A concept for characterizing, predicting and recognizing threat situations is developed. The goal is to establish a systematic approach to automating some of these functions. The proposed approach addresses the fundamental problems of (a) sparse and ambiguous indicators of potential or actualized threat activity buried in massive background data; and (b) uncertainty in threat capabilities, intent and opportunities. Attack hypotheses are adaptively generated, evaluated and refined as the understanding of the situation evolves. This effort builds upon advances in Situation, Ontology and Estimation theory. Specific features of the approach include (a) fuzzy definition of situations and relationships; (b) integration of diverse inference bases: logical/semantic, causal, conventional, etc.; and (c) context-conditioned reasoning with uncertain evidence formulated in terms of “probabilistic infons.”


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    An Approach to Threat Assessment

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