In this presentation we overview a methodology for dynamic security risk quantification and optimal resource allocation of security assets for high profile venues. This methodology is especially applicable to venues that require security screening operations such as mass transit (e.g., train or airport terminals), critical infrastructure protection (e.g., government buildings), and largescale public events (e.g., concerts or professional sports). The method starts by decomposing the three core components of risk -- threat, vulnerability, and consequence -- into their various subcomponents. For instance, vulnerability can be decomposed into availability, accessibility, organic security, and target hardness and each of these can be evaluated against the potential threats of interest for the given venue. Once evaluated, these subcomponents are rolled back up to compute the specific value for the vulnerability core risk component. Likewise, the same is done for consequence and threat, and then risk is computed as the product of these three components. A key aspect of our methodology is dynamically quantifying risk. That is, we incorporate the ability to uniquely allow the subcomponents and core components, and in turn, risk, to be quantified as a continuous function of time throughout the day, week, month, or year as appropriate.
The next step in our methodology is to assess the effectiveness of the different security assets, which may also include a deterrence factor, that can be used to counter the threats against the given venue. Typically, security assets are a constrained resource, so the challenge is how to best deploy them to minimize risk over time. Our approach is to formulate the problem as a mathematical program which is concerned with optimizing the allocation of limited resources between competing activities while simultaneously satisfying all constraints associated with the problem. Once formulated, this mathematical program can be solved by traditional methods to yield the best allocation of the constrained resources that minimize the overall venue risk. Additional solution algorithms can also be invoked to help keep to the problem tractable when the number of variables involved becomes large.