7 Biometric Data Mining Applied to On-line Recognition Systems José Alberto Hernández-Aguilar¹, Crispin Zavala¹, Ocotlán Díaz¹, Gennadiy Burlak², Alberto Ochoa³ and Julio César Ponce 4 ¹FCAeI-UAEM, ²CIICAp. Universidad Autónoma del Estado de Morelos ³Universidad Autónoma de Ciudad Juárez 4 Universidad Autónoma de Aguascalientes 1,2,3,4 México 1. Introduction Data mining has become an increasingly popular activity in all areas of research, from business to science, biometrics being no exception. Data mining is the computer-intensive activity of exploring large data sets with the purpose of discovering, within a subset of data, some relationship of patterns or hypothesis that may be worthy of further study (Hernández-Aguilar et al., 2008; Amaratunga & Cabrera, 2004). According to a widely accepted definition, knowledge discovery in databases (KDD), more widely known as data mining, is a non-trivial process of identifying valid, novel, potentially useful and understandable patterns in data (Fayyad et al., 1996). 1.1 Basic definitions But, what is biometric data mining? What does it study? First of all, let us clarify the meaning of biometric. According to Dunstone & Yager, 2009, there is a considerable amount of inconsistency among the terminology used within the biometric research and industrial communities. The best effort to date is ISO/IEC 17975-1, Information technology – Biometric performance testing and reporting. The following definitions of biometric and biometrics are consistent with this document: Biometrics is the automatic identification of an individual based on his or her physiological or behavioural characteristics. Biometric: A measure of a biological or behavioural characteristic used for recognition. There are four requirements for a biometric attribute: every person must have it, it should be sufficiently different for every person, it should remain constant over time, and it must measurable quantitatively. Let us now define Biometric data mining (BDM). BDM is the application of knowledge discovery techniques to biometric information with the purpose to identify underlying patterns. A principal objective of many data mining problems in biometrics research is to uncover characteristics of subsets of cases that are substantially different from the rest of the cases (Amaratunga & Cabrera, 2004). Consider the following: