Abstract
It is hypothesized that many of the current covert organizations organize according to leaderless principles, see [15]. According to [4] international law enforcement pressure is forcing criminal and terrorist organizations to decentralize their organizational structures, e.g., Mexican law enforcement efforts are causing drug cartels in Mexico to break into smaller units. It is also known that terror organizations exist that are a mix of hierarchical and decentralized structures, i.e., think of Hezbollah and Peru former’s Shining Path (cf. [4]). Clearly this is done to frustrate intelligence agencies that try to disrupt such organizations by taking out key leaders. If the networks are flat rather than hierarchical it becomes very difficult to determine who the leaders are based on network principles alone. The study of covert networks has received high levels of attention from the modeling community in the last decade. Among others, covert networks have been formally characterized by Tsvetovat and Carley[18], McAllister [13] and McCormick and Owen [14], and their optimal network structures have been analyzed and approximated by Lindelauf et al.[9] and Enders and Su [5]. Other approaches concern covert network destabilization strategies, see [6] and [3], and tools to identify the most important members of the corresponding organizations, see [8, 12] and [17].
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Husslage, B., Lindelauf, R., Hamers, H. (2013). Leaderless Covert Networks: A Quantitative Approach. In: Subrahmanian, V. (eds) Handbook of Computational Approaches to Counterterrorism. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-5311-6_13
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