Digital Commons Network^™

The Role Of Trust In Advice Acceptance From Non-Human Actors, Rahul Banerjee

Dissertations and Theses Collection (Open Access)

Advancements in technology are now allowing non-human actors in the form of robot-advisors, driverless cars, medical assistants to perform increasingly complex tasks. While technological change is as old as civilization, these non-human actors can do novel tasks. One such task is that they provide advice which is a credence service (Dulleck, & Kerschbamer, 2006). Using a financial services context this thesis studies the role trust plays in advice acceptance.

Robo-advisors are rapidly replacing human financial advisors as the agent-provider for portfolio investment services. For centuries, it was the banker (human financial advisor) who was responsible for providing his investors with …

Impact Of Information Breaches On Health Care Records, Anton Antony Arockiasamy

Walden Dissertations and Doctoral Studies

Although there were almost 3.5 million reported information breaches of health care data in the first quarter of 2019, health care providers do not know the extent of digital and nondigital breaches of patient medical records. The purpose of this quantitative, comparative study was to identify the difference between the individual patient records affected by digital versus nondigital breaches for three types of health care entities in the United States, health care providers, health care plans, and health care clearinghouses. Allman’s privacy regulation theory, the National Institute of Standards and Technology Privacy Framework, and ecological systems theory comprised the theoretical …

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

Dissertations

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

Security Awareness Strategies Used In The Prevention Of Cybercrimes By Cybercriminals, Pascal Pouani Tientcheu

Walden Dissertations and Doctoral Studies

Cybercrime is a growing phenomenon that impacts many lives worldwide. Businesses, organizations, and governments continue to search for ways to protect their data and intellectual property from cybercrimes. Grounded in the routine activity theory, the purpose of this general qualitative study was to explore strategies information security officers used to prevent cybercrimes. The participants included seven information security officers listed on social media who manage information security within organizations located in the northeast geographic region of the United States. Data were collected using semistructured interviews, the National Institute of Standards and Technology documentations and analyzed using thematic analysis. Four key …

Book Review: Computer Capers: Tales Of Electronic Thievery, Embezzlement, And Fraud. By Thomas Whiteside, Brian Nussbaum

International Journal of Cybersecurity Intelligence & Cybercrime

No abstract provided.

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 …

The Future Of Work Now: Ai-Driven Transaction Surveillance At Dbs Bank, Thomas H. Davenport, Steven M. Miller

Research Collection School Of Computing and Information Systems

One of the most frequently-used phrases at business events these days is “the future of work.” It’s increasingly clear that artificial intelligence and other new technologies will bring substantial changes in work tasks and business processes. But while these changes are predicted for the future, they’re already present in many organizations for many different jobs. The job and incumbents described below are an example of this phenomenon. Steve Miller of Singapore Management University and I co-authored the story.

Detecting Credit Card Fraud: An Analysis Of Fraud Detection Techniques, William Lovo

Senior Honors Projects, 2020-current

Advancements in the modern age have brought many conveniences, one of those being credit cards. Providing an individual the ability to hold their entire purchasing power in the form of pocket-sized plastic cards have made credit cards the preferred method to complete financial transactions. However, these systems are not infallible and may provide criminals and other bad actors the opportunity to abuse them. Financial institutions and their customers lose billions of dollars every year to credit card fraud. To combat this issue, fraud detection systems are deployed to discover fraudulent activity after they have occurred. Such systems rely on advanced …

A Data-Analytics Approach For Risk Evaluation In Peer-To-Peer Lending Platforms, Feng He, Yuelei Li, Tiecheng Xu, Libo Yin, Wei Zhang, Xiaotao Zhang

Research Collection School Of Accountancy

The goal of this article is to investigate the roles of individual behavior characteristics and Internet finance industry risk in the light of bank run theory for P2P. We know that risk evaluation is clearly important for peer-to-peer (P2P) lending platforms in China, as during the last two years, the industry has experienced thousands of platform crashes. Traditional approaches to evaluate enterprise risk are increasingly ineffective in this industry, due to the difficulty of assessing the real information. In addition, the Internet business model makes it possible to record new kinds of information. By applying a data-driven analytics method, we …

Teaching About The Dark Web In Criminal Justice Or Related Programs At The Community College And University Levels., Scott H. Belshaw, Brooke Nodeland, Lorrin Underwood, Alexandrea Colaiuta

Journal of Cybersecurity Education, Research and Practice

Increasingly, criminal justice practitioners have been called on to help solve breaches in cyber security. However, while the demand for criminal justice participation in cyber investigations increases daily, most universities are lagging in their educational and training opportunities for students entering the criminal justice fields. This article discusses the need to incorporate courses discussing the Dark Web in criminal justice. A review of existing cyber-criminal justice programs in Texas and nationally suggests that most community colleges and 4-year universities have yet to develop courses/programs in understanding and investigating the Dark Web on the internet. The Dark Web serves as the …

Reducing Payment-Card Fraud, Chares R. Ross

Walden Dissertations and Doctoral Studies

Critical public data in the United States are vulnerable to theft, creating severe financial and legal implications for payment-card acceptors. When security analysts and managers who work for payment card processing organizations implement strategies to reduce or eliminate payment-card fraud, they protect their organizations, consumers, and the local and national economy. Grounded in Cressey’s fraud theory, the purpose of this qualitative single case study was to explore strategies business owners and card processors use to reduce or eliminate payment-card fraud. The participants were 3 data security analysts and 1 manager working for an international payment card processing organization with 10 …

Strategies To Mitigate The Effects Of Identity Theft In The Hospitality Industry, Patricia Lee Jirsa

Walden Dissertations and Doctoral Studies

Leaders in the U.S. hospitality industry experience significant losses in profitability, increased mitigation cost, and reduced revenues because of business and consumer identity theft. Grounded in the fraud triangle theory and the fraud diamond theory, the purpose of this qualitative multiple-case study was to explore strategies leaders in the hospitality industry use to mitigate identity theft. A purposeful sample of 5 leaders of 5 different hospitality businesses in Montana participated in the study. Data were collected through semistructured interviews, member checking, and a review of company documents. During data analysis using Yin’s 5-step process, 3 key themes emerged: a new …

Effective Data Analytics And Security Strategies In Internal Audit Organizations, Desiree Auchey

Walden Dissertations and Doctoral Studies

The digitization of the corporate and regulatory environment presents an opportunity for internal audit organizations to change their audit techniques and increase their value to corporations. Audit functions have not kept pace with these advancements, as evidenced by the massive frauds in recent years, and current audit methodology does not robustly incorporate analytics and security of data. Grounded in agency theory, the purpose of this qualitative case study was to explore successful strategies business leaders use to implement data analytics and security for internal auditing and fraudulent activity. The participants comprised 3 audit leaders in Pennsylvania, who effectively used data …

Strategies To Mitigate The Effects Of Identity Theft In The Hospitality Industry, Patricia Lee Jirsa

Walden Dissertations and Doctoral Studies

Leaders in the U.S. hospitality industry experience significant losses in profitability, increased mitigation cost, and reduced revenues because of business and consumer identity theft. Grounded in the fraud triangle theory and the fraud diamond theory, the purpose of this qualitative multiple-case study was to explore strategies leaders in the hospitality industry use to mitigate identity theft. A purposeful sample of 5 leaders of 5 different hospitality businesses in Montana participated in the study. Data were collected through semistructured interviews, member checking, and a review of company documents. During data analysis using Yin’s 5-step process, 3 key themes emerged: a new …

Df 2.0: An Automated, Privacy Preserving, And Efficient Digital Forensic Framework That Leverages Machine Learning For Evidence Prediction And Privacy Evaluation, Robin Verma, Jayaprakash Govindaraj Dr, Saheb Chhabra, Gaurav Gupta

Journal of 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 data privacy protection is not a performance measure, however, preventing privacy violations during the digital forensic investigation, is also a big challenge. With a perception that the completeness of investigation and the data privacy preservation are incompatible with each other, the researchers have provided solutions to address the above-stated challenges that either focus on the effectiveness of the investigation …

Analysis And Categorization Of Drive-By Download Malware Using Sandboxing And Yara Ruleset, Mohit Singhal

Computer Science and Engineering Theses - Archive

With the increase in the usage of websites as the main source of information gathering, malicious activity especially drive-by download has exponentially increased. A drive-by download refers to unintentional download of malicious code to a user computer that leaves the user open to a cyberattack. It has become the preferred distribution vector for many malware families. Malware is any software intentionally designed to cause damage to a user computer. The purpose of this research is to analyze the malware that were obtained from visiting approximately 100,000 malicious URLs and then running these binaries in sandboxes and then analyzing their runtime …

Artificial Intelligence Hits The Barrier Of Meaning, Melanie Mitchell

Computer Science Faculty Publications and Presentations

Today’s AI systems sorely lack the essence of human intelligence: Understanding the situations we experience, being able to grasp their meaning. The lack of humanlike understanding in machines is underscored by recent studies demonstrating lack of robustness of state-of-the-art deep-learning systems. Deeper networks and larger datasets alone are not likely to unlock AI’s “barrier of meaning”; instead the field will need to embrace its original roots as an interdisciplinary science of intelligence.

Strategies To Reduce The Fiscal Impact Of Cyberattacks, Shirley Denise Smith

Walden Dissertations and Doctoral Studies

A single cyberattack event involving 1 major corporation can cause severe business and social devastation. In this single case study, a major U.S. airline company was selected for exploration of the strategies information technology administrators and airline managers implemented to reduce the financial devastation that may be caused by a cyberattack. Seven participants, of whom 4 were airline managers and 3 were IT administrators, whose primary responsibility included implementation of strategies to plan for and respond to cyberattacks participated in the data collection process. This study was grounded on the general systems theory. Data collection entailed semistructured face-to-face and telephone …

Detection Of Fraud Risks In Retailing Sector Using Mlp And Svm Techniques, Davut Pehli̇vanli, Süleyman Eken, Ebu Beki̇r Ayan

Turkish Journal of Electrical Engineering and Computer Sciences

In today's business conditions, where business activities are spreading over a wide geographical area, fraud auditing processes have crucial importance especially for the retailing sector which has a high branch network. In the retailing sector, especially purchasing processes are subject to high fraud risks. This paper shows that it is possible to detect fraudulent processes by applying data mining techniques on operational data related to purchasing activities. Within this scope, in order to detect the fraudulent purchasing operations, support vector machine (SVM) models with different kernels and artificial neural networks methods have been used and successful results have been achieved. …

Multimodal Approach For Malware Detection, Jarilyn M. Hernandez Jimenez

Graduate Theses, Dissertations, and Problem Reports (ETD)

Although malware detection is a very active area of research, few works were focused on using physical properties (e.g., power consumption) and multimodal features for malware detection. We designed an experimental testbed that allowed us to run samples of malware and non-malicious software applications and to collect power consumption, network traffic, and system logs data, and subsequently to extract dynamic behavioral-based features. We also extracted code-based static features of both malware and non-malicious software applications. These features were used for malware detection based on: feature level fusion using power consumption and network traffic data, feature level fusion using network traffic …

Automated Essay Evaluation Using Natural Language Processing And Machine Learning, Harshanthi Ghanta

Theses and Dissertations

The goal of automated essay evaluation is to assign grades to essays and provide feedback using computers. Automated evaluation is increasingly being used in classrooms and online exams. The aim of this project is to develop machine learning models for performing automated essay scoring and evaluate their performance. In this research, a publicly available essay data set was used to train and test the efficacy of the adopted techniques. Natural language processing techniques were used to extract features from essays in the dataset. Three different existing machine learning algorithms were used on the chosen dataset. The data was divided into …

Managing Cyber Risks & Business Exposure In The Surface Transportation Ecosystem, Jacques R. Francoeur

Mineta Transportation Institute

This report focuses on Surface Transportation (ST), both fixed and route-based, and the growing threats to their information technology (IT) infrastructures. As an industry, ST seeks to optimize the movement of people and goods, while ensuring safety and resiliency and minimizing environmental impact. Cyber threats are a powerful medium for those with the political, social, and economic motivations and wherewithal to disrupt and destroy existing ST systems. The ultimate objective is to develop a new paradigm to define, describe, design, and deploy the most effective protection, at the lowest cost, in the shortest time within the limits of available resources. …

Application Of Machine Learning Techniques In Credit Card Fraud Detection, Ronish Shakya

UNLV Theses, Dissertations, Professional Papers, and Capstones

Credit card fraud is an ever-growing problem in today’s financial market. There has been a rapid increase in the rate of fraudulent activities in recent years causing a substantial financial loss to many organizations, companies, and government agencies. The numbers are expected to increase in the future, because of which, many researchers in this field have focused on detecting fraudulent behaviors early using advanced machine learning techniques. However, the credit card fraud detection is not a straightforward task mainly because of two reasons: (i) the fraudulent behaviors usually differ for each attempt and (ii) the dataset is highly imbalanced, i.e., …

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 …

Weaponizing Twitter Litter: Abuse-Forming Networks And Social Media, Hal Berghel

Computer Science Faculty Research

Instead of liberating us from the biases of the educated among us, the Internet has saddled us with the biases of the unreasoned among us.

Scheduling In Mapreduce Clusters, Chen He

School of Computing: Dissertations, Theses, and Student Research

MapReduce is a framework proposed by Google for processing huge amounts of data in a distributed environment. The simplicity of the programming model and the fault-tolerance feature of the framework make it very popular in Big Data processing.

As MapReduce clusters get popular, their scheduling becomes increasingly important. On one hand, many MapReduce applications have high performance requirements, for example, on response time and/or throughput. On the other hand, with the increasing size of MapReduce clusters, the energy-efficient scheduling of MapReduce clusters becomes inevitable. These scheduling challenges, however, have not been systematically studied.

The objective of this dissertation is to …

An Empirical Assessment Of Senior Citizens’ Cybersecurity Awareness, Computer Self-Efficacy, Perceived Risk Of Identity Theft, Attitude, And Motivation To Acquire Cybersecurity Skills, Carlene G. Blackwood-Brown

CCAC Theses and Dissertations

Cyber-attacks on Internet users have caused billions of dollars in losses annually. Cybercriminals launch attacks via threat vectors such as unsecured wireless networks and phishing attacks on Internet users who are usually not aware of such attacks. Senior citizens are one of the most vulnerable groups who are prone to cyber-attacks, and this is largely due to their limited cybersecurity awareness and skills. Within the last decade, there has been a significant increase in Internet usage among senior citizens. It was documented that senior citizens had the greatest rate of increase in Internet usage over all the other age groups …

An Efficient System For Subgraph Discovery, Aparna Joshi

Legacy Theses & Dissertations (2009 - 2024)

Subgraph discovery in a single data graph---finding subsets of vertices and edges satisfying a user-specified criteria---is an essential and general graph analytics operation with a wide spectrum of applications. Depending on the criteria, subgraphs of interest may correspond to cliques of friends in social networks, interconnected entities in RDF data, or frequent patterns in protein interaction networks to name a few. Existing systems usually examine a large number of subgraphs while employing many computers and often produce an enormous result set of subgraphs. How can we enable fast discovery of only the most relevant subgraphs while minimizing the computational requirements?

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

Dissertations

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