Digital Commons Network^™

Assessing The Financial Impact Of Spoofing Attacks In Michigan’S Finance Industry, Shatarsha Smith

Walden Dissertations and Doctoral Studies

Spoofing attacks have become an increasingly significant cybersecurity threat, exposing organizations and customers to financial losses by impersonating trusted identities in digital environments. Cybersecurity leaders need a better understanding of how information security maturity and the selection of cybersecurity strategy relate to spoofing loss outcomes. Grounded in game theory, the purpose of this quantitative cross-sectional correlational study was to examine the relationships among information security maturity, cybersecurity strategy selection, and spoofing loss outcomes in the financial industry. Data were collected from approximately 90 IT professionals employed in a Michigan-based government office in the public finance sector with at least 5 …

How Do Dual Tasks Affect Id Verification? A Mobile Eye-Tracking Analysis, Nathan Wieters

Masters Theses (Archived)

ID screening is a two-part process — the card and identity must be authenticated. Psychological research has typically focused on identity verification without considering card verification. To fill this gap, the present study had participants complete an ID verification task while wearing eye-tracking glasses to record gaze behavior during face-matching decisions. After 2 practice trials, a research assistant presented 48 physical ID cards with embedded facial images, one at a time, beside a computer monitor that presented a facial videos and calendar date. Participants were asked to decide if the ID card was valid on a 6-option scale from Definitely …

Surveyception: An Exploration Of Deceptive Survey Forms, Muhammad Danish

Computer Science ETDs

Survey platforms such as Google Forms and Microsoft Forms are widely used for feedback, data collection, and engagement, but scammers increasingly exploit them to distribute phishing and deceptive attacks. This thesis presents a large-scale study of survey-form abuse across ten major providers. We collected 140,000 forms from three sources: public posts on X, search-engine results, and web pages from the top 10 million DomCop-ranked domains. Using automated filtering and manual qualitative review, we identified 2,645 forms requesting sensitive information and classified 566 as scams. These forms used techniques including phishing, private-secret theft, account and personal-data harvesting, financial deception, and psychological …

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 …

Exploring Critical Limitations And The Sustainability Of Small- And Medium-Sized Enterprises, Uluocha Diamond Okojie

Walden Dissertations and Doctoral Studies

No abstract provided.

Building Trustworthy Information Systems: A Unified Framework For Comparative Risk Detection, Parisa Momeni

USF Tampa Graduate Theses and Dissertations

Risk detection in large scale information systems increasingly depends on heterogeneous data generatedby both centralized and distributed ecosystems. While centralized systems provide curated and validated reports, distributed environments produce large-scale and real-time observational evidence. Existing computational approaches analyze these ecosystems in isolation, limiting systematic comparison of risk repre-sentations across heterogeneous sources.

This dissertation presents a unified computational framework for comparative risk detection across centralized and distributed information systems. The framework provides a domain independent methodology for transforming heterogeneous risk reporting data into comparable multidimensional representations. To enable interpretable comparison of heterogeneous risk distributions, this work introduces the Geometric Overlap Score …

Extending Unibreak: Semantic Retrieval And Harmful-Intent Direction Suppression For Token-Level Llm Jailbreaking, Sanket Saha

Master’s Dissertations

Token-level adversarial perturbations remain one of the most efficient known attacks against the safety alignment of instruction-tuned large language models (LLMs). Among recent works, the UniBreak framework (You et al., 2026) stands out for unifying gradient-based optimization with an evolutionary perturbation repository. However, its repository relies solely on accumulated success frequency without utilizing query content, and its fitness function implicitly assumes that suppressing refusal tokens is sufficient to elicit harmful responses. In this dissertation, we extend UniBreak along both axes and re-evaluates the framework under stricter generalization and judgment protocols. Specifically, we introduce a semantic perturbation repository that replaces frequency-only …

Accounting In Practice: An Analysis Of Real-World Business And Regulatory Case Studies, Claire E. Coursey

Honors Theses

This thesis consists of several accounting case studies completed throughout two semesters of Honors Accountancy 420 under the direction of Dr. Victoria Dickinson. The projects combined both individual and group work and focused on applying accounting knowledge to real-world business situations and current events. Each case study required research, analysis, and evaluation of topics related to financial reporting, auditing, regulation, and corporate operations. Throughout the fall semester, the case studies introduced a variety of accounting and business topics that helped develop research, analytical, and communication skills. During the spring semester, the primary focus shifted toward analyzing the potential impact of …

Exploring Real-World Accounting Problems Through Case Studies, Molly Clark

Honors Theses

This thesis is made up of six different accounting case studies completed both individually and collaboratively over two semesters in Accy 420 under the guidance of Dr. Dickinson. These case studies required in-depth research on the topics and reflection on how accounting concepts apply to real-world business situations. In the fall semester, a variety of case studies were assigned to help broaden understanding of relevant accounting topics such as regulatory issues and financial reporting. In the spring semester, students were placed into groups to do research on the “Make America Healthy Again” movement and evaluate its potential impact on an …

Bridging Theory And Application: Case Studies In Financial Reporting, Regulation, And Ethics, Keili Cm Ikemori

Honors Theses

This thesis explores the intersection of financial reporting, regulation, and ethics through a series of applied case studies designed to bridge theoretical accounting concepts with real world application. The case studies focus on how accounting principles are implemented in corporate environments, how regulatory frameworks influence business operations, and how ethical considerations shape financial decision making. During the fall semester of Accy 420, we were tasked with case studies that increased our knowledge in financial statement literacy, accounting concepts, relevant accounting regulations, and ethics. During the spring semester of Accy 420, we used the knowledge gained from the prior semester in …

Accounting 420 Case Studies Of Current Accounting Topics And Trends, Reed Anderson

Honors Theses

This thesis consists of six separate accounting cases including a three part case that analyzes the effects of the “Make America Healthy Again” (MAHA) movement on the company Conagra Brands. These cases were assigned by Dr. Dickinson during the 2024-2025 school year. During the fall semester, we were given four cases referencing different accounting related trends and were instructed to research these topics extensively. We were placed in groups where we could conduct research and consult amongst each other in order to expand our understanding of each topic provided. In between cases, we were lucky enough to hear from multiple …

Information Security Strategies To Thwart Cybersecurity Attacks In The Financial Services Industry, Donovan Anthony Miles

Walden Dissertations and Doctoral Studies

Financial markets and industries are vulnerable to ransomware attacks. Information technology (IT) security subject matter experts (SMEs) are concerned about ransomware cyberattacks on critical infrastructure that threaten their customers’ financial privacy and the institution’s reputation, causing severe financial losses and diminishing productivity. Grounded in the diffusion of innovation theory, the purpose of this qualitative pragmatic inquiry was to explore strategies IT security SMEs use to increase the implementation of existing solutions to thwart cybersecurity attacks in the financial services sector. The participants were six IT security SMEs in the financial industry in the Northeast United States who were responsible for …

The Effect Of Moral Potency On Employee Fraud Motive In Organizations, John Kopalchick Iii

PhD in Organizational Leadership

This study examined the drivers of employee fraud behavior. The theory of planned behavior served as the foundation for understanding how moral potency related to employee fraud motive. A sample of 102 auditors and audit-related professionals completed a survey on fraudsters’ behavioral traits. Using quantitative, nonexperimental methods, this study employed correlational and predictive statistical tests to examine the relationship between moral potency and employee fraud motive. Results showed no significant relationship between moral potency and employee fraud motive. The study filled a gap by applying quantitative methods, specifically the employee fraud motive scale, to understand employee fraud behavior in a …

Media On Trial: The Effects Of Media Coverage On Legal Proceedings In High-Profile Cases, Julia Luxon

Honors Theses

This paper examines the constitutional tension between the First Amendment and the Sixth Amendment, specifically in relation to media coverage and the right to a fair trial in high-profile criminal cases. This study explores the contextual and media environments surrounding the high-profile cases of Sheppard v. Maxwell, The People of the State of California v. Orenthal James Simpson, and State of South Carolina v. Richard Alexander Murdaugh. By conducting a comparative analysis, I examined the media narratives present in each case and how they influenced public perception and its impact on the administration of justice. This study …

Financial Fraud In Mississippi Public Agencies: Case Studies Of Control Failures And Implications On Civic Engagement, Gracie Sullivan

Honors Theses

This study analyzes the relationship between financial fraud in Mississippi public institutions and its potential impact on civic engagement. While the existing literature explores the mechanics of fraud through frameworks such as the Fraud Triangle and the role of internal controls in preventing misconduct, limited research examines how government corruption influences civic disengagement, particularly in Mississippi. Using a quantitative, comparative research design, this study examines the relationship between major public financial fraud cases and voter turnout in case-linked and comparison counties. These cases include the Mississippi TANF welfare fraud, the Department of Corrections bribery case, and the misuse of funds …

Leveraging Accounting Analytics To Enhance Payroll Accuracy And Fraud Detection In U.S. Public Sector Institutions: A Case Study Approach, Regina Debrah

Beacom School of Business Student Publications

This study explores how accounting analytics can be leveraged to enhance payroll accuracy and improve fraud detection in U.S. public-sector institutions, addressing persistent irregularities amid rising demands for fiscal transparency. The research employs a qualitative design with secondary sources including academic literature, reports, and case studies. The literature identifies successful analytics implementation, such as Treasury OPI’s machine learning for data integration for unemployment claims. These precedents demonstrate direct transferability to payroll’s high volume and rules-based structure. Findings show that analytics significantly reduce improper payments through real-time screening, data integration, and risk prioritization when embedded in workflows. The findings also show …

Strategies For Reducing Fraud In Corporate Organizations, Tarshall Horton Mccauley

Walden Dissertations and Doctoral Studies

Financial statement fraud has been a persistent problem that poses risks to corporations globally. Business leaders are concerned about financial statement fraud due to its potential to weaken financial stability, erode stakeholder confidence, and create conditions that may lead to significant financial distress or organizational collapse. Grounded in the fraud triangle theory, the purpose of this qualitative pragmatic inquiry research was to explore internal control strategies corporate leaders use to reduce financial statement fraud risk. The participants were 11 financial leaders in North Carolina, the District of Columbia, and Virginia who practiced effective internal controls to minimize financial fraud. Data …

Tackling The Societal And Regulatory Challenges Of Emerging Technologies: A Case Study Of Deepfake, Jingyao Li

2026

Governing emerging technologies such as Artificial Intelligence (AI) poses enduring challenges for policymakers, industries, and societies. Early-stage governance is often hindered by limited understanding of technological implications, rapid innovation cycles, and resistance from powerful industry actors who favor minimal oversight. Yet, timely and effective governance is essential, as new technologies are most malleable in their formative stages. This dissertation examines how emerging technologies can be governed effectively by using deepfakes technology as a focal case. This dissertation comprises three interrelated studies.

The first paper reviews the literature on deepfakes and emerging technology governance, identifying the distinct characteristics of deepfake technology …

Adaptive Real-Time Fraud Detection Using Online Learning And Explicit Concept-Drift Detection, Purva Govind Tugaonkar

Master's Projects

Real-time credit card fraud detection faces challenges such as extreme class imbalance, delayed feedback, and concept drift in transaction streams. This project implements and evaluates an adaptive streaming fraud detection framework based on three methodologies: (1) online learning with incremental updates, (2) explicit conceptdrift detection using statistical monitoring, and (3) separate models for immediate and delayed supervision, combined with cost-sensitive learning and anomaly detection. The system processes the credit card fraud dataset in a batched streaming fashion, uses multiple online learners and ensembles. Experiments show that online, driftaware models maintain high recall on frauds while controlling false positives under imbalanced …

They're Collecting My Data, So What? The Effects Of Privacy Fatigue On Trust And User Experience, Vanessa Brewster

Dissertations from the Executive Doctorate in Business Administration Program

With the increasingly connected nature of Web 4.0 and the AI-enabled internet, new ways to capture biometric data through smart devices are becoming more commonplace, and users are presented with an overwhelming number of decisions regarding how their data is collected and used. As such, concerns about data privacy remain a key issue among those with varying levels of fears of technology. However, privacy concern scales have not yet been updated to give researchers a full picture of the impact, and with control mechanisms varying widely across countries as regulation struggles to keep pace with innovation, trust in technology can …

Security-Oriented Voice Authentication Using Machine Learning, Ifeoluwa Stella Elegbe

College of Graduate Studies: Theses & Dissertations

This study develops and evaluates a machine learning and deep learning-based voice authentication system for secure identity verification. As traditional authentication methods such as passwords, PINs, and security tokens continue to face challenges, including identity theft, forgetting, and unauthorized access, voice biometrics offers a more secure, convenient, and user-friendly alternative, especially for remote, hands-free, and accessibility-focused applications. The study adopts a closed-set speaker identification framework, where the system determines the most likely speaker from a predefined group of enrolled users. A structured methodology is implemented, beginning with audio preprocessing and feature extraction. Key acoustic features, including Mel-Frequency Cepstral Coefficients (MFCCs), …

Robust Anomaly Detection Under Data Imbalance, Noise, And Label Scarcity, Zahra Salekshahrezaee

Electronic Theses and Dissertations 2020 - Present

In today’s data-driven landscape, large volumes of data are generated continuously, often containing imperfections such as noise, missing data, or unreliable labeling. These real-world datasets are typically high-dimensional, sparsely labeled, and imbalanced, creating substantial challenges for both supervised and unsupervised learning. These challenges are especially prevalent in the task of anomaly detection, where instances belonging to the class of interest are rare and underrepresented compared to normal instances. This dissertation proposes and evaluates robust frameworks for anomaly detection that address these data challenges and improve model performance and robustness using real-world datasets, including credit card transactions and cognitive assessments. Supervised …

Internal Control Strategies To Reduce Occupational Fraud In Small Business, Karen Walauskas

Walden Dissertations and Doctoral Studies

Small businesses can be at a heightened risk of occupational fraud if their internal control strategies are not effective. This risk is a major concern for small business owners, who might face financial and operational challenges as a result. Grounded in Cressey’s fraud triangle framework, the purpose of this qualitative multiple case study was to explore effective internal control strategies to reduce the risk of occupational fraud from occurring. Participants were six small business owners in New England who had developed effective internal controls. Data were collected through semistructured interviews and employee handbooks. Through thematic analysis, four themes emerged, including …

Beyond Compliance: Rethinking Ethical Accounting Through Ai And Esg, Rafael L. Portillo

Honors Program Theses and Research Projects

With the increasing adoption of these modern technologies in world markets while maintaining these ethical principles, there is an increasing need for alignment between technology development and ethical responsibility. For instance, in the world of accounting, there is an increasing demand to maintain alignment between technology development and ethics. It is for this reason that these researchers have chosen to explore the link between Artificial Intelligence, ESG, and financial reporting ethics.

The goal of this study is to look at new concerns and moral risks that appear when ESG expectations, AI systems, and accounting practices interact. Earlier research usually studies …

Explainable A.I. For Analysis And Interpretation Of Heterogeneous Crime Data., Sadaf Ahmed

Electronic Theses and Dissertations

This dissertation examines the problem of fragmented data in the context of crime and cybercrime analysis. While both domains generate substantial public data, these sources vary widely in format, structure, and coverage, making it difficult to perform consistent inference or develop reliable predictive models. To address these limitations, this work proposes a layered integration framework grounded in ontology-driven modeling and data fusion. The approach is applied to two distinct but related case studies, each focused on constructing a coherent representation of criminal activity from heterogeneous sources. The first case study explores the integration of drug and human trafficking data from …

Cross-Modal Prompting For Multi-Class Visual Anomaly Localization, Duncan F. Mccain

All Theses

Visual anomaly detection is a technology that uses computer vision to automatically identify defects or irregularities in images, such as cracks, scratches, or discolorations on manufactured products. Unsupervised visual anomaly detection does this without needing examples of those defects during the training process. This "unsupervised" approach is crucial in industries like manufacturing, automotive, electronics, and pharmaceuticals, where ensuring product quality is essential for safety, reliability, and cost efficiency. For instance, it helps spot flaws in circuit boards, fabrics, or medical pills during production lines, preventing faulty items from reaching consumers. By reducing manual inspections, it saves time and resources, benefiting …

Bridging The Digital Divide: Educating Older Adults To Recognize And Prevent Scams, Isabella S. Chan

Capstone Projects and Master's Theses

The older adult community, especially those 60 years and older, is a frequent target of scams and financial exploitation. When an individual is scammed, and with the likelihood of older adults choosing not to report, many do not recover their money (CFPB 2022). Social isolation and cognitive decline are significant factors that increase an older adult’s susceptibility to scams; however, digital literacy and their lack of understanding of technology are also obstacles to detecting a scammer’s deception. In response to these concerns, I created an hour-long presentation to educate and bring awareness to older adults about scams and how to …

Striking A Balance Between Personal Data Protection And Transactional Efficiency In The Context Of Data-Driven Mergers, Jun Hu

Dissertations and Theses Collection (Open Access)

The proliferation of data-driven mergers and acquisitions (M&A) has created a critical tension between the commercial value of integrated data assets and the fundamental privacy rights of users. This dissertation addresses the underexplored micro-foundations of user consent when personal data is transferred wholesale to an acquiring firm. It develops and empirically tests a sequential mediation model, anchored in Privacy Calculus and Signaling Theory, to explain how users' perceptions and intentions are shaped by different corporate data protection strategies.

A between-subjects experimental design was employed (N=532), exposing participants to one of three distinct protection mechanisms: procedural safeguards (emphasizing fairness and control), …

Ai-Facilitated Abuse & Misogyny: A Feminist Response To Non-Consensual Intimate Image Deepfakes, Lizbeth Carmona

Open Access Theses & Dissertations

The creation of non-consensual intimate images utilizing AI deepfake technology has been demonstrated to overwhelmingly target women. The harms of non-consensual intimate image deepfakes are similar to other forms of misogynistic abuse, including intimate image abuse and online objectification. This project seeks to contextualize this phenomenon within feminist accounts of misogyny and its role in regulating women's behavior. In particular, this project highlights that the accessibility of this technology has lowered the threshold of abuse, despite the individual woman's preventive measures. Furthermore, this project argues that the dissemination of non-consensual intimate image deepfakes is a morally problematic situation because it …

Lamda: A Longitudinal Android Malware Dataset For Benchmarking Concept Drift Detection And Adaptation, Md Ahsanul Haque

Open Access Theses & Dissertations

Machine learning (ML)-based malware detection systems often fail to account for the dynamic nature of real-world training and test data distributions. In practice, these distributions evolve due to frequent changes in the Android ecosystem, adversarial development of new malware families, and the continuous emergence of both benign and malicious applications. Prior studies have shown that such concept drift—distributional shifts in benign and malicious samples—leads to significant degradation in detection performance over time. Despite the practical importance of this issue, existing datasets are often outdated and limited in temporal scope, diversity of malware families, and sample scale, making them insufficient for …