For this month’s blog challenge, I was inspired by one of the month’s big stories: how Osama bin Laden was caught.
The Navy SEALs deservedly get a lot of credit for the role they play in the ongoing wars on terror, but nerds also play a critical role in fighting terror. The intelligence that played a role in finding bin Laden depended on people on the ground in foreign countries as well as on analytics. Many intelligence agencies are populated by nerds who use analytical techniques on the large volume of data they collect.
We’ll never know exactly how important analytics is in fighting terrorism, but I’ve written a few thoughts here.
Various US government agencies collect and analyze an enormous amount of data on a daily basis. The NSA collects data equivalent in size to the Library of Congress every six hours. All of this data obviously cannot be scrutinized at a detailed level (hopefully they don’t get to all of it–I may be put on a watch list if someone looks at the google search terms I used to write this post). A data rich environment can lead to excellent decision-making if care is taken to determine how to use one’s limited resources for using analytical techniques. In the terrorism example, how does one determine
- which cell phone communications to record?
- which phone conversations deserve a transcript and which emails need to be translated?
- which data to summarize as metadata?
Another problem with terrorism is the lack of a proper dependent variable. For example, suppose you collect some cell phones that were used by known terrorists. If you want to look at the terrorists’ social networks by examining the calls sent and received from the terrorists’ phones, it is impossible to know if their calls were made to other terrorists or not (unless some of the numbers are to known terrorists).
This problem is not unlike, say, credit card companies trying to detect fraud. Both terrorism and fraud detection involve finding a needle in the haystack. However, terrorism social networks are large and involve many types of transactions (rather than, say, just credit card transactions). Osama bin Laden used flash drives and written communication delivered by courier, whereas others who are lower in the food chain use cell phones, land lines, email, etc. Credit card companies can also make decisions like dropping risky customers that don’t have analogous decisions when fighting terror.
It’s “easier” for a credit card company to determine who is fraudulent based on having more knowledge about their customers and having more certainty about their dependent variable (whether fraud is an issue). My credit card company called me while on vacation this winter, since my unusual purchases set of some kind of red flag. I was able to verify that no fraud was taking place after I answered a few questions. I was glad that they were looking out for me. No harm no foul.
Analytics used for fighting terror includes mining cell phone traffic for patterns, identifying social network analysis of terrorist organizations, and creating a system for analyzing risk air passengers or cargo containers (this report summarizes some of the analytical techniques that have been used). There are certainly some fascinating examples that are classified, but well have to speculate about those.
I’ve enjoyed the other blog posts about Analytics, especially those that discuss how analytics fits with the past and future of operations research. Please check out the other OR blogs to read more about analytics.