Digital Commons Network^™

Selected California State University Cybersecurity Readiness Policies And Related Guidance For Staff: A Qualitative Document Analysis, Andrew Hung-Nguyen

Dissertations

This study examines the cybersecurity and data privacy policy guiding the staff in the following four California State University campuses: Long Beach, San Bernardino, Chico, and Northridge. The purpose is to evaluate how institutional policies communicate expectations for staff and support cybersecurity readiness. Using a qualitative document analysis approach, the study analyzes publicly available policy documents as primary data sources. The analysis is guided by three frameworks, as follows: Weidman’s framework (2018), which assesses the presence of key policy elements; Karakoç’s framework (2022), which evaluates the depth of policy content; and the Flesch Reading Ease and Flesch-Kincaid Grade Level formulas …

Understanding The Cybersecurity Knowledge And Cybercrime Experiences Of Older Adults Using A Learning Game, Richard Conrad West

Dissertations

The purpose of this case study was two-fold. First, it was intended to evaluate the effectiveness of teaching internet safety to older adults through a fun, internet-based learning game. Second, it was carried out to understand the experience of internet fraud on older adults so that fraud prevention techniques can be refined and tailored to the online threats they face. Five adults over 60 who were previously online fraud victims participated in this study, which was carried out over three phases.

First, participants played a learning game that assessed their understanding of key cybersecurity topics, provided lessons explaining the risks, …

Balancergnn: Balancer Graph Neural Network For Imbalanced Datasets, Mallika Boyapati

Dissertations

Addressing imbalanced datasets is challenging due to machine learning models' inclination to learn the majority class. Graph construction plays a major role in determining how Graph Neural Networks (GNNs) perform on imbalanced datasets. In this research, we introduce the BalancerGNN framework to tackle highly imbalanced datasets, demonstrating its effectiveness in fraud detection as one of the case studies. This framework is designed to work for any binary node classification dataset with significant class imbalances. This research addresses the following questions: i) How effective are feature engineering techniques in the case of imbalanced datasets? ii) How do graph representation learning and …

Program Analysis For Android Security And Reliability, Sydur Rahaman

Dissertations

The recent, widespread growth and adoption of mobile devices have revolutionized the way users interact with technology. As mobile apps have become increasingly prevalent, concerns regarding their security and reliability have gained significant attention. The ever-expanding mobile app ecosystem presents unique challenges in ensuring the protection of user data and maintaining app robustness. This dissertation expands the field of program analysis with techniques and abstractions tailored explicitly to enhancing Android security and reliability. This research introduces approaches for addressing critical issues related to sensitive information leakage, device and user fingerprinting, mobile medical score calculators, as well as termination-induced data loss. …

Ai Approaches To Understand Human Deceptions, Perceptions, And Perspectives In Social Media, Chih-Yuan Li

Dissertations

Social media platforms have created virtual space for sharing user generated information, connecting, and interacting among users. However, there are research and societal challenges: 1) The users are generating and sharing the disinformation 2) It is difficult to understand citizens' perceptions or opinions expressed on wide variety of topics; and 3) There are overloaded information and echo chamber problems without overall understanding of the different perspectives taken by different people or groups.

This dissertation addresses these three research challenges with advanced AI and Machine Learning approaches. To address the fake news, as deceptions on the facts, this dissertation presents Machine …

Exposing And Fixing Causes Of Inconsistency And Nondeterminism In Clustering Implementations, Xin Yin

Dissertations

Cluster analysis aka Clustering is used in myriad applications, including high-stakes domains, by millions of users. Clustering users should be able to assume that clustering implementations are correct, reliable, and for a given algorithm, interchangeable. Based on observations in a wide-range of real-world clustering implementations, this dissertation challenges the aforementioned assumptions.

This dissertation introduces an approach named SmokeOut that uses differential clustering to show that clustering implementations suffer from nondeterminism and inconsistency: on a given input dataset and using a given clustering algorithm, clustering outcomes and accuracy vary widely between (1) successive runs of the same toolkit, i.e., nondeterminism, and …

Can Generative Adversarial Networks Help Us Fight Financial Fraud?, Sean Mciver

Dissertations

Transactional fraud datasets exhibit extreme class imbalance. Learners cannot make accurate generalizations without sufficient data. Researchers can account for imbalance at the data level, algorithmic level or both. This paper focuses on techniques at the data level. We evaluate the evidence of the optimal technique and potential enhancements. Global fraud losses totalled more than 80 % of the UK’s GDP in 2019. The improvement of preprocessing is inherently valuable in fighting these losses. Synthetic minority oversampling technique (SMOTE) and extensions of SMOTE are currently the most common preprocessing strategies. SMOTE oversamples the minority classes by randomly generating a point between …

Application Of Synthetic Informative Minority Over-Sampling (Simo) Algorithm Leveraging Support Vector Machine (Svm) On Small Datasets With Class Imbalance, Akshatha Fakkeriah Kallappanamatt

Dissertations

Developing predictive models for classification problems considering imbalanced datasets is one of the basic difficulties in data mining and decision-analytics. A classifier’s performance will decline dramatically when applied to an imbalanced dataset. Standard classifiers such as logistic regression, Support Vector Machine (SVM) are appropriate for balanced training sets whereas provides suboptimal classification results when used on unbalanced dataset. Performance metric with prediction accuracy encourages a bias towards the majority class, while the rare instances remain unknown though the model contributes a high overall precision. There are chances where minority instances might be treated as noise and vice versa. (Haixiang et …

Automation Of Authorisation Vulnerability Detection In Authenticated Web Applications, Niall Caffrey

Dissertations

In the beginning the World Wide Web, also known as the Internet, consisted mainly of websites. These were essentially information depositories containing static pages, with the flow of information mostly one directional, from the server to the user’s browser. Most of these websites didn’t authenticate users, instead, each user was treated the same, and presented with the same information. A malicious party that gained access to the web server hosting these websites would usually not gain access to confidential information as most of the information on the web server would already be accessible to the public. Instead, the malicious party …

Can Phishing Education Enable Users To Recognize Phishing Attacks?, Hanaa Alghamdi

Dissertations

Phishing attacks have increased rapidly and caused many drastic damages and losses for internet users‟ .The purpose of this research is to investigate on effectiveness of phishing education and training to help users identify different forms of phishing threats. The study has been conducted through developing a phishing quiz mobile application which includes four kinds of phishing threats. It tested the ability of users to recognize spoofed emails, SMS phishing (SMshing), scam phone calls (Vishing), and phishing through social media networks. A comprehensive literature review was discussed to investigate on the research area, understand the research problem, support the proposed …

Continuous Monitoring Of Enterprise Risks: A Delphi Feasibility Study, Robert Baksa

Dissertations

A constantly evolving regulatory environment, increasing market pressure to improve operations, and rapidly changing business conditions are creating the need for ongoing assurance that organizational risks are continually and adequately mitigated. Enterprises are perpetually exposed to fraud, poor decision making and/or other inefficiencies that can lead to significant financial loss and/or increased levels of operating risk. Increasingly, Information Systems are being harnessed to reinvent the risk management process. One promising technology is Continuous Auditing, which seeks to transform the audit process from periodic reviews of a few transactions to a continuous review of all transactions. However, the highly integrated, rapidly …

An Exploratory Study Of The Curricular Integration Of Ethics In Executive Mba Programs, Jaime M. Franco

Dissertations

An Exploratory Study of the Curricular Integration of Ethics in Executive MBA Programs

News headlines of corporate scandals have unleashed a contentious debate of whether or not graduate management education has contributed to corporate collapses and the resultant financial crisis. In particular, questions abound as to the willingness of Executive MBA program (EMBA) administrators and faculty to integrate ethics into the curriculum.

A sizable amount of research has been conducted and published on the curricular integration of ethics in graduate management education. Unfortunately, very little is known about the curricular integration of ethics in EMBA programs. Over time, the number …

Battery And Abuse In The Elderly: A Forensic Analysis, Amy Y. Carney Phd, Mfs, Np

Dissertations

Elder abuse is a recognized social problem in the United States. First labeled as "granny battering" and originally studied under the umbrella of family violence, maltreatment of the elderly has received more funding and research in recent years. Multiple aspects of elder abuse have been examined in the literature including measures for detection, assessment, and documentation. Although studies have examined the circumstances surrounding abuse as well as theories of causation and characteristics of the abuser and the abused, studies of the relationship between the abuser and the abused are less well documented. The purpose of this research was to examine …

The Impact Of Authentic Leadership And Ethical Organizational Culture On Auditor Behavior, Janice Taylor Morris Phd

Dissertations

Recently, unprofessional behavior resulted in several high-profile financial scandals and business failures. Many blamed external auditors of these companies' financial statements for failing to detect and/or report errors and fraud that led to the failures. Leaders within major audit firms have been urged to foster more ethical firm environments as a means of inhibiting dysfunctional auditor behavior (DAB) such as premature sign-off, gathering insufficient audit evidence, and the underreporting of time spent conducting an audit. This advice is based on two assumptions: (1) auditor behavior is one element of audit quality and (2) the behavior of employees is influenced by …