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Biometric & Biographic Data Resolution and Identity Management

IT Technology based on Fusion Biometrics, Data Mining, and Business Process-Driven Systems as an Integrated Data Analysis Solution

The concept of "biometric resolution and identity management" is an approach to multimodal biometric identity resolution techniques leveraged by physiological characteristics(combined facial, fingerprint,iris, signature, etc. recognition technologies or "fusion biometrics") and process-driven identity management work-flows consisting of assigning roles, permissions and tasks to individuals as identity cases are processed via process management-enabled routines. Matching precision, system adaptability, and process flexibility are key tenets of the biometric resolution and identity management systems and data mining approaches.

The analysis of identity records in large and very-large data sets or databases can be addressed by systemic data-mining techniques leveraged by the convergence of biometric (fingerprint, facial, iris) and biographic (textual, numeric, phonetic) recognition technologies. The capacity to biometrically and biographically (or demographically) determine duplicate identity records in databases (identity data cleansing, "scrubbing", or deduplication) or to pinpoint individuals with multiple identity representations in diverse functional environments (impersonation) can effectively reduce identity fraud exposure, significantly alleviate security and public safety risks, and substantially reduce operational costs. The above is achieved by cross-referencing data records against each other, maximizing output by biometric and biographic data analytics and pattern recognition technologies via the score-level or decision-level fusion of the combined outputs of unimodal biometric and biographic algorithms.

[1] Handbook of Multibiometrics. Ross, Arun A., Nandakumar, Karthik, Jain, Anil K. International Series on Biometrics, 2006, XXII, 202 pages and 65 illustrations, Hardcover ISBN: 978-0-387-22296-7

[2] Biometric System and Data Analysis: Design, Evaluation, and Data Mining. Dunstone, Ted and Yager, Neil. Springer. New York, New York 10013 USA. November 2009. ISBN-13: 978-0-387-77625-5.