Rapid Identification of Asymmetric Threat Networks from Large Amounts of Unstructured Data
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AbstractThe asymmetric adversary the U.S. faces today and in the foreseeable future is radically different from previous adversaries and must be thought of in an entirely new light. As events in Afghanistan and Iraq illustrate, warfare is being transformed from a closed, state-sponsored affair to one in which adversaries operating in small, agile, and distributed cells can declare war on nations. Gathering, translating, and analyzing intelligence on these adversaries has proven difficult due to their use of unstructured open source information, which has exponentially increased the burden on intelligence analysts. Securboration, teaming with Dr. Yaneer Bar-Yam from the New England Complex Systems Institute (NECSI), proposes an innovative solution, referred to as Open Source Monitoring System, or OSMOSYS. OSMOSYS leverages Securboration’s powerful semantic modeling techniques to effectively normalize OSINT input streams and uses a technique patented by Dr. Yaneer Bar-Yam that subdivides neural networks in a manner similar to physiological systems. The result is a system that generates warnings and actionable intelligence from OSINT that allows friendly forces to operate inside the observe-orient-decide-act, or OODA, loop of asymmetric and irregular foes thus depriving them of the initiative and forcing them into reactive modes.
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