the shaping operation, the degree centrality of the residual graph needs to be maximized. In this paper, we propose a new greedy algorithm for k-FMP. We discover some interesting discrete properties and use this to design a more thorough greedy algorithm for k-FMP. Our simulation result shows that the proposed algorithm outperforms Callahan et al.'s algorithm in terms of maximizing degree centrality. While our algorithm incurs higher running time (factor of k), given that the applications of the problem is expected to allow sufficient amount of time for thorough computation and k is expected to be much smaller than the size of input graph in reality, our algorithm has a better merit in practice.