Although not the standard article, M. Elisabeth Pat-Cornell and David M. Blum’s ongoing research into the use of Bayesian analysis in intelligence problems is extremely relevant to the current subject matter. Their work builds on previous and ongoing research conducted by the National Center for Risk and Economic Analysis of Terrorism Events (CREATE).
According to the article, one of the main problems facing US national and homeland security is the response to very-near future threats. While longer term threats allow the time to build reports and plan courses of action, near term threats do not. As a result, analysts need to be able to judge the reliability of the new threat information in the context of all available intelligence in order to both minimize risk as well as responses to false threats. Researchers at CREATE have previously determined that Bayesian analysis is useful in such situations, as a way to gauge the credibility of potential threat scenarios. Furthermore, Bayesian analysis has been used in conjunction with various other analytical approaches, including probabilistic risk analysis, game theory, and Markov models.
1) the idea of the prior in intelligence has not been well defined;
2) academic research tends to assume a substantial amount of pre-processing by analysts to produce intelligence reports from raw intelligence feeds;
3) many Bayesian tools evaluate only a single hypothesis, ignoring multiple strategic interests;
4) crises imply a short but moving time horizon, which current models lack;
5) the process through which new intelligence data relating to a threat updates the prior belief about the threat has been considered trivial.
Another research project on a similar topic is Bayesian Approach to Intelligence Analysis: (http://create.usc.edu/2011/03/bayesian_approach_to_intellige.html)