Midway Revisited: Detecting Deception by Analysis of Competing
Hypothesis
July 2004
Frank J. Stech, The MITRE Corporation
Christopher Elsässer, The MITRE Corporation
ABSTRACT
Historical accounts of military deception abound, but there are few historical
accounts of counter-deception, and fewer operational theories. This paper
describes a business process and semi-automated tools for detecting deception.
Our prototype counter-deception business process starts with hypothesis
generation. For tactical situations, this consists of automated course of action
generation. Strategic situations rely on elicitation from analysts. Next, a Bayesian
belief network is generated. This is followed by sensitivity analysis based on
Bayesian classification. The result is a weighted list of possible observations that:
(1) identify distinguishing evidence that a deceiver must hide and a counterdeceiver
must uncover, (2) isolate local deception in intelligence reporting and
sensing from global deception, and (3) identify circumstances when it might be
fruitful to entertain additional hypotheses. We illustrate this model by describing
how it could have been used by the Japanese Navy before the Battle of Midway to
detect the American denial and deception tactics that allowed the U.S. Pacific
Fleet aircraft carriers to ambush and sink four Japanese carriers.
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