CCE Theses and Dissertations

Date of Award

2016

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Information Systems (DISS)

Department

College of Engineering and Computing

Advisor

Yair Levy

Committee Member

Stephen S. Furnell

Committee Member

Peixiang Liu

Keywords

Biometric, BIO+PIN, BIO-PIN, Personal Identification Number, Two-Factor Authentication

Abstract

The issue of traditional user authentication methods, such as username/passwords, when accessing information systems, the Internet, and Web-based applications still pose significant vulnerabilities. The problem of user authentication including physical and logical access appears to have limited, if any, coverage in research from the perspective of biometric as ‘something the user knows.’ Previous methods of establishing ones’ identity by using a password, or presenting a token or identification (ID) card are vulnerable to circumvention by misplacement or unauthorized sharing. The need for reliable user authentication techniques has increased in the wake of heightened concerns about information security and rapid advancements in networking, communication, and mobility. The main goal of this research study was to examine the role of the authentication method (BIO-PIN™ or username/password) and time, on the effectiveness of authentication, as well as the users’ ability to remember the BIO-PIN™ versus username/password (UN/PW). Moreover, this study compared the BIO-PIN™ with a traditional multi-factor biometric authentication using multiple fingerprints (without sequence) and a numerical PIN sequence (noted as "BIO+PIN"). Additionally, this research study examined the authentication methods when controlled for age, gender, user’s computer experience, and number of accounts. This study used a quasi-experimental multiple baseline design method to evaluate the effectiveness of the BIO-PIN™ authentication method. The independent, dependent, and control variables were addressed using descriptive statistics and Multivariate Analysis of Variance (MANOVA) statistical analysis to compare the BIO-PIN™, the BIO+PIN, and UN/PW authentication methods for research questions (RQs) 1 and 2. Additionally, the Multivariate Analysis of Covariance (MANCOVA) was used to address RQ 3 and RQ4, which seeks to test any differences when controlled by age, gender, user experience, and number of accounts. This research study was conducted over a 10-week period with participant engagement occurring over time including a registration week and in intervals of 2 weeks, 3 weeks, and 5 weeks. This study advances the current research in multi-factor biometric authentication and increases the body of knowledge regarding users’ ability to remember industry standard UN/PWs, the BIO-PIN™ sequence, and traditional BIO+PIN.

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