> *Dissertation Defense Announcement > To: The George Mason University Community* > > *Candidate: David L. Bolduc > Program: PhD Biodefense > * > *Date: Tuesday April 26, 2011 > Time: 1:30 p.m. > Place: George Mason University > ** Research I Bldg., Room 161 > Fairfax campus <http://www.gmu.edu/resources/visitors/findex.html> > > Dissertation Chair: Dr. Robert L. Dudley > Committee members: Dr. Charles L. Bailey, Dr. Joseph A. Marr* > *Title: "Development of an Algorithm for Predicting /'Relative Risk'/ > of Terrorist-CBRN" > * > The dissertation is on reserve in the Johnson Center Library, Fairfax campus. > The doctoral project will not be read at the meeting, but should be read in advance. > /**/All members of the George Mason University community are invited to attend. > > > *ABSTRACT: > *In the past decade there has been a tremendous rise in the number of extremist groups with radical goals. To achieve their objectives, some of these groups > are resorting to terrorist tactics. With the rapid expansion of scientific technology brought on through increasing globalization, the prospect of incorporating the > use of chemical, biological, radiological and nuclear (CBRN) weapons into their tactics is becoming increasingly feasible and likely. As these radical groups > become more energized, they may resort to using CBRN. In order to avert a disaster from a terrorist-CBRN (T-CBRN) event, it is important to study > the likelihood of these groups employing CBRN. Analysts continue to search for sound methodologies in assessing the risk of such groups pursuing CBRN. > Psychological and mathematical modeling attempts have been made in discerning terrorist's propensities for CBRN Asal (2010), Sullivan and Perry (2004), > Post (2002), Tucker (2000) etc., but there still remains considerable gaps in these areas. > > > > > Because of the deficiencies in analytical methodologies and > controversial techniques used for modeling T-CBRN, we proposed the > questions: can a more accurate predictive model of T-CBRN use be > developed? And, when compared against past event data, would such a > model reliably predict the amount of "/Relative Risk/" of a terrorist > that would elect to use CBRN? > > > > This study entailed the development of an algorithm linked with > statistical software (ProStat Version 5.5, Poly Software > International) for predicting the Relative Risk of a terrorist seeking > CBRN. This was achieved through four phases. Phase I involved > searching open literature and proposing independent-variables > associated with T-CBRN. Phase II entailed the construction of a > "/Random-Nations Matrix/" representing the T-CBRN universe. This > matrix was then used for correlating variables suspected of being > associated with T-CBRN. Phase III involved the construction of a > multivariate model from the variables which met our correlation > criteria with T-CBRN. The final phase, Phase IV, entailed the > construction of an algorithm derived from the model design, for > predicting the amount of Relative Risk of a terrorist seeking, > acquiring and or using CBRN, and the Relative Risk of T-CBRN occurring > in a specific country. Probability was measured by the strength of > the relationship indicated by the p-value. > > > > The study drew primarily from the following databases: the Memorial > Institute for the Prevention of Terrorism (2007), the U.S. Department > of State (2010), Globalsecurity.org (2010), the Global Terrorism > Database (2010), the Central Intelligence Agency World Fact Book > (2009-2010), the James Martin Center for Nonproliferation > Studies/Monterey WMD Terrorism Database (2010), the Center for Defense > Information (2009), the Freedom House Center for Systemic Peace (2009) > and the McDonald's Corporation's list of worldwide McDonald's > restaurants (2010). > > > > A Random Nations Matrix was developed for determining the two > independent-variables that correlated with our dependent-variable > "/Terrorist-CBRN/". This matrix was constructed from the random > selection of 74 countries and/or locations from the CIA World Fact > Book (2009-2010). Thirty-nine of the same variables were measured for > each of the seventy-four selected countries or locations compiled in > the matrix. The 39 variables selected for each country or location, > were correlated with each other and the T-CBRN variable for > determining correlative significance. A multivariate-model was > developed with 67.3 percent predictive power for T-CBRN using the > independent-variables: "/Political Violence Per Capita/" and "/Number > of Terrorist-CBRN Technical Experts/". Average lag-times between > terrorist's interest and use of CBRN were also calculated for the > various classifications of terrorist-groups. > >