Nuclear weapons proliferation produces a vehement global safety and security
concern. Perhaps most threatening is the scenario of a rogue nation or a terrorist
organization acquiring nuclear weapons where the conventional ideas of nuclear
deterrence may not apply. To combat this threat, innovative tools are needed that will
help to improve understanding of the pathways an organization will take in attempting to
obtain nuclear weapons and in predicting those pathways based on existing evidence. In
this work, a methodology was developed for predicting these pathways. This
methodology uses a Bayesian network. An organization’s motivations and key
resources are evaluated to produce the prior probability distributions for various
pathways. These probability distributions are updated as evidence is added. The
methodology is implemented through the use of the commercially available Bayesian
network software package, Netica.
A few simple scenarios are considered to show that the model’s predictions agree
with intuition. These scenarios are also used to explore the model’s strengths and
limitations. The model provides a means to measure the relative threat that an organization poses to nuclear proliferation and can identify potential pathways that an
organization will likely pursue. Thus, the model can serve to facilitate preventative
efforts in nuclear proliferation. The model shows that an organization’s motivations
biased the various pathways more than their resources; however, resources had a greater
impact on an organization’s overall chance of success. Limitations of this model are that
(1) it can not account for deception, (2) it can not account for parallel weapon programs,
and (3) the accuracy of the output can only be as good as the user input. This work
developed the first, published, quantitative methodology for predicting nuclear
proliferation with consideration for how an organization’s motivations impact their
pathway probabilities.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-3023 |
| Date | 15 May 2009 |
| Creators | Freeman, Corey Ross |
| Contributors | Charlton, William S. |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Thesis, text |
| Format | electronic, application/pdf, born digital |
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