TABLE OF CONTENTS Identity theft is the nation's fastest-growing crime, and it is not just terrorists who create identities to mask their presence; this crime is also committed by perpetrators who steal credit cards through various schemes on the Web or from trash dispensers. After 9/11, advances have been made to unify state driver's licenses and to regulate Social Security numbers more tightly. While these efforts will lessen the masking of perpetrators, data mining can also be used to validate the identify of individuals. In this chapter, a theoretical architecture for accessing multiple and disparate data sets will be described, the purpose of which is to validate a person's identity via machine-learning algorithms coupled with the experience of seasoned investigators.
The entity validation system (EVS) will develop predictive models that will support a wide range of field personnel and devices in confirming the identity of individuals. The concept is to provide data mining as a Web service for security deterrence purposes. The evolution of the Internet, wireless networks, and a number of information system standards provides the infrastructure for such a system. In the near future, this kind of service will be feasible using a pervasive network, linking systems and agents via a grid, providing real-time intelligence derived from autonomous data mining robots that are self-adjustable, evolutionary, and continuously learning, under the tutelage of experienced analysts.
The envisioned EVS would utilize remote data access via networks and an evolutionary real-time data mining system. The concept advanced here is one of...
