# Airline Screening List Mathematics

What do Santa Claus and DHS have in common? They both keep a list of who’s naughty or nice. DHS’s list isn’t quite as large as Santa’s, but it’s getting quite big. From the AFP:

A watchlist of possible terror suspects distributed by the US government to airlines for pre-flight checks is now 80,000 names long, a Swedish newspaper reported, citing European air industry sources.

The classified list, which carried just 16 names before the September 11, 2001 attacks in New York and Washington had grown to 1,000 by the end of 2001, to 40,000 a year later and now stands at 80,000, Svenska Dagbladet reported.

Airlines must check each passenger flying to a US destination against the list, and contact the US Department of Homeland Security for further investigation if there is a matching name.

A few days ago, I blogged about a news article that revealed that 30,000 people are wrongly flagged as “matches” on the list.

So applying my very amateur mathematics skills, that means of the 80,000 names on the list, possibly about 30,000 of them (37.5%) match those of an innocent traveler.

Now, I bet that there are repeats, so several of the 30,000 could have the same name. If John Smith is one of the names on the list, it could account for a number of innocent travelers being flagged. Still, these numbers strike me as quite alarming. Something is seriously wrong. Is this really a competent way to go about airline security? What, precisely, gets a name on the list? Why are these lists so bad that they capture so many innocent people?

I guess the DHS is no Santa Claus.

Related Posts:

Hat tip: Privacy.org

### 3 Responses

1. ac says:

A healthy false positive rate is expected even with a very high quality list, given the number of travelers, the frequency of actual threats, and the nonuniqueness of names. The odds are stacked against the scheme. Biometrics have some prospect of reducing the number of false positives.

2. Adam S says:

I think your math is off.

30,000 people have gone through the process of adding their names to the cleared list. We can presume some fraction of them (let’s say 100) are named David Nelson. All of these 100 people are actually a single match against an unknown name in the list. It might be David Nelson, or it might David Ellison, or something else. Without knowing the names of the removed, we can’t guess how many of the names on the lists are being matched.

Also, we don’t know from the 30,000 number how many matches occur. (TSA has repeatedly claimed to keep no statistics on this, which I find odd, because it means they can’t evaluate if Secure Flight improves anything.) That 30,000 could be (a) everyone who matched, or it could be (b) everyone who matched who also flew in the relevant period, or (c) everyone in ‘b’ who didn’t decide that the new process was so disgusting they’d never fly again, or (d) some subset of ‘b’ who asked the right questions after 2003 and was given the form and believed that the government would do something useful with it.

I’d go with option ‘d,’ and suggest that its a class whose size is difficult to measure, but is likely far smaller than ‘a’ or ‘b.’

3. Paul Gowder says:

AC has a very good Bayesian point… which doesn’t make the list justified, mind.