Defense Date

2010

Document Type

Thesis

Degree Name

Master of Science

Department

Mathematical Sciences

First Advisor

Laura McLay

Abstract

One of the most pressing concerns in homeland security is the illegal passing of weapons-grade nuclear material through the borders of the United States. If terrorists can gather the materials needed to construct a nuclear bomb or radiological dispersion device (RDD, i.e., dirty bomb) while inside the United States, the consequences would be devastating. Preventing plutonium, highly enriched uranium (HEU), tritium gas or other materials that can be used to construct a nuclear weapon from illegally entering the United States is an area of vital concern. There are enormous economic consequences when our nation's port security system is compromised. Interdicting nuclear material being smuggled into the United States on cargo containers is an issue of vital national interest, since it is a critical aspect of protecting the United States from nuclear attacks. However, the efforts made to prevent nuclear material from entering the United States via cargo containers have been disjoint, piecemeal, and reactive, not the result of coordinated, systematic planning and analysis. Our economic well-being is intrinsically linked with the success and security of the international trade system. International trade accounts for more than thirty percent of the United States economy (Rooney, 2005). Ninety-five percent of international goods that enter the United States come through one of 361 ports, adding up to more than 11.4 million containers every year (Fritelli, 2005; Rooney, 2005; US DOT, 2007). Port security has emerged as a critically important yet vulnerable component in the homeland security system. Applying game theoretic methods to counterterrorism provides a structured technique for defenders to analyzing the way adversaries will interact under different circumstances and scenarios. This way of thinking is somewhat counterintuitive, but is an extremely useful tool in analyzing potential strategies for defenders. Decision analysis can handle very large and complex problems by integrating multiple perspectives and providing a structured process in evaluating preferences and values from the individuals involved. The process can still ensure that the decision still focuses on achieving the fundamental objectives. In the decision analysis process value tradeoffs are evaluated to review alternatives and attitudes to risk can be quantified to help the decision maker understand what aspects of the problem are not under their control. Most of all decision analysis provides insight that may not have been captured or fully understood if decision analysis was not incorporated into the decision making process. All of these factors make decision analysis essentially to making an informed decision. Game theory and decision analysis both play important roles in counterterrorism efforts. However, they both have their weaknesses. Decision analysis techniques such as probabilistic risk analysis can provide incorrect assessments of risk when modeling intelligent adversaries as uncertain hazards. Game theory analysis also has limitations. For example when analyzing a terrorist or terrorist group using game theory we can only take into consideration one aspect of the problem to optimize at a time. Meaning the analysis is either analyzing the problem from the defenders perspective or from the attacker’s perspective. Parnell et al. (2009) was able to develop a model that simultaneously maximizes the effects of the terrorist and minimizes the consequences for the defender. The question this thesis aims to answer is whether investing in new detector technology for screening cargo containers is a worthwhile investment for protecting our country from a terrorist attack. This thesis introduces an intelligent adversary risk analysis model for determining whether to use new radiological screening technologies at our nation’s ports. This technique provides a more realistic risk assessment of the true situation being modeled and determines whether it is cost effective for our country to invest in new cargo container screening technology. The optimal decision determined by our model is for the United States to invest in a new detector, and for the terrorists to choose agent cobalt-60, shown in Figure 18. This is mainly due to the prominence of false alarms and the high costs associated with screening all of these false alarms, and we assume for every cargo container that sounds an alarm, that container is physically inspected. With the new detector technology the prominence of false alarms decreases and the true alarm rate increases, the cost savings associated with this change in the new technology outweighs the cost of technical success or failure. Since the United States is attempting to minimize their expected cost per container, the optimal choice is to invest in the new detector. Our intelligent adversary risk analysis model can simultaneously determine the best decision for the United States, who is trying to minimize the expected cost, and the terrorist, who is trying to maximize the expected cost to the United States. Simultaneously modeling the decisions of the defender and attacker provides a more accurate picture of reality and could provide important insights to the real situation that may have been missed with other techniques. The model is extremely sensitive to certain inputs and parameters, even though the values are in line with what is available in the literature, it is important to understand the sensitivities. Two inputs that were found to be particularly important are the expected cost for physically inspecting a cargo container, and the cost of implementing the technology needed for the new screening device. Using this model the decision maker can construct more accurate judgments based on the true situation. This increase in accuracy could save lives with the decisions being made. The model can also help the decision maker understand the interdependencies of the model and visually see how his resource allocations affect the optimal decisions of the defender and the attacker.

Rights

© The Author

Is Part Of

VCU University Archives

Is Part Of

VCU Theses and Dissertations

Date of Submission

August 2010

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