A Novel Behavioural Biometric Technique for Robust User Authentication

ABSTRACT

In this paper, we propose a novel approach termed as fingerprint dynamics, targeted for multi-instance authentication system. Inspired by the concept of keystroke dynamics, the technique analyses the behavioural characteristics associated with multi-instance fingerprint acquisition. To capture the user data, an acquisition set-up (hardware) is devised. Data-set of genuine users and imposters are created using time-derived information, collected for unique fixed length sequences by 32 volunteers. Systematic evaluation of features and feature subset selection is performed. Goal of this paper is to determine potential of fingerprint dynamics and establish it as a successful biometric trait for the purpose of robust user authentication. The technique can be implemented as a part of multifactor authentication system or standalone alternative. Statistical analysis of classifier outputs for different kernels, by performing classification cross validation, and assessment of verification accuracies confirms the discriminating capability of proposed technique.

KEYWORDS:

• Authentication
• Biometrics
• Classification
• Feature subset selection
• Fingerprint dynamics
• Pattern recognition

Additional information

Notes on contributors

Ishan Bhardwaj

Ishan Bhardwaj received the BTech degree in computer science and engineering from UP Technical University, Lucknow, India, in 2010 and the MTech degree in computer technology from National Institute of Technology, Raipur, India, in 2012. He is currently pursuing the PhD degree at National Institute of Technology, Raipur, India. His research interest includes the information security, biometrics, and pattern recognition techniques. Apart from articles in conferences and journals, he holds two patents (pending) in the field of biometrics.

E-mail: [email protected]

Narendra D. Londhe

Narendra D. Londhe received his BE degree from Amravati University in 2000. Later, he received his MTech and PhD degrees in the year 2004 and 2011, respectively, from Indian Institute of Technology, Roorkee. He is presently working as an assistant professor in Department of Electrical Engineering of National Institute of Technology, Raipur. He has published articles in many reviewed journals and conferences. He is a senior member of IEEE.

E-mail: [email protected]

Sunil K. Kopparapu

Sunil K. Kopparpu received his doctoral degree in electrical engineering from the Indian Institute of Technology, Mumbai, India, in 1997. From 1997 to 2000, he was with Commonwealth Scientific and Industrial Research Organization, Brisbane, Australia. Prior to joining, the Cognitive Systems Research Laboratory, Tata Infotech Limited, as a senior research member, in 2001, he was associated with the R&D Group at Aquila Technologies Private Limited, India, as an expert for developing virtual self-line of e-commerce products. In his current role as a principal scientist with the TCS Innovations Labs Mumbai, he is actively working in the areas of speech, image, and natural language processing. Apart from several patents and journal and conference publications, he coauthored books and more recently a Springer brief on non-linguistic analysis of call center conversation.

E-mail: [email protected]