Abstract
Covert networks are nearly impossible to fully describe due to inherent difficulties in obtaining data. To have complete information on a covert network, it is necessary to simulate such data. The simulation presented in this paper dynamically builds a covert network off of an existing network structure. Through parameter tuning, the user is able to generate a wide variety of networks which mimic real world covert networks. Due to the dynamic nature of the simulation, changes in network structure can be analyzed over time. Additionally, network response to intervention, such as the killing of members, can be modeled and compared with real world findings. As the simulation can generate a wide variety of networks, its use can help with testing intervention strategies in different situations.
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O’Neil, P. (2012). Dynamic, Covert Network Simulation. In: Yang, S.J., Greenberg, A.M., Endsley, M. (eds) Social Computing, Behavioral - Cultural Modeling and Prediction. SBP 2012. Lecture Notes in Computer Science, vol 7227. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29047-3_29
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DOI: https://doi.org/10.1007/978-3-642-29047-3_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29046-6
Online ISBN: 978-3-642-29047-3
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