Digital Commons Network^™

The Impact Of The 2008 Financial Crisis On Crime And Cybercrime In The United States, Rashed Adel Alsuwaidi

Theses

This thesis will examine how the traditional crime and cy- were affected by the 2008 financial crisis. United States are also experiencing a rise in crime between 2005 and 2012. Based on the FBI data at the national level. The Internet Crime Complaint Center (IC3), Uniform Crime Reports and important economic indicators. The study, which involves tors, including unemployment, GDP, rates of foreclosures, and mortgage rates, is a combination. correlationbased interpretation supported by exploratory descriptive trend analysis. model-fit checks. The results indicate that contrary to the conventional expectations, violent and property crime also maintained their long-term reduction during the period …

Detecting Fraud In Police Reports Using Machine Learning And Natural Language Processing, Maryam Almarar

Theses

The paper explores how statistical analysis and machine learning can be used to identify the fraud patterns in the police reports. The study aims at establishing the most important predictive factors and indicators distinguishing fraudulent and valid cases with the use of structured data of police databases. The work was done in the background of the increase in financial fraud instances and the rising necessity of the introduction of automated detection systems in police departments. Police reports of the pastwere mined down to data and analyzed on SPSS 1, to carry out statistical operations. The sample was structured data which …

A Systematic Review Of Corporate Ethics Program Training Strategies To Improve Ethical Workplace Cultures, Robin Raye Altice

Educational Leadership & Workforce Development Theses & Dissertations

The demand for corporations to practice more ethically responsible conduct and decision making is growing with every news report of another corporate scandal, lawsuit, fine, or high-visibility C-suite firing. To develop an ethical workplace culture, organizations should implement a comprehensive ethics program that fosters and encourages ethical decision making, especially among current and future leaders. However, there is little research and few guidelines for how ethics program administrators should design corporate ethics training to effectively practice and master the skill of ethical decision-making in efforts to continually grow a more ethical work environment. This study aims to identify corporate ethics …

Rise Of Social Media Hacking: Ai-Based Ip Tracking For Uae Law Enforcement, Mounikha Naarrayen Chakravarthula

Theses

Social media has evolved into a critical channel for communication, expression, and public influence, but it has also become a prevalent avenue for cybercrime, particularly in digitally advanced nations such as the United Arab Emirates (UAE). The rising complexity of online offences, coupled with anonymisation tools and cross-border digital behaviour, has made the attribution of social-media-based cyber incidents increasingly challenging for law enforcement. In this context, artificial intelligence (AI) offers the potential to strengthen digital investigations by providing intelligent, scalable, and evidence-driven attribution capabilities. This research develops an AI-assisted Internet Protocol (IP) attribution framework tailored specifically for UAE law enforcement …

Deepfake Audio Detection, Rashed Alfalasi

Theses

The rise of deepfake audio technology has introduced a serious threat to information credibility, personal security, and media integrity. This thesis investigates the application of machine learning techniques for detecting synthetic audio through the analysis of acoustic features, including Mel-Frequency Cepstral Coefficients (MFCCs), spectral centroid, chroma_stft, and zero-crossing rate. The dataset used in this study was sourced from Kaggle and contains labeled samples of real and fake audio clips. The research aimed to train and evaluate multiple machine learning models—Support Vector Machines (SVM), Random Forest, XGBoost, Logistic Regression, and Neural Networks—to determine the most effective approach for deepfake audio classification. …

Retrieval Augmented Framework For Deepfake Audio Detection, Avinash Saxena

Master's Theses

The widespread use of AI-based audio deepfakes threatens severely to undermine media integrity and public trust. Speech synthesis techniques have improved dramatically in voice conversion (VC) and text-to-speech (TTS) in recent years, making forgeries sound highly realistic, and concerns are raised about possible malevolent uses. Existing state-of-the-art techniques for identifying fake speech have proven to be effective in some cases but are still limited in application and robustness when faced with novel attacking strategies, different acoustic conditions, or alternative linguistic domains. To address some of these limitations, the current research presents a novel deepfake audio detection system based on personalized …

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 …

Implementation Strategies For Microservice Architecture In The Banking Sector, Gururaj Achar

Walden Dissertations and Doctoral Studies

Information technology (IT) leaders in regulated banking face significant risks related to system complexity and cybersecurity when implementing large-scale systems. Although microservice architecture (MSA) offers enhanced scalability and agility, IT leaders lack specific strategic guidance for its effective adoption within highly regulated banking environments. Grounded in the Technology Acceptance Model, the purpose of this qualitative, pragmatic study was to explore effective MSA adoption strategies for IT architects and managers transitioning legacy systems to support risk and compliance management. Data were collected through semistructured interviews with seven banking IT leaders and were analysed using thematic analysis. Three themes emerged: adoption drivers …

Face Card Declined: The Deepfake Threat To Biometric Security In Financial Systems, Hazel Fernandez

Washington and Lee Law Review Online

Once limited to entertainment and disinformation, deepfakes are now extending into the financial sector, where voice and facial impersonations exploit biometric authentication systems to facilitate fraudulent transactions. This evolution exposes gaps in existing legal and regulatory frameworks, raising critical questions about consumer protection and institutional safeguards. This Note argues for a reconceptualization of deepfake harms as both a privacy and a financial security issue. It examines the illusion of consent generated by synthetic impersonation and insufficient statutory protections. The analysis examines the patchwork of federal, state, and international laws governing data privacy and artificial media, highlighting the gaps that allow …

Systematic Review Of Elementary Cybersecurity Education: Curriculum, Pedagogy, And Barriers, Na Liu, Siyu Long, Florence Martin

Journal of Cybersecurity Education, Research and Practice

Abstract -As children increasingly engage with digital platforms, the need for effective cybersecurity education has become urgent. This systematic review synthesizes 81 studies published between 2017 and 2024 to examine global curricula research focus and topics, pedagogical approaches and assessment methods, and key challenges in elementary cybersecurity education. The findings reveal six major thematic categories: student awareness, parental mediation, teacher engagement, curriculum design, community and policy support, and pedagogical innovation. Among instructional strategies, game-based learning and narrative storytelling emerge as the most frequently explored. Despite this growth, major gaps remain in curriculum consistency, teacher preparation, assessment rigor, and stakeholder coordination. …

Does A Ceo Turnover Lead To A Cfo Turnover? Evidence From Voluntary And Forced Turnover, Bakhtear Talukdar, Sabur Mollah, Suchismita Mishra, Junhong Yang

Management Faculty Publications

The role of CFO has become increasingly important since the enactment of SOX 2002. The existing literature suggests that CFOs tend to leave office within 6 to 12 months of a CEO’s departure, but studies addressing whether forced and voluntary turnover behave differently are unexplored. There is also no attempt to explore whether financial performance or institutional shareholding play moderating roles in mitigating successive CFO and CEO turnovers. These scholars find that forced (voluntary) CEO turnover has a higher significant marginal effect on forced (voluntary) CFO turnover. They also find that, in general, higher financial performance and institutional ownership play …

Bridging The Expectations Gaap In Financial Reporting, Neal F. Newman

Faculty Scholarship

The true nature of auditing publicly traded companies’ financial statements has been somewhat of an enigma to the general public. Due to this mystery, an “expectations gap” has formed between the public expectations of auditors’ roles and what the auditor actually does in their analysis of financial statements. Auditors are an extremely important piece of the financial reporting puzzle because they determine whether or not a company’s financial statements are a fair and accurate reflection of the company’s financial position, a determination that can be a major influence on how the financial strength of a company is perceived. Newman’s Article …

Foreign Director Exit In The Midst Of Deteriorating Bilateral Political Relations, Xiaocong Tian, Yuehua Xu, Daphne W. Yiu

Research Collection Lee Kong Chian School Of Business

Amid global geopolitical realism pushing for a race of hegemonic rivalry nowadays, an outflow of global human talents is a pressing organizational concern. Our study draws attention to the underexamined phenomenon of the exit of foreign directors from their host countries during geopolitical tensions. Theorizing from a sensemaking logic, we posit that the deterioration of bilateral political relations serves as an unexpected event that activates foreign directors’ schemas for dual identity conflict, propelling them to react behaviorally to such identity threats by exiting the board in the host country. In addition, we further posit that the sensemaking process is contingent …

User Privacy In The Digital Playground: An In-Depth Investigation Of Facebook Instant Games, Sideeq Bello

LSU Master's Theses

Amid growing concerns over data privacy in web and mobile applications, this study aims to assess the privacy mechanisms in instant games on Facebook, a platform with approximately 3.03 billion monthly active users and a substantial repository of personal data. Instant Games have become increasingly popular due to their ease of access and social integration features. Investigating these games can provide insights into privacy mechanisms and practices, thereby informing the development of more fair, compliant, and user privacy-centric gaming experiences. Thus, this study proposes an integrated analytical framework that leverages a combination of descriptive, memory, and network analysis techniques to …

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 …

Web3-Based Identity And Kyc Innovations For Next-Generation Fintech, Usama Arshad, Abdallah Tubaishat, Sajid Anwar, Zahid Halim, Abedallah Abualkishik, Abrar Ullah

All Works

The growing reliance on digital financial services necessitates a secure, efficient, and privacy-centric approach to identity verification and Know Your Customer (KYC) compliance. Traditional identity management systems rely on centralized databases, making them susceptible to data breaches, inefficiencies, and regulatory constraints. Over 10 billion identity records have been exposed in centralized KYC breaches, leading to a 60% increase in financial fraud cases. The rise of Decentralized Finance (DeFi) has further complicated KYC compliance, requiring innovative solutions that balance privacy and regulatory requirements. This paper proposes a Web3-powered decentralized identity framework that leverages blockchain technology, self-sovereign identity (SSI), verifiable credentials (VCs), …

Examining Iot-Enhanced For Current Developments In Face Image Authentication (Fia) Methods And Their Drawbacks, Marwa Jamal Hadi, Emaan Ouudha Oraby

Al-Esraa University College Journal for Engineering Sciences

The quick development of IoT and facial image manipulation (FIM) algorithms, as well as the growth of their user-friendly applications, highlight the pressing need for manipulation detection methods. These techniques need to demonstrate how face photos have been altered and validate their legitimacy. The scientific community has recently taken notice of the phrase “DeepFakes” and methods for detecting them. Take note of the latest methods for identifying watermark-based face image modification as well. The important thing to remember is that every one of these methods has its own set of drawbacks. This study provides a brief introduction to face image …

Emotionally Unstable: Addressing Emotional Distress As A Concrete Injury In Data Breach Cases Post-Transunion, Anna P. Cox

Fordham Law Review

Data breaches and data breach litigation are exponentially on the rise. Plaintiffs whose information is stolen in a data breach often claim emotional distress for fear of future harm the data breach may cause. However, plaintiffs who bring suit in federal court must show that they have suffered an injury in fact for purposes of Article III standing before a federal court will exercise jurisdiction. The U.S. Supreme Court’s decision in TransUnion LLC v. Ramirez requires that plaintiffs who seek money damages under a theory of risk of future harm show that they have suffered a present concrete injury to …

Assessing Market Efficiency In Corporate And Securities Litigation, Charles Korsmo, Minor Myers

Indiana Law Journal

In recent decades, courts have increasingly looked to trading prices as evidence—often conclusive evidence—in high-stakes corporate law disputes over a company’s fair value. This development has been especially dramatic, and consequential, in Delaware. Where a stock trades in an efficient market, the logic goes, the prevailing trading price can be used to resolve any disputed issue of valuation. But this expedient comes with an unavoidable question: When is a market “sufficiently efficient” for a court to rely on it as a measure of value?

 Federal courts have long experience evaluating the relative efficiency of trading markets in the context of …

Future Crime: A Theoretical Foundation For Designing Effective Cybercrime Laws In The Age Of Ai And Ransomware, Thi Ha Do, Niloufer Selvadurai

North Carolina Journal of Law & Technology

No abstract provided.

A Comprehensive Review Of Financial Knowledge Graphs, Jeyaraman Brindha Priyadarshini, Bing Tian Dai, Yuan Fang

Research Collection School Of Computing and Information Systems

Knowledge Graphs (KGs) are increasingly used in finance to manage complex, interconnected data and support advanced analytics. This survey provides an overview of how KGs are applied across various financial areas, such as fraud detection, credit risk assessment, anti-money laundering, and regulatory compliance. We examine key techniques for building and using KGs in finance, including graph construction, embedding methods, and machine learning models. The survey also discusses challenges specific to finance, like handling private data, ensuring interpretability, and managing real-time data. Additionally, we explore the emerging combination of KGs with large language models and generative AI, which offers new possibilities …

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 …

A Federated Approach To Scalable And Trustworthy Financial Fraud Detection, Yaser Alhasawi, Aljwhrh Abdalaziz Almtrf, Muhammad Asad

School of Engineering, Computing and Mathematics

Financial fraud remains a critical challenge for digital banking, requiring detection solutions that ensure both scalability and data privacy. Traditional centralized approaches face limitations due to security risks and system bottlenecks. This paper proposes FedFraud, a novel federated learning (FL) framework that detects fraudulent transactions without sharing raw data. FedFraud introduces two key innovations: (i) a trust-aware client aggregation mechanism that assigns weights based on update reliability and (ii) an asynchronous communication protocol enabling clients to contribute updates independently. Evaluated on the Credit Card Fraud Detection dataset under a nonidentically distributed (non-IID) data setting where client data distributions differ significantly, …

Gun Violence Declines Came Through Strategic Planning And Community Focus (Op-Ed), Alvin Bragg

Other Publications

No abstract provided.

Older Adults And Financial Exploitation, Aaron Li, Natalie Galucia, Cal J. Halvorsen

Harvey A. Friedman Center for Aging

The National Adult Protective Services Association defines elder financial exploitation as misuse, mishandling, or exploitation of an older adult’s property, possession, or assets. These actions often occur without consent and are typically carried out through false pretense, undue influence, coercion, or manipulation.

Ponzilens+: Visualizing Bytecode Actions For Smart Ponzi Scheme Identification, Xiaolin Wen, Tai D. Nguyen, Shaolun Ruan, Qiaomu Shen, Jun Sun, Feida Zhu, Yong Wang

Research Collection School Of Computing and Information Systems

With the prevalence of smart contracts, smart Ponzi schemes have become a common fraud on blockchain and have caused significant financial loss to cryptocurrency investors in the past few years. Despite the critical importance of detecting smart Ponzi schemes, a reliable and transparent identification approach adaptive to various smart Ponzi schemes is still missing. To fill the research gap, we first extract semantic-meaningful actions to represent the execution behaviors specified in smart contract bytecodes, which are derived from a literature review and in-depth interviews with domain experts. We then propose PonziLens+, a novel visual analytic approach that provides an intuitive …

Identifying Potentially Illicit Money Laundering And Terrorism Financing Transactions Through Machine Learning Techniques, Shiuh Tong Lim, Rou Qing Khoo, Khai Wah Khaw, Xinying Chew

International Journal of Management, Finance and Accounting

Financial institutions worldwide face significant challenges in detecting and preventing illicit financial activities, such as money laundering and terrorism financing. Traditional rule-based methods often generate high false positive rates, increasing manual verification efforts and higher operational costs. This research explores machine learning techniques to enhance the detection of suspicious transactions. Several algorithms, including K-Nearest Neighbors, Decision Tree, Random Forest, Logistic Regression, Support Vector Machine, and Naïve Bayes, are applied and evaluated using a dataset from a financial institution. After a comprehensive performance assessment, the Random Forest model is the most effective, exhibiting the highest accuracy of 0.9333 in identifying suspicious …

An Envisioned And Efficient Design Of Next Generation Decentralized Iot Bot Detection Model, Ahmed Abdullah Almalki

Doctoral Dissertations

The Industrial Internet of Things (IIoT) and Internet of Medical Things (IoMT) are revolutionizing critical infrastructures, but their expansion has also introduced severe cybersecurity vulnerabilities. Traditional IoT Bot Detection Systems (IBDS) struggle to scale in environments characterized by high-dimensional, large-scale, and redundant network traffic. These challenges hinder the development of reliable cloud-based intrusion detection systems. The limitations of static and rulebased methods in detecting evolving IoT botnet attacks—such as those launched by Mirai and Gafgyt—underscore the need for intelligent, adaptive approaches. To address this, the present study proposes a machine learning and deep learning-driven IoT Botnet Detection Model, validated through …

Generating Financial Risk Tiers For Geo-Located Entities Using Monetary Claims From User-Generated Content And Transactional Signals, Mithun Kumar S R

Defensive Publications Series

Moderation systems for local business platforms may have difficulty identifying certain types of financial fraud, such as overcharging or fake deposit scams, because of challenges in validating monetary claims found in user-generated content (UGC). A disclosed method can address this potential limitation by synthesizing two different data streams. A system can use technologies, for example natural language processing and computer vision, to extract unstructured financial claims and pricing information from UGC, which may include content such as text reviews and photos of menus or receipts. The system can then correlate these claims with structured, verified transactional signals from integrated payment …

Design And Development Of Machine Learning And Deep Learning Based Algorithms For Cyberattacks Detection, Abiramasundari S

Theses and Dissertations

E-mail is the fastest mode of communication. It is amongst the most commonly used modes of communication and can be used for both legal and illegal purposes. Many elements that could be useful in detecting email fraud are constantly being investigated. Phishing assaults in which thieves use Internet to trick consumers into visiting fake websites are very common and are causing significant harm to victims. Several methods of filtering phishing emails have been devised but a solution to the problem still evades. One of the attacks addressed in this research is email phishing. Machine learning is a popular and efficient …