## TSA Uses Monte Carlo Simulations to Weigh Airplane Risks

Does this make sense to anyone?

TSA said Boeing would use its Monte Carlo simulation model “to identify U.S. commercial aviation system vulnerabilities against a wide variety of attack scenarios.”

The Monte Carlo method refers to several ways of using randomly generated numbers fed into a computer simulation many times to estimate the likelihood of an event, specialists in the field say.

The Monte Carlo method plays an important role in many statistical techniques used to characterize risks, such as the probabilistic risk analysis approach used to evaluate possible problems at a nuclear power plant and their consequences.

Boeing engineers have pushed the mathematical usefulness of the Monte Carlo method forward largely by applying the technique to evaluating the risks and consequences of aircraft component failures.

A DHS source said the work of the U.S. Commercial Aviation Partnership, a group of government and industry organizations, had made TSA officials aware of the potential applicability of the Monte Carlo method to building an RMAT for the air travel system.

A paper by four Boeing technologists and a TSA official describing the RMAT model appeared recently in Interfaces, a scholarly journal covering operations research.

I can’t imagine how random simulations are going to be all that useful in evaluating airplane threats, as the adversary we’re worried about isn’t particularly random—and, in fact, is motivated to target his attacks directly at the weak points in any security measures.

Maybe “chatter” has tipped the TSA off to a Muta al-Stochastic.

Coow • June 22, 2007 1:18 PM

From the abstract, it seems they are attempting to perform a cost-benefit analysis of proposed security measures:

===========ABSTRACT============

## The United States Commercial Aviation Partnership (USCAP), a group of government and industry stakeholders, combined several operations research methods in an analytical process and model that encompasses the US commercial aviation industry, including travelers, airlines, airports, airline and airport suppliers, government agencies, and travel and tourism entities. With input from these stakeholders, the model, combining system dynamics and econometrics, evaluates the effects of proposed security measures over 25 years. It enables all stakeholders to share a common understanding of these effects and helps government decision makers to improve security without undue and unforeseen operational and economic impact. The model uses linear and nonlinear programming, single and multivariate regression, system dynamics, econometrics, and Monte Carlo simulation. Since 2004, the government has considered the model results in determining policies for screening and credentialing airport employees, screening passengers and cargo, determining security staffing levels, and charging security fees. All participating stakeholders reviewed each analysis for acceptability. Based on the model’s success, they envision extending its use to include nonsecurity policy issues.