Digital Commons Network^™

Mental Model Dilemma Of Technological Shifts And Generational Gaps? Incorporated From The Musings Of An Octogenarian., Madhavi Chakrabarty

Atlantic Marketing Association Proceedings

No abstract provided.

Mental Model Dilemma Of Technological Shifts And Generational Gaps? Incorporated From The Musings Of An Octogenarian, Madhavi Chakrabarty

Atlantic Marketing Association Proceedings

No abstract provided.

Gentrification, Poverty, And Investors’ Influence On Vulnerable Populations: A Market Perspective Case Study, Doreen E. Sams, Mary K. Rickard, Aruna Sadasivan

Atlantic Marketing Association Proceedings

No abstract provided.

Predictive Modeling In Social Media Deepfake Identification, Samuel Whatley Ii

Helms School of Government Spring Public Policy Conference

No abstract provided.

Ai In Government Accounting & Fraud Detection, Amy Hernandez Paz

Doctoral Student Association Conference

The United States is seeing an alarming rise in financial fraud and suspicious activity trends within its government entities (Bruce et al., 2024). According to the Accountability Office (2024) the federal government estimates the annual financial loss has increased from $233 billion to $521 billion, based on data from fiscal years 2018 through 2022. Advancements in technology are not strictly limited to government financial solutions. The Federal Bureau of Investigation (2024) found a rise in generative Artificial Intelligence (AI) exploitation among criminals to facilitate financial schemes such as fraud and extortion. The literature review aims to investigate the gap in …

Gc-1215 Clinicalrag: A Scalable Benchmark Of Privacy, Relevance, And Speed In Semantic Retrieval For Clinical Transcriptions​ ​, Pradyumna Kumar, Sai Sruti Dandibhatla, Srinivasan Subramanian, Purna Chandu Anukula, Pranitha Athukuri

C-Day Computing Showcase

Traditional keyword search struggles with the scale, complexity, and contextual depth of clinical data. This project develops and evaluates semantic search systems that better understand medical language, enabling physicians and researchers to retrieve contextually relevant information through a Retrieval Augmented Generation (RAG) framework. We integrate privacy-preserving methods, including differential privacy and homomorphic encryption to protect sensitive clinical transcriptions. For improved speed and accuracy, we enhance the baseline RAG architecture with Hierarchical Navigable Small World (HNSW) indexing and Maximal Marginal Relevance (MMR) based reranking. To ensure scalability, clinical documents are ingested using PySpark and stored in a vector database optimized for …

Emotional Disinformation And Engagement Bait: Ai-Generated Images On Facebook, Hyrije Mehmeti

UBT International Conference

Emotional disinformation and engagement bait: AI-generated images on Facebook PhD. Student Hyrije Mehmeti1 Abstract Images generated with Artificial Intelligence (AI) are emerging as a powerful tool for disinformation, particularly on Facebook, where content spreads rapidly and reaches wide audiences. This paper examines how such images are used as engagement bait in Albanianlanguage Facebook posts to spread emotional disinformation. The study draws on fact-checkerverified cases where fabricated visuals were paired with captions designed to provoke user interaction and amplify reach. Using a qualitative case study approach, the analysis was guided by three criteria: the post included an AI-generated image, the text …

Assessing The Effectiveness And Implementation Of Artificial Intelligence In Detecting And Preventing International Financial Crimes: A Case Study Of The United Kingdom, Robert J. Dalton

OneUSF Undergraduate Research Conference

Financial crime has been an issue that has plagued the world for as long as the concept of trade has existed. With the rise of the digital age and globalization, financial crime has continuously and significantly evolved, with increasingly complex and intricate methods of financial crime and fraud being committed each year. Government organizations and financial institutions are having to constantly overcome new barriers and challenges to monitor financial crimes due to their evolving nature. Artificial intelligence, a new technology that is being constantly researched and explored, has the potential to innovate current and new technologies within the financial intelligence …

Exploring The Role Of Personality Traits In Predicting Financial Vulnerability: Moderating Effects Of Digital Literacy And Financial Literacy Within The Framework Of The Theory Of Planned Behavior, Saad Ahmed Almarzooqi

Thesis/ Dissertation Defenses

The growing integration of digital financial services in the UAE has introduced new challenges in mitigating financial fraud, particularly in understanding individual susceptibility to such risks. This study explores the role of personality traits and shaping financial fraud vulnerability, employing the theory of planned behavior (TPB) to examine how extraversion, agreeableness, consciousness, neuroticism, and openness to experience influence this vulnerability. The study further assesses the mediating roles of subjective norms, attitude towards financial fraud, and perceived behavioral control in these relationships, as well as the moderating effects of digital and financial literacy.

Results from a cross-sectional survey of 406 UAE …

Leveraging Benford’S Law And Machine Learning For Financial Fraud Detection, Benjamin R. Fu

Cybersecurity Undergraduate Research Showcase

Financial fraud, particularly credit card fraud, continues to pose substantial challenges to financial institutions due to its increasing frequency and impact on consumer trust. While traditional rule-based methods have provided foundational defenses, their limitations in scalability and adaptability have accelerated the adoption of machine learning (ML) techniques. Concurrently, Benford’s Law—a statistical principle often used in forensic accounting—has demonstrated efficacy in detecting anomalies within naturally occurring numerical datasets. This study explores a hybrid fraud detection approach that integrates Benford’s Law with supervised machine learning algorithms, including Logistic Regression, Random Forest, and k-Nearest Neighbors. Using the publicly available European credit card fraud …

How Can We Improve Our Security Measures To Safeguard Against Cyber Threats?, Mattea Trotter-Hicks

Cybersecurity Undergraduate Research Showcase

Many people face the issue of having their information stolen without their knowledge of what is happening. I understand that some people don’t pay attention to everything when it comes to making sure their information is being secured properly. There must be set stages for those who don’t know technology as well and will need help with knowing what to do. There are many stories of people going through issues with getting hacked or scammed out of their money or important information. We are going to dive into finding ways to fix the outcome of others knowing what to do …

The Evolution Of Web Development, Leart Musahu, Faton Kabashi, Lamir Shkurti, Vehbi Sofiu, Laura Gjikokaj

UBT International Conference

The evolution of web development has been marked by significant technological advancements, transforming the way users interact with digital content. This topic will analyze the key milestones and breakthroughs that have shaped the development of the web from its early days to the modern era. Initially, web development focused on static HTML pages, offering limited interactivity and user engagement. The introduction of CSS and JavaScript brought dynamic content and responsive designs, greatly enhancing the user experience. The emergence of Web 2.0 introduced a new era of web development characterized by user-generated content, social networks, and the rise of interactive web …

The Importance Of Financial Literacy, The Inclusion Of Financial Education In The School Curriculum (Case Study: Kosovo), Ardian Uka, Valon Ismajli, Erzana Uka

UBT International Conference

The paper discusses the value of financial literacy and emphasises the importance of financial education inclusion into Kosovo's publicschool curriculum. The paper initially elaborates on the importance of financial literacy and then expands on its impact on people’s knowledge to become or maintain their financial stability and well-being. It is pointed out that understanding personal finance management can help people have a better connection with money and their finances. Research suggests that young people getting ready for adulthood should be encouraged to become financially literate to meet society's health and economic concerns. In this context, after observing the school curriculum …

International Conference On Management Business And Economics, University For Business And Technology - Ubt

UBT International Conference

UBT Annual International Conference is the 13th international interdisciplinary peer reviewed conference which publishes works of the scientists as well as practitioners in the area where UBT is active in Education, Research and Development. The UBT aims to implement an integrated strategy to establish itself as an internationally competitive, research-intensive university, committed to the transfer of knowledge and the provision of a world-class education to the most talented students from all background. The main perspective of the conference is to connect the scientists and practitioners from different disciplines in the same place and make them be aware of the recent …

Trends From 20 Years Of Artificial Intelligence In Financial Services In Africa, Nthabiseng Moela, Lerato Matlala, Jackie Ma, Dipuo Maphutha, Hossana Twinomurinzi

African Conference on Information Systems and Technology

The need for financial inclusion in Africa, particularly for marginalised groups like women and small businesses, highlights the importance of leveraging Artificial Intelligence (AI). This study provides a bibliometric analysis of AI's integration into African financial services from 2003 to 2023. The key results show a significant increase in AI use, particularly in fraud detection, credit risk prediction, and stock market volatility forecasting, with 49% of the research coming from South Africa, Nigeria, and Tunisia. However, areas like financial development management, inflation control, and gender disparities in loan access remain underexplored. The emphasis has been on the technical implementation of …

Anomalous Transaction Detection In Bank Credit Card Data Using Machine Learning, Lerdinia Varaidzo Mapepa, Jerremiah Musariwa, Lucia Makwasha, Samuel Mugijima

African Conference on Information Systems and Technology

Illegal money changers pose a number of risks to the financial system, including but not limited to money laundering, fraud, and other under-the-carpet dealings intended to frustrate regulatory efforts for financial integrity. The efficiency and accuracy of anti-money laundering (AML) measures using machine learning (ML) models in the detection of suspicious patterns in bank card transactions are investigated in this paper. The key focus will be to develop an efficient machine learning framework that should be proficient in underlining main transactions dealing with illegal money changers and other similar fraudulent activities. The features indicative of illicit behaviour are determined by …

Profiling Cybercriminals: Behavioral Analysis And Motivations Behind Cybercrime Activities, A'Shya Latrice Reynolds

Cybersecurity Undergraduate Research Showcase

The study of cybercriminal behavior and motivations is crucial for understanding and combating the evolving landscape of digital crime. This paper delves into the intricate realm of cybercrime profiling, employing a multidisciplinary approach to dissect the behavioral patterns and underlying motivations of cybercriminals. Drawing from psychology, sociology, and criminology, the research examines the intricate interplay of individual traits, social dynamics, and technological factors that shape cybercriminal activities.

Through analysis of case studies and research, this paper uncovers the diverse range of motivations driving individuals towards engaging in cybercrime. From financial gain and ideological extremism to thrill-seeking and revenge, cybercriminals exhibit …

Data Profits Vs. Privacy Rights: Ethical Concerns In Data Commerce, Amiah Armstrong

Cybersecurity Undergraduate Research Showcase

In today’s digital age, the collection and sale of customer data for advertising is gaining a growing number of ethical concerns. The act of amassing extensive datasets encompassing customer preferences, behaviors, and personal information raises questions of its true purpose. It is widely acknowledged that companies track and store their customer’s digital activities under the pretext of benefiting the customer, but at what cost? Are users aware of how much of their data is being collected? Do they understand the trade-off between personalized services and the potential invasion of their privacy? This paper aims to show the advantages and disadvantages …

Machine Learning Radio-Frequency-Based Anomaly Detection For Ground Station And Satellite Telecommunication, Raffaele Bua, Lucia Necchi, Pietro Corrado, Matteo Cappella, Bérenger Villat, Giovanni Pandolfi

Small Satellite Conference

Satellite-to-ground station telecommunication is a crucial aspect of satellite missions, representing a single point of failure of the entire space system.

Each failed contact is an issue for all satellite missions, leading to a potential data loss. The detection and forecasting of data transfer failures are critical challenges in satellite operations, given the unpredictability and variety of potential causes for such anomalies.

Considering the spectral waterfall plot the most appropriate tool to describe the anatomy of satellite contacts, an automatic waterfall analysis could help satellite mission operators, by promptly discovering potential data transmission failures between satellites and ground stations, and …

Uc-388 Quantum Computing In Cybersecurity Related Data Analysis : A Comparative Analysis Of Classical And Quantum Machine Learning Models On Various Security Threats, Ryan Lowhorn, Zac Cardwell

C-Day Computing Showcase

Financial fraud has become an increasingly prevalent and sophisticated issue in the modern world, causing significant losses for individuals, businesses, and economies alike. The exponential growth of digital transactions has only accelerated the need for effective and efficient fraud detection systems to safeguard these financial ecosystems. Traditional machine learning techniques, such as Neural Networks (NNs), K-Nearest Neighbors (KNN), and Support Vector Machines (SVM), have played a crucial role in mitigating the impact of fraud by employing advanced algorithms to identify and prevent fraudulent transactions. With the recent advent of quantum computing and its potential to revolutionize the field of machine …

P-01 Financial Reporting Fraud: How Merger And Acquisition Complexity Provide Greater Opportunities For Ceos To Engage In Wrongdoing, Carmelita J. Troy, Jong Chool Park, Madeline Domino

Celebration of Research and Creative Scholarship

Using mergers and acquisitions (M&As) as a proxy to increase organizational complexity, we build upon Schnatterly et al.’s (2018) framework to addresses the gap in the management literature relating to how major firm disruptions, such as M&As, provide greater opportunities to entrenched CEOs for financial statement fraud due to higher levels of complexity. We extend the research on complexity-based information asymmetries (Ndofor et al. 2015) by empirically investigating whether accounting fraud is linked to M&As using a diverse set of variables. We propose the complex nature of M&A transactions result in higher information asymmetry, which provides a “veil” for self-interested …

Gr-175 - Credit Default Prediction Of Money Borrowing Companies Using Pyspark Framework, Jitendra Sai Kota, Mallika Boyapati

C-Day Computing Showcase

Credit-lending companies have resorted to the use of Machine Learning algorithms in the recent past to predict the probability of default of a customer for future credit lending purposes. Most credit companies view this as a binary classification problem of predicting whether an individual would default or not. Companies have been using models of Logistic Regression for a long time because of the explainability of the final feature set used in modeling. Explainability brings transparency to every stakeholder involved in the process. Other models like Neural Nets have achieved better accuracy scores, but the features generated by them are not …

A Survey Of Serious Games For Cybersecurity Education And Training, Winston Anthony Hill Jr., Mesafint Fanuel, Xiaohong Yuan, Jinghua Zhang, Sajad Sajad

KSU Proceedings on Cybersecurity Education, Research and Practice

Serious games can challenge users in competitive and entertaining ways. Educators have used serious games to increase student engagement in cybersecurity education. Serious games have been developed to teach students various cybersecurity topics such as safe online behavior, threats and attacks, malware, and more. They have been used in cybersecurity training and education at different levels. Serious games have targeted different audiences such as K-12 students, undergraduate and graduate students in academic institutions, and professionals in the cybersecurity workforce. In this paper, we provide a survey of serious games used in cybersecurity education and training. We categorize these games into …

Gender Difference In White-Collar Crime And The Importance Of Gender Diversity, Alexa Malerba

Academic Festival

Edwin H. Sutherland, who served as the 29th President of the American Sociological Society delivered his lecture, “White-Collar Criminality,” at the organization's annual meeting in December, 1939. He defined white-collar crime as, “a crime committed by a person of respectability and high status in the course of his occupation” (Sutherland, 1967; emphasis added). The gender-specific definition has since changed, but white-collar crime remains the same. Crimes committed by white-collar workers are typically non-violent crimes, ranging from accounting schemes which misinform auditors and investors about a company’s financial position, Ponzi schemes, and insider trading fraud involving large sums of money. Also …

Protection Of Privacy And Banking Secrecy In Swiss Banking, Bashkim Nuredini, Vesna Paunkoska Dodevska

UBT International Conference

Despite being one of the most developed and regulated countries in the world, Switzerland is also considered to be the leading financial center in the world. Everyone agrees with the fact that banking is one of the most recognizable activities in Switzerland, and also places it among the most important international financial centers with a long tradition, stretching back to medieval times.

Swiss banking is a synonym for a banking system in which the principle of secrecy in banking is widely used. Banking secrecy as an established practice is based on the fact that customer data is kept secret for …

Towards A Development Of Predictive Models For Healthcare Hipaa Security Rule Violation Fines, Jim Furstenberg, Yair Levy

KSU Proceedings on Cybersecurity Education, Research and Practice

The Health Insurance Portability and Accountability Act’s (HIPAA) Security Rule (SR) mandate provides a national standard for the protection of electronic protected health information (ePHI). The SR’s standards provide healthcare covered entities (CEs’) flexibility in how to meet the standards because the SR regulators realized that all health care organizations are not the same. However, the SR requires CEs’ to implement reasonable and appropriate safeguards, as well as security controls that protect the confidentiality, integrity, and availability (CIA) of their ePHI data. However, compliance with the HIPAA SR mandates are confusing, complicated, and can be costly to CEs’. Flexibility in …

Df 2.0: Designing An Automated, Privacy Preserving, And Efficient Digital Forensic Framework, Robin Verma, Jayaprakash Govindaraj, Gaurav Gupta

Annual ADFSL Conference on Digital Forensics, Security and Law

The current state of digital forensic investigation is continuously challenged by the rapid technological changes, the increase in the use of digital devices (both the heterogeneity and the count), and the sheer volume of data that these devices could contain. Although it is not directly related to the performance of Digital Forensic Investigation process, preventing data privacy violations during the process is also a big challenge. The investigator gets full access to the forensic image including suspect's private data which may be sensitive at times as well as entirely unrelated to the given case under investigation. With a notion that …

Monitor’S Report Regarding Compliance By Defendants Ocwen Financial Corporation And Ocwen Loan Servicing, Llc For The Reporting Periods Ended September 30, 2016, December 31, 2016 And March 31, 2017, Consumer Financial Protection Bureau, Et Al. V. Ocwen Financial Corporation And Ocwen Loan Servicing, Llc

National Mortgage Settlements Digital Archive

No abstract provided.

Digital Forensics Tool Selection With Multi-Armed Bandit Problem, Umit Karabiyik, Tugba Karabiyik

Annual ADFSL Conference on Digital Forensics, Security and Law

Digital forensics investigation is a long and tedious process for an investigator in general. There are many tools that investigators must consider, both proprietary and open source. Forensics investigators must choose the best tool available on the market for their cases to make sure they do not overlook any evidence resides in suspect device within a reasonable time frame. This is however hard decision to make, since learning and testing all available tools make their job only harder. In this project, we define the digital forensics tool selection for a specific investigative task as a multi-armed bandit problem assuming that …

Paper Session Ii: Computer Forensics Field Triage Process Model, Marcus K. Rogers, James Goldman, Rick Mislan, Timothy Wedge, Steve Debrota

Annual ADFSL Conference on Digital Forensics, Security and Law

With the proliferation of digital based evidence, the need for the timely identification, analysis and interpretation of digital evidence is becoming more crucial. In many investigations critical information is required while at the scene or within a short period of time - measured in hours as opposed to days. The traditional cyber forensics approach of seizing a system(s)/media, transporting it to the lab, making a forensic image(s), and then searching the entire system for potential evidence, is no longer appropriate in some circumstances. In cases such as child abductions, pedophiles, missing or exploited persons, time is of the essence. In …