Deception and Counter-Deception Decision Support using Bayesian Networks

Quek Mei Xian

Abstract

Deception plays a critical role in military mission success. It can be used in both defense and attack operations. Detecting deception is difficult because deception is usually driven by hidden intentions. Therefore, in order to detect deception, these hidden intentions must be captured for analysis by the model. This thesis discusses a possible deception detection method to defend against military threats, as well as techniques for planning and executing deception during attacks. Various information theories are examined and implemented within the model. The detection method primarily uses correlation between the various sensors to identify any inconsistency, since inconsistency is usually an indicator of deception. With the knowledge to detect deception, the thesis then proposes techniques to plan and execute deception for military attacks. The deception attacking method aims to achieve minimum inconsistency while hiding the intent.