Human reliability-based MC&A models for detecting insider theft.
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.
- Research Organization:
- Sandia National Laboratories
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 1020366
- Report Number(s):
- SAND2010-3770C
- Country of Publication:
- United States
- Language:
- English
Similar Records
Evaluating the contributions of material control to insider protection
The SO-20.3 MC&A modernization plan final report.