Safeguards and security (S&S) systems for nuclear facilities include material control and accounting (MC&A) and a physical protection system (PPS) to protect nuclear materials from theft, sabotage and other malevolent human acts. The PPS for a facility is evaluated using probabilistic analysis of adversary paths on the basis of detection, delay, and response timelines to determine timely detection. The path analysis methodology focuses on systematic, quantitative evaluation of the physical protection component for potential external threats, and often calculates the probability that the PPS is effective (PE) in defeating an adversary who uses that attack path. By monitoring and tracking critical materials, MC&A activities provide additional protection against inside adversaries, but have been difficult to characterize in ways that are compatible with the existing path analysis methods that are used to systematically evaluate the effectiveness of a site’s protection system. This research describes and demonstrates a new method to incorporate MC&A protection elements explicitly within the existing probabilistic path analysis methodology. MC&A activities, from monitoring to inventory measurements, provide many, often recurring opportunities to determine the status of critical items, including detection of missing materials. Human reliability analysis methods are applied to determine human error probabilities to characterize the detection capabilities of MC&A activities. An object-based state machine paradigm was developed to characterize the path elements and timing of an insider theft scenario as a race against MC&A activities that can move a facility from a normal state to a heightened alert state having additional detection opportunities. This paradigm is coupled with nuclear power plant probabilistic risk assessment techniques to incorporate the evaluation of MC&A activities in the existing path analysis methodology. Event sequence diagrams describe insider paths through the PPS and also incorporate MC&A activities as path elements. This work establishes a probabilistic basis for incorporating MC&A activities explicitly within the existing path analysis methodology to extend it to address insider threats. The analysis results for this new method provide an integrated effectiveness measure for a safeguards and security system that addresses threats from both outside and inside adversaries. / text
| Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/ETD-UT-2010-12-2223 |
| Date | 09 February 2011 |
| Creators | Durán, Felicia Angélica |
| Source Sets | University of Texas |
| Language | English |
| Detected Language | English |
| Type | thesis |
| Format | application/pdf |
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