Publications

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The performance of many of the technologies used in physical protection systems that guard high-value assets are heavily influenced by weather and visibility conditions as well as intruder capabilities. This complicates the already difficult problem of optimizing the design of multi-layered physical protection systems. This paper develops an optimization model for the automatic design of these systems with explicit consideration of the impact of weather and visibility conditions as well as intruder capabilities on system performance. An illustrative case study is provided.

Despite the known degrading impact of high nuisance and false alarm rates (NAR/FAR) on operator performance, analyses of security systems often ignores operator performance. We developed a model to analyze the impact of nuisance alarm rates on operator performance and on overall system performance. The model demonstrates that current methods that do not account for operator performance produce optimistic estimates of system performance. As shown in our model, even low NAR/FAR levels and the associated alarm queueing effect can increase operator detect and response time, which in turn reduces the amount of time the response force has to interrupt the intruder. An illustrative analysis shows that alarm processing times can be higher than the assessment time due to queue wait times and that systems with only one or two operators can become overwhelmed as NAR increases, decreasing system performance.

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In July 2012, protestors cut through security fences and gained access to the Y-12 National Security Complex. This was believed to be a highly reliable, multi-layered security system. This report documents the results of a Laboratory Directed Research and Development (LDRD) project that created a consistent, robust mathematical framework using complex systems analysis algorithms and techniques to better understand the emergent behavior, vulnerabilities and resiliency of multi-layered security systems subject to budget constraints and competing security priorities. Because there are several dimensions to security system performance and a range of attacks that might occur, the framework is multi-objective for a performance frontier to be estimated. This research explicitly uses probability of intruder interruption given detection (P_I) as the primary resilience metric. We demonstrate the utility of this framework with both notional as well as real-world examples of Physical Protection Systems (PPSs) and validate using a well-established force-on-force simulation tool, Umbra.

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The performance of a multi-layered security system, such as those protecting high-value facilities or critical infrastructures, is characterized using several different attributes including detection and interruption probabilities, costs, and false/nuisance alarm rates. The multitude of technology options, alternative locations and configurations for those technologies, threats to the system, and resource considerations that must be weighed make exhaustive evaluation of all possible architectures extremely difficult. This paper presents an optimization model and a computationally efficient solution procedure to identify an estimated frontier of system configuration options which represent the best design choices for the user when there is uncertainty in the response time of the security force, once an intrusion has been detected. A representative example is described.

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This paper focuses on optimizing the selection and configuration of detection technologies to protect a target of interest. The ability of an intruder to simply reach the target is assumed to be sufficient to consider the security system a failure. To address this problem, we develop a game theoretic model of the strategic interactions between the system owner and a knowledgeable intruder. A decomposition-based exact method is used to solve the resultant model.

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