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Human reliability-based MC&A models for detecting insider theft

Duran, Felicia A.; Wyss, Gregory D.

Material control and accounting (MC&A) safeguards operations that track and account for critical assets at nuclear facilities provide a key protection approach for defeating insider adversaries. These activities, however, have been difficult to characterize in ways that are compatible with the probabilistic path analysis methods that are used to systematically evaluate the effectiveness of a site's physical protection (security) system (PPS). MC&A activities have many similar characteristics to operator procedures performed in a nuclear power plant (NPP) to check for anomalous conditions. This work applies human reliability analysis (HRA) methods and models for human performance of NPP operations to develop detection probabilities for MC&A activities. This has enabled the development of an extended probabilistic path analysis methodology in which MC&A protections can be combined with traditional sensor data in the calculation of PPS effectiveness. The extended path analysis methodology provides an integrated evaluation of a safeguards and security system that addresses its effectiveness for attacks by both outside and inside adversaries.

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TYPE Conference YEAR 2010
OSTI

A total risk assessment methodology for security assessment

Wyss, Gregory D.; Otero, Consuelo J.; Pless, Daniel J.; Rhea, Ronald E.; Kaplan, Paul G.

Sandia National Laboratories performed a two-year Laboratory Directed Research and Development project to develop a new collaborative risk assessment method to enable decision makers to fully consider the interrelationships between threat, vulnerability, and consequence. A five-step Total Risk Assessment Methodology was developed to enable interdisciplinary collaborative risk assessment by experts from these disciplines. The objective of this process is promote effective risk management by enabling analysts to identify scenarios that are simultaneously achievable by an adversary, desirable to the adversary, and of concern to the system owner or to society. The basic steps are risk identification, collaborative scenario refinement and evaluation, scenario cohort identification and risk ranking, threat chain mitigation analysis, and residual risk assessment. The method is highly iterative, especially with regard to scenario refinement and evaluation. The Total Risk Assessment Methodology includes objective consideration of relative attack likelihood instead of subjective expert judgment. The 'probability of attack' is not computed, but the relative likelihood for each scenario is assessed through identifying and analyzing scenario cohort groups, which are groups of scenarios with comparable qualities to the scenario being analyzed at both this and other targets. Scenarios for the target under consideration and other targets are placed into cohort groups under an established ranking process that reflects the following three factors: known targeting, achievable consequences, and the resources required for an adversary to have a high likelihood of success. The development of these target cohort groups implements, mathematically, the idea that adversaries are actively choosing among possible attack scenarios and avoiding scenarios that would be significantly suboptimal to their objectives. An adversary who can choose among only a few comparable targets and scenarios (a small comparable target cohort group) is more likely to choose to attack the specific target under analysis because he perceives it to be a relatively unique attack opportunity. The opposite is also true. Thus, total risk is related to the number of targets that exist in each scenario cohort group. This paper describes the Total Risk Assessment Methodology and illustrates it through an example.

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TYPE Conference YEAR 2009
OSTI
Results 51–75 of 84
Results 51–75 of 84