Digital Commons Network^™

Improving Credit Card Fraud Detection Using Transfer Learning And Data Resampling Techniques, Charmaine Eunice Mena Vinarta

Electronic Theses, Projects, and Dissertations

This Culminating Experience Project explores the use of machine learning algorithms to detect credit card fraud. The research questions are: Q1. What cross-domain techniques developed in other domains can be effectively adapted and applied to mitigate or eliminate credit card fraud, and how do these techniques compare in terms of fraud detection accuracy and efficiency? Q2. To what extent do synthetic data generation methods effectively mitigate the challenges posed by imbalanced datasets in credit card fraud detection, and how do these methods impact classification performance? Q3. To what extent can the combination of transfer learning and innovative data resampling techniques …

The Economics Of Financial Scams: Evidence From Initial Coin Offerings, Kenny Phua, Bo Sang, Chi Shen Wei, Gloria Yang Yu

Research Collection Lee Kong Chian School Of Business

We examine the economics of financial scams by analyzing the market for initial coin offerings (ICOs). Using data snapshots of 5,873 ICOs, we find that irregularities in ICO characteristics across listing websites predict higher scam risk and are likely intentional. These patterns are consistent with a model where malicious issuers maximize profits by using irregularities to screen for naïve investors. Almost half of the ICOs in our sample may be scams, amounting to more than U.S. $6 billion in losses. Our results draw attention to the frequent use of screening mechanisms in financial scams.

Ercole A. Mirarchi V. United States Executive Branch Of The Government

2023 Decisions

USDC for the Eastern District of Pennsylvania

Consumer Harms Arising From The Competition Dynamic Of E-Commerce Platforms In Malaysia, Tze Chin Ong Dr, Mei Fei Lee Ms., Norhoneydayati Abdul Manap, Zalina Abdul Halim Dr., Sridevi Thambapillay

International Journal on Consumer Law and Practice

The structure of the digital market of e-commerce platforms is dynamic, with a combination of characteristics such as strong network effects, concentrated multi-sided platforms, extreme economies of scale and scope, low marginal costs, and high data returns. These strong network externalities within the multisided e-commerce market make the competitive environment in e-commerce significantly different from the conventional monogamous market as they create gatekeeper positions favouring a few incumbent e-commerce platforms. In these circumstances, gatekeeper incumbent e-commerce platforms often set commercial conditions that have the effect of undermining other players and potential rivals within the ecosystem. In this regard, there has …

The Age Of Synthetic Realities: Challenges And Opportunities, João Phillipe Cardenuto, Jing Yang, Rafael Padilha, Renjie Wan, Daniel Moreira, Haoliang Li, Shiqi Wang, Fernanda Andaló, Sébastien Marcel, Anderson Rocha

Computer Science: Faculty Publications and Other Works

Synthetic realities are digital creations or augmentations that are contextually generated through the use of Artificial Intelligence (AI) methods, leveraging extensive amounts of data to construct new narratives or realities, regardless of the intent to deceive. In this paper, we delve into the concept of synthetic realities and their implications for Digital Forensics and society at large within the rapidly advancing field of AI. We highlight the crucial need for the development of forensic techniques capable of identifying harmful synthetic creations and distinguishing them from reality. This is especially important in scenarios involving the creation and dissemination of fake news, …

Deciphering Trends And Tactics: Data-Driven Techniques For Forecasting Information Spread And Detecting Coordinated Campaigns In Social Media, Kin Wai Ng Lugo

USF Tampa Graduate Theses and Dissertations

The main objective of this dissertation is to develop models that predict and investigate the spread of information in social media over time. In this context, we consider topics of discussions as the information that spreads. Thus, we are interested in forecasting the number of messages per day in a future interval of time. We take a data-driven approach, in which we compare our results with real datasets from a multitude of socio-political contexts and from multiple social media platforms, specifically, Twitter and YouTube.

We identified a number of challenges related to forecasting social media time series per topic. First, …

Optimizing E-Payment Applications For Older Adults: User-Centered Solutions To Improve Security, Privacy, Usability, And Accessibility, Urvashi Kishnani

Electronic Theses and Dissertations

In an increasingly digital world, older adults are rapidly becoming a vital demographic in the realm of electronic financial transactions. It is imperative to address their unique needs and challenges to ensure their financial well-being. Older adults can be more vulnerable to various online threats, making security and privacy paramount. As they adapt to the digital age, understanding their specific privacy concerns and preferences is crucial for creating trustworthy e-payment systems. Moreover, enhancing the usability of e-payment applications for older adults promotes financial independence and inclusion, contributing to their overall quality of life. By focusing on these critical dimensions, we …

Mitigating Industry Contagion Effects From Financial Reporting Fraud: A Competitive Dynamics Perspective Of Non-Errant Rival Firms Exploiting Product-Market Opportunities, Eugene Kang, Nongnapat Thosuwanchot, David Gomulya

Research Collection Lee Kong Chian School Of Business

Existing studies show that financial reporting frauds by errant firms cause declines in stock market valuations for non-errant rival firms (i.e. industry contagion effects). We posit that contagion effects may be mitigated by investors’ expectations of non-errant rivals exploiting product-market opportunities at the expense of errant firms. We apply the competitive dynamics literature to argue that non-errant rivals experience lower contagion effects when they have more available slack to engage in competitive actions. This effect is expected to strengthen when rival firms have previously deployed more resources for research and development and advertising investments or have higher prior market share …

Rule Violation And Time-To-Enforcement In Weak Institutional Environments: A Good Faith Perspective, Jun Xia, Yusi Jiang, Heli Wang, Yuan Li

Research Collection Lee Kong Chian School Of Business

Previous studies on corporate misconduct have focused mainly on preventing misconduct or remedying it after detection, but it remains unclear how misconduct can be effectively detected in the first place once it occurs. We apply the good faith perspective in the context of China, which represents a weak institutional environment, and argue that the ability of culpable leaders to conceal information may delay misconduct disclosure because such ability helps maintain the good faith of regulators. Moreover, we argue that because the regulators have faith in professionals (external auditors, institutional investors, and securities analysts) whose skills are in fact often underdeveloped …

Corporate Social Responsibility May Induce Unethical Choices In Leaders, Aaron Sanborn

UNH Today Archive

No abstract provided.

Executive Pay Clawbacks And Their Taxation, David I. Walker

Florida Tax Review

Executive pay clawback provisions require executives to repay previously received compensation under certain circumstances, such as a downward adjustment to the financial results upon which their incentive pay was predicated. The use of these provisions is on the rise, and the SEC is expected to soon finalize rules implementing a mandatory, no-fault clawback requirement enacted as part of the Dodd-Frank legislation. The tax issue raised by clawbacks is this: should executives be allowed to recover taxes previously paid on compensation that is returned to the company as a result of a clawback provision? This Article argues that a full tax …

Enterprise, Liability, And Insolvency: An Essay In Honor Of Aaron Twerski, Edward Janger

Faculty Scholarship

No abstract provided.

Voucher Abuse Detection With Prompt-Based Fine-Tuning On Graph Neural Networks, Zhihao Wen, Yuan Fang, Yihan Liu, Yang Guo, Shuji Hao

Research Collection School Of Computing and Information Systems

Voucher abuse detection is an important anomaly detection problem in E-commerce. While many GNN-based solutions have emerged, the supervised paradigm depends on a large quantity of labeled data. A popular alternative is to adopt self-supervised pre-training using label-free data, and further fine-tune on a downstream task with limited labels. Nevertheless, the "pre-train, fine-tune" paradigm is often plagued by the objective gap between pre-training and downstream tasks. Hence, we propose VPGNN, a prompt-based fine-tuning framework on GNNs for voucher abuse detection. We design a novel graph prompting function to reformulate the downstream task into a similar template as the pretext task …

Advance Fee Fraud On The Increase: The Shield Of Support Over The Victims, Ovenseri Ven Ogbebor

Doctoral Dissertations and Projects

This research study addresses the activities of Advance Fee Fraudsters whose activities sometimes impact the status and life of their victims. Research to date appears to have focused on crime, Advance Fee Fraud, and its techniques. The intent of this study is to take the reader through the various types of Advance Fee Fraud (AFF) with special attention to how the victims may get help, an aspect of AFF that has been greatly neglected by previous researchers who mainly focus on the techniques and modus operandi of the fraudsters. Until recently, the concept of AFF was limitedly known, but with …

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. …

Indonesian Capital Market Investor Protection In Cases Of Embezzlement, Arman Nefi, Adiwarman Adiwarman

Indonesia Law Review

Law Number 8 of 1995 on Capital Market, in Articles 90 to 98, regulates fraud, market manipulation and insider trading. There is no regulation of embezzlement in the Indonesian Capital Market. Have the legislators forgotten, or have anticipated that there will never be embezzlement in the legal realm of the Indonesian Capital Market? The paper deals with the absent of criminalization of embezzlement in capital market act and produce the recommendation to cope with the issue. This study uses a normative legal analysis method with a conceptual, an analytical, and a case study approach. Several legal cases that are strongly …

Victimization By Deepfake In The Metaverse: Building A Practical Management Framework, Julia Stavola, Kyung-Shick Choi

International Journal of Cybersecurity Intelligence & Cybercrime

Deepfake is digitally altered media aimed to deceive online users for political favor, monetary gain, extortion, and more. Deepfakes are the prevalent issues of impersonation, privacy, and fake news that cause substantial damage to individuals, groups, and organizations. The metaverse is an emerging 3-dimensional virtual platform led by AI and blockchain technology where users freely interact with each other. The purpose of this study is to identify the use of illicit deep fakes which can potentially contribute to cybercrime victimization in the metaverse. The data will be derived from expert interviews (n=8) and online open sources to design a framework …

Toward A Multilevel Sociology Of Fraud, Brooke Harrington, Camilo Arturo Leslie

Northwestern University Law Review

This Essay applies a distinctively sociological multilevel analysis to fraud to provide novel insights and recommendations on an old problem. Rather than treating fraud as a problem of “criminogenic environments” or of individual psychologies and motivations, this multilevel analysis investigates the ways in which individuals (the micro level) interact with organizations (the meso level) and institutional systems (the macro level) to produce fraud. We illustrate these interactions and the insight that an interactive analysis can provide by using ethnographic data from an in-depth case study of the R. Allen Stanford offshore financial fraud. The case, which occurred in the Caribbean …

The Persistent Limits Of Fraud Prevention In Historical Perspective, Emily Kadens

Northwestern University Law Review

Fraud has been ubiquitous throughout history, and so have the methods of fraud prevention. History demonstrates that no anti-fraud measures have fully succeeded in eliminating deceptive market behavior. Instead, this Essay uses evidence from premodern England to argue that societies and individual contracting parties balance tolerating a certain amount of fraud against the costs of fraud prevention.

Auditing Overseas: How The United States Can Learn From Recent Financial Audit Reform In The United Kingdom, Daniel Damitio

Northwestern University Law Review

Financial auditing is one of the cornerstones of an effective capital market structure. When performed correctly, an independent financial audit provides investors with the security they need to effectively transact based on company disclosures. When this system fails, however, the results for investors and the economy as a whole can be devastating. In recognition of this danger, the market for financial auditing in the United States is regulated by a number of governmental and nongovernmental bodies charged with maintaining its health and effectiveness. But stakeholders within the U.S. market and government have criticized these regulators for failing to adequately respond …

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 …

The Impact Of The Digital Revolution On The Efficiency Of Auditors In Auditing Computerized Programs, R. Alkabbji, T. H. Almubaydeen, T. Qushtom, M. Hamza

Information Sciences Letters

This study aimed to research the impact of the digital revolution and its various fields, secrets, and ramifications on the auditors efficiency in auditing computerized programs that precede auditing financial statements, and to ensure their integrity to give an impartial technical opinion. To achieve the study objectives, a questionnaire comprising of 16 sections was created and distributed to two groups: auditors in Jordan and computerized program administrators. Each group was allocated 100 questionnaires, with 70 and 80 questionnaires retrieved from the first and second group respectively. Statistical analysis using the SPSS program was conducted to extract the mean and standard …

Exploring The Impact Of Hexagon Fraud Theory On Fraud Tendencies Among Regional Work Unit Employees In Bandung City: A Quantitative Analysis, Andini Dwiyanti, Nunuy Nur Afiah, Ivan Yudianto

Journal of Accounting Auditing and Business

This research aimed to analyze the effect of the hexagon fraud theory on fraud tendencies based on the perceptions of regional work unit employees in Bandung City. This research used a quantitative approach. The sample was 364 regional work unit employees in Bandung City. A simple random sampling method was used in this research. Data were analyzed using multiple linear regression. The results of this research indicated that the variables of distributive justice (proxy of stimulus), collusion, and internal control (proxy of opportunity) have a negative and significant effect on fraud tendencies. Meanwhile, the variables of leadership style (proxy of …

Increasing The Efficiency And Accuracy Of Collective Intelligence Methods For Image Classification, Md Mahmudulla Hassan

Open Access Theses & Dissertations

Collective intelligence has emerged as a powerful methodology for annotating and classifying challenging data that pose difficulties for automated classifiers. It works by leveraging the concept of "wisdom of the crowds" which approximates a ground truth after aggregating experts' feedback and filtering out noise. However, challenges arise when certain applications, such as medical image classification, security threat detection, and financial fraud detection, demand accurate and reliable data annotation. The unreliability of experts due to inconsistent expertise and competencies, coupled with the associated cost and time-consuming judgment extraction, presents additional challenges.

Input aggregation is the process of consolidating and combining multiple …

Invading The Integrity Of Deep Learning (Dl) Models Using Lsb Perturbation & Pixel Manipulation, Ashraful Tauhid

Theses and Dissertations

The use of deep learning (DL) models for solving classification and recognition-related problems are expanding at an exponential rate. However, these models are computationally expensive both in terms of time and resources. This imposes an entry barrier for low-profile businesses and scientific research projects with limited resources. Therefore, many organizations prefer to use fully outsourced trained models, cloud computing services, pre-trained models are available for download and transfer learning. This ubiquitous adoption of DL has unlocked numerous opportunities but has also brought forth potential threats to its prospects. Among the security threats, backdoor attacks and adversarial attacks have emerged as …

Ai Techniques For Combating Electronic Crimes And Enhancing Cybersecurity: Kuwaits Security Services As A Model, Nassereldin A. Osman, Mohammad M. Alshammari, Tarek I. Mohamed

Information Sciences Letters

The research aimed to examine the security agencies use of artificial intelligence (AI) techniques in combating cybercrime and its reflection on enhancing cyber security. The study used the survey method in its descriptive and analytical levels. The interview tool was used to collect information from the research sample, the size of which was 12 items. The research found a set of results where the respondents declared the presence of an anti- cybercrime team comprised of specialists in police sciences, engineering, information systems, and network engineering. They added that using AI enables specialists in security agencies to benefit from its enormous …

Application Of Machine Learning Algorithm For Creating Sustainable Omni-Channel Retail Ecosystem, Somedip Karmakar, Anuja Shukla

Management Dynamics

The retail ecosystem has evolved from simple Kirana stores to large omni-channel retail systems. The advent of omni-channel retailing has seen an increased count of fraudsters who can abuse the gap between the online and offline channels to perform different types of fraudulent activities. Fraud can be related to payment, account take over, refund and cancellation abuse, collusion of customers with associates. Waste can be due to over-production, sub-optimal pricing or discounts, damaged products, throwaways, availability issues, packaging waste. The paper tries to identify the need for better research on improvement in fraud detection systems for sparse data, improvement of …

Risk Assessment Approaches In Banking Sector –A Survey, Mona Sharaf, Shimaa Mohamed Ouf, Amira M. Idrees Ami

Future Computing and Informatics Journal

Prediction analysis is a method that makes predictions based on the data currently available. Bank loans come with a lot of risks to both the bank and the borrowers. One of the most exciting and important areas of research is data mining, which aims to extract information from vast amounts of accumulated data sets. The loan process is one of the key processes for the banking industry, and this paper examines various prior studies that used data mining techniques to extract all served entities and attributes necessary for analytical purposes, categorize these attributes, and forecast the future of their business …

Unveiling The Digital Shadows: Cybersecurity And The Art Of Digital Forensics, Derek Beardall

Cyber Operations and Resilience Program Graduate Projects

This paper navigates the symbiotic relationship between cybersecurity and digital forensics, exploring the profound role of digital forensic methodologies in addressing cyber incidents. Beginning with foundational definitions and historical evolution, this study delves into diverse types of methodologies and their applications across law enforcement and cybersecurity domains. The mechanics of cyber incident response illuminates the strategic orchestration of digital forensic methodologies. Amidst triumphs, challenges emerge from the shadows: swift threat evolution, digital ecosystem complexity, standardization gaps, resource limitations, and legal intricacies. Best practices guide experts through this intricate terrain, culminating in an enhanced understanding of the inseparable bond between cybersecurity …

Place-Based Versus Practice-Based Norms For American Lawyers: "It's The End Of The World As We Know It (And I Feel Fine)", James E. Moliterno

South Carolina Law Review

No abstract provided.