Combating Terrorism Insurgency Resolution Software: A Research Note

  • Joshua Sinai
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3975)


This is a research note to propose the development of a combating terrorism (CbT) insurgency resolution software that would operationalize and visualize all the processes involved in resolving terrorist-type insurgencies, including metrics for measures of success. Such a computerized CbT application is not currently available in the non-governmental, open source community, so this research note is intended to stimulate the development of such a prototype through collaboration between combating terrorism subject matter experts and software developers. When it is finally developed, the CbT software is intended to guide a user to formulate coordinated and integrated response strategies and tactics, whether at the governmental or analytical levels, to resolve a hypothetical or actual terrorist insurgency using a spectrum of possible responses. Of particular relevance to contemporary CbT concerns, the software program would also have the capability to respond to the spectrum of terrorist warfare, ranging from “conventional” low impact to “unconventional” high impact chemical, biological, radiological, and nuclear (CBRN) terrorist tactics and weaponry.

Once developed as an operating system, the tool’s objective is to enable the user—whether in government, law enforcement, intelligence, the military, or the public policy/academic communities—to use it either as an educational and training or operational application in which structured argumentation is used to formulate all the steps and processes involved in planning and executing a CbT campaign, as well as assessing the effectiveness of previous or on-going CbT campaigns in order to draw lessons and applications for future CbT responses.


Terrorist Group Structure Argumentation Peace Accord Target Society Open Source Community 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Joshua Sinai
    • 1
  1. 1.Logos Technologies 

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