Predictive analysis of concealed social network activities based on communication technology choices: early-warning detection of attack signals from terrorist organizations

Katya Drozdova () and Michael Samoilov ()
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Katya Drozdova: Hoover Institution, and NSI
Michael Samoilov: University of California

Computational and Mathematical Organization Theory, 2010, vol. 16, issue 1, No 3, 88 pages

Abstract: Abstract Terrorist threat prevention and counteraction require timely detection of hostile plans. However, adversary efforts at concealment and other challenges involved in monitoring terrorist organizations may impede timely intelligence acquisition or interpretation. This study develops an approach to analyzing technological means rather than content of communications produced within the social networks comprising covert organizations, and shows how it can be applied towards detecting terrorist attack precursors. We find that differential usage patterns of hi-tech versus low-tech communication solutions could reveal significant information about organizational activities, which may be further used to detect signals of impending terrorist attacks. (Such potential practical utility of our method is supported by the detailed empirical analysis of available al Qaeda communications.) The described approach thus provides a common framework for utilizing diverse activity records from heterogeneous sources as well as contributes new tools for their rapid analysis aimed at better informing operational and policy decision-making.

Keywords: Organization; Social network; Fault-intolerant network organization (FINO); Terrorist; Clandestine; Covert; Communications; Technology; Hi-tech; Low-tech; Traceability; Modeling; Predictive signals; Quantitative analysis; Intelligence; Indicators and warnings; Counterterrorism; National security; International security (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10588-009-9058-2

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