In order to address the threat to knowledge that deception poses, intelligence analysts (e.g., Whaley 1982 and Bell 2003) and cybersecurity experts (e.g., Rowe and Rrushi 2016) have identified various techniques that deceivers use, techniques such as masking, dazzling, mimicking, and decoying.  Epistemology (i.e., the study of knowledge) should be able to answer two questions about these techniques.  First, what intended epistemic effect do they have in common such that they all count as deception?  Second, how do their intended epistemic effects differ such that they count as distinct forms of deception?  Philosophers Roderick Chisholm and Thomas Feehan (1977) proposed an influential scheme for classifying types of deception in terms of their intended epistemic effects.  In this talk, Dr. Fallis argues that their scheme is too course-grained to distinguish between the different forms of deception, because it utilizes a simple categorical belief model of cognitive states. Fallis will show how Bayesian epistemology, which represents cognitive states in terms of credences, can be used to understand what unifies and what distinguishes the various deception techniques that intelligence analysts and cybersecurity experts have identified.  Thus, it puts us in a better position to detect (and/or deploy) these techniques.