Investigative Data Mining for Security and Criminal Detection

In this chapter, we will explore some of the criminal patterns in several areas, such as financial crimes (fraud), as well as those in the insurance industry involving medical scams, and, most importantly, those being perpetrated in the telecommunications industry. The telecommunications carriers, as is the case with e-commerce, represent the type of business entities of the future, where identity theft through the combination of available credit and the absence of a physical presence can lead to financial losses in the millions of dollars. Some of these crimes may apply to other industries, but we will concentrate on these three sectors as they are by far the most common. The data mining investigative methodology remains the same across different industrial crimes.
Fraud is defined as "an act of deceiving illegally in order to make money or obtain goods" by the Oxford Dictionary. It is also known as "scams" or, more elegantly, as "economic offenses." By any definition, it is a crime, which in our networked environment can cost businesses billions of dollars a year. Fraud detection involves an assortment of deterrence activities: pattern recognition, profiling of perpetrators, early warning systems, prevention schemes, avoidance organization, minimizing false alarms, estimating losses, risk analysis, surveillance and monitoring, enhanced security, forensic analysis, evidence collection, prosecution of criminals, and notification of law enforcement officials.
We will first discuss some of the known MOs and some known indicators of these crimes, then move on to present a general methodology that can be...