Deception Detection by Analysis of Competing Hypotheses

MITRE Sponsored Research by Frank Stech & Chris Elsaesser.

Abstract: We outline a business process to assist intelligence analysts detect deception. We describe how deceptions exploit cognitive limits and biases and review prior work on processes that can help people recognize organized deceptions. Our process is based on Heuer’s Analysis of Competing Hypotheses, which we automate by generating state-based plans and converting them to Bayesian belief networks. Our process uses a concept from Bayesian classification to identify distinguishing evidence that a deceiver must hide and a counter-deceiver must uncover. White paper

Fooled Again? Developing Counter-deception Decision Support