Thesis (M.S. in Information Systems and Operations)--Naval Postgraduate School, March 2003. / Thesis advisor(s): Alex Bordetsky, Randy J. Hess. Includes bibliographical references (p. 101-105). Also available online.

Thesis (M.S. in Computer Science)--Naval Postgraduate School, June 2003. / Thesis advisor(s): Cynthia Irvine, Timothy Levin. Includes bibliographical references (p. 91-92). Also available online.

M. Tech. Business Information Systems / Vehicle crime rate is increasing in many countries, particularly, in the developing countries. This includes theft and physical damages. These crimes are of major concern to individuals and organizations (such insurance companies). The crime rate on vehicles has impact on the country's economy. A more accurate identification processes and methods can help prevent crime, fraud, essential resources and reliable for access control. In the world today, car theft seems to grow every day and one of the best possible solution is to put in place high and accurate authorization and authentication method. The study investigated how Fingerprint Biometric Technology could be deployed in Motor vehicles to enhance the security features. This include investigation on the factors which influence and impact technology adoption. Factors influencing the deployment of Fingerprint Biometric Technology were identified from the findings and a Framework was developed. The primary aim of the Framework is to guide the adoption and use of Fingerprint Biometric Technology for an improved and enhanced security systems in Motor vehicles.

Multi-modal biometrics is one of the most promising avenues to address the performance problems in biometrics-based personal authentication systems. While uni-modal biometric systems have bolstered personal authentication better than traditional security methods, the main challenges remain the restricted degrees of freedom, non-universality and spoof attacks of the traits. In this research work, we investigate the performance improvement in bi-modal biometrics authentication systems based on the physiological trait, the iris, and behavioral trait, the signature. We investigate a model to detect the largest non-occluded rectangular part of the iris as a region of interest (ROI) from which iris features are extracted by a cumulative-sums-based grey change analysis algorithm and Gabor Filters. In order to address the space complexity of biometric systems, we proposed two majority vote-based algorithms which compute prototype iris features codes as the reliable specimen templates. Experiments obtained a success rate of 99.6%. A text-based directional signature verification algorithm is investigated. The algorithm verifies signatures, even when they are composed of symbols and special unconstrained cursive characters which are superimposed and embellished. The experimental results show that the proposed approach has an improved true positive rate of 94.95%. A user-specific weighting technique, the user-score-based, which is based on the different degrees of importance for the iris and signature traits of an individual, is proposed. Then, an intelligent dual ν-support vector machine (2ν-SVM) based fusion algorithm is used to integrate the weighted match scores of the iris and signature modalities at the matching score level. The bi-modal biometrics system obtained a false rejection rate (FRR) of 0.008, and a false acceptance rate (FAR) of 0.001. / Thesis (Ph.D)-University of KwaZulu-Natal, Westville, 2010.

Thesis (M.S.)--Youngstown State University, 2007. / Includes bibliographical references (leaves 24-28).

Thesis (M. Sc.)--University of Canterbury, 2008. / Typescript (photocopy). Includes bibliographical references (leaves 89-94). Also available via the World Wide Web.

Thesis (Ph. D.)--West Virginia University, 2009. / Title from document title page. Document formatted into pages; contains xiv, 195 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 181-195).

Thesis (M.S.)--West Virginia University, 2009. / Title from document title page. Document formatted into pages; contains ix, 92 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 76-79).

Thesis (Ph. D.)--West Virginia University, 2008. / Title from document title page. Document formatted into pages; contains xv, 136 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 125-136).

Thesis (Ph. D.)--West Virginia University, 2007. / Title from document title page. Document formatted into pages; contains x, 117 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 109-117).