Midway Revisited: Detecting Deception by Analysis of Competing Hypothesis

摘要

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. The counter-deception business process begins with hypothesis generation. This consists of automated course of action generation in tactical situations; strategic situations require hypothesis elicitation from analysts. Next, hypotheses and related potential evidence are represented by a Bayesian belief network. This network is the basis of a diagnostic analysis derived from classification theory. The result is a weighted list of possible observations that: (1) identify distinguishing evidence that a deceiver must hide and a counter-deceiver 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 process 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.