Biometric Person Authentication (8020.2)

Principles of biometric authentication; physical biometrics, fingerprints, iris, retina, hand geometry, facial characteristics; behavioural biometrics, speech, writing, typing, pointing; statistical models, Bayesian analysis, prior and posterior probabilities, likelihood ratio; identification and verification paradigms, type-1 and type-2 errors, detection error tradeoff (DET) curves; role of the independent expert.

Learning outcomes

On successful completion of this unit students will be able to show an understanding of different methods for physical and behavioural biometric person authentication; an understanding of the statistical models underlying the identification and verification paradigms; an understanding of the Bayesian decision framework, including error categories, prior and posterior probabilities; and an understanding of the role of the independent expert. In terms of generic skills, students will be able to: identify problems and analyse the main features of problems relevant to their professional field; apply appropriate problem solving processes, arguments, critical and creative thinking; implement and evaluate strategies for the resolution of problems; anticipate and define new problems; and identify and resolve new problems in new fields.

Prerequisites

Discrete Mathematics or Engineering Mathematics 1 or Engineering Mathematics 2 and Software Technology 1.