CEC Theses and Dissertations

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Date of Award

2014

Document Type

Dissertation - NSU Access Only

Degree Name

Doctor of Philosophy in Computer Information Systems (DCIS)

Department

Graduate School of Computer and Information Sciences

Advisor

Maxine S Cohen

Committee Member

James Cannady

Committee Member

James Bryant

Abstract

The usability of Identity Management (IdM) systems is highly dependent upon design that simplifies the processes of identification, authentication, and authorization. Recent findings reveal two critical problems that degrade IdM usability: (1) unfeasible techniques for managing various digital identifiers, and (2) ambiguous security interfaces. The rapid growth of online services consisting of various identifier concepts and indistinct designs overwhelm users and disrupt desired computing activities. These complexities have led to an increase in work operations and additional effort for end users. This work focused on these challenges towards developing a contextual model that enhanced IdM usability. The context of this model provided users with preapproved identification and technical features for managing digital identifiers.

A sample population of military and government participants were surveyed to capture their relative computing characteristics and end user requirements for IdM and identifiers. Characteristics, such as Ease of Access Management, Cognitive Overload, Identifier Selection, Confidentiality, and Trust were recorded and measured by means of their frequency of occurrence. A standard deviation was utilized for assessing the volatility of the results. Conclusive results were successfully integrated into an attribute-based architecture so that the contextual model's algorithm, which was the contribution of this work, could be utilized for interpreting requirement attributes for defining end user IdM parameters for business applications. Usability inspection results illustrated that the model's algorithm was able to reduce cognitive overloads and disruptions in workflow by limiting recognition, recall, and convenience values of end users.

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