And since the tails of Monte Carlo risk distributions, which would be of the most interest here, are very sensitive to the inputs, they are pretty useless as forecasting devices for phenomena such as terrorism, even though they work quite well for phenomena such as failure rates of machinery. ]]>

If folks are interested in coming to work on RMAT and can pass a security clearance, send me your resume. I am hiring.

- TSA Director of Risk Mgmt

Monte Carlo methods can be usefuleven in problems that ave no randomness in the original problem at all. By transforming it into a randomised problem and then solving by Monte Carlo methods, an approximate solution can be obtained with vastly less computation (and hence, lower cost.)

The classic example of this is finding the value of pi by Monte Carlo. Obviously, pi is not random. But what we do is generate random points (pairs of random numbers) where x is in (-1,1) and y is in (-1,1). We then find the distance of (x,y) from origin, it is sqrt(x^2+y^2). If the distance is less than 1 then it is in the unit circle, so we count it “in”. In the long run the fraction of points counted “in” is pi/4, so we can find pi.

This is actually not a very good way to calculate pi (the number of random points required rises exponentially with the number of digits of precision wanted) but it shows that the domain of Monte Carlo methods goes far beyond “randomised”, “probabilistic” and “statistical” problems and includes even such things as complex, nonlinear but strictly analytic problems.

So is the Boeing team approach sensible? It is impossible to say from this article. It might as well say they are using calculus. All it tells us it that they know some mathematics, it doesn’t tell us anything about whether or not their proposed method is correct.

]]>I can imagine this working in a safety context. You don’t have the resources to check the security of every part of an airport. Instead you do a thorough review of those areas that a random number generator told you to.

The advantage? Again, it removes bias. In particular it forces you to review a certain number of areas where you can’t imagine a vulnerability.

]]>Now, how many car bombs have you seen detonated?

If you were the TSA, which would you defend against – a suicide bomber on a plane or a suicide bomber in the security line in the airport leading to the plane?

Today’s TSA doesn’t even functionally prevent the suicide bomber on the plane scenario – they just steal toddlers’ sippy cup liquids. So where does that leave us? Without rights or security. Go Ben.

“Those who would give up essential liberty to purchase a little temporary safety deserve neither liberty nor safety.” – Ben Franklin

]]>All this discussion, and still no one has mentioned the last paragraph of the article referenced by Bruce’s link:

“As for operations researchâ€™s role in the Battle of the Atlantic, the Navy used it not only to help find submarines but also as a public relations smokescreen to hide the more effective mathematical tool used to sink subs: Cryptanalysis of German naval radio traffic.”

duh.

]]>This is likely in response to the “next time I’m driving” sentiment and the recent news stories about the diminished utility of air travel for time and money savings. By predicting the wait time more accurately and having pre-baked impact plans, they’ll allow people to spend less time idle at the airport – they can diminish the security exposure of the massive campgrounds at the terminal, and improve passenger throughput (and presumably revenue).

]]>Identify vulnerabilities? no, the potential attacks and defenses as well as all components involved must be well known to run Monte Carlo.

]]>http://en.wikipedia.org/wiki/Monte_Carlo_method

Yes, it seems to make sense.

]]>As far as I can tell from Google “RMAT” is about reliability and maintainability. Aviation engineers appear to develop these models routinely. They predict the likely maintenance costs and downtime for aircraft, and as others have noted, Monte Carlo methods are generally used in the evaluation engines of these tools.

So it looks like someone at the TSA has taken an RMAT tool and tried to build a model of terrorist success. As others have noted, terrorists can apply intelligence, but if you consider a certain attack mode (e.g. 50g of a certain explosive) then you can use a model like that to predict the likely impact: does the airline break in half, or does it just get a hole in the side? Would overpressure release mechanisms help? And so on.

So yes, it makes sense. The only sad thing is that the press release makes it sound a lot more important than it is. But hey, thats what we employ PR people to do.

Paul.

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