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Proceedings Paper

Recognition of coordinated adversarial behaviors from multi-source information
Author(s): Georgiy M. Levchuk; Djuana Lea; Krishna R. Pattipati
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Paper Abstract

To successfully predict the actions of an adversary and develop effective counteractions, knowledge of the enemy's mission and organization are needed. In this paper, we present new models and algorithms to identify behaviors of adversaries based on probabilistic inference of two main signatures of behavior: plans (what the enemy wants to do) and organizations (how the enemy is organized and who is responsible for what). The technology allows extraction, classification, and temporal tracking of behavior signatures using multi-source data, as well as prescribes intelligence collection plans to reduce the ambiguity in current predictions.

Paper Details

Date Published: 16 April 2008
PDF: 16 pages
Proc. SPIE 6943, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense VII, 694305 (16 April 2008); doi: 10.1117/12.777150
Show Author Affiliations
Georgiy M. Levchuk, Aptima, Inc. (United States)
Djuana Lea, Air Force Research Lab. (United States)
Krishna R. Pattipati, Univ. of Connecticut (United States)


Published in SPIE Proceedings Vol. 6943:
Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense VII
Edward M. Carapezza, Editor(s)

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