Computer Sciences Commons^™

Cross Domain Iw Threats To Sof Maritime Missions: Implications For U.S. Sof, Gary C. Kessler, Diane M. Zorri

Publications

As cyber vulnerabilities proliferate with the expansion of connected devices, wherein security is often forsaken for ease of use, Special Operations Forces (SOF) cannot escape the obvious, massive risk that they are assuming by incorporating emerging technologies into their toolkits. This is especially true in the maritime sector where SOF operates nearshore in littoral zones. As SOF—in support to the U.S. Navy— increasingly operate in these contested maritime environments, they will gradually encounter more hostile actors looking to exploit digital vulnerabilities. As such, this monograph comes at a perfect time as the world becomes more interconnected but also more vulnerable.

Effect Of Augmented Reality On Consumer Behavior In E-Commerce, Chibuke Uzoechina, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

AR technology has been referred to as the future of e-commerce. In this paper, we propose to investigate the effect of AR on consumer behavior in e-commerce. Based on the theory of telepresence, we generated a set of hypotheses on their relationships. An experimental study is proposed to test the hypotheses. Our findings will be of interest to e-commerce companies that are looking at incorporating AR into their e-commerce platforms.

Working With Smart Machines: Insights On The Future Of Work, Thomas H. Davenport, Steven M. Miller

Research Collection School Of Computing and Information Systems

In this article, we share our observations on how and why AI-based systems are being deployed. We look at how these systems have been integrated into existing and new work processes, especially the implications for the changing nature of work and how it will be conducted in future with AI-based smart machines. This will help companies that are in the earlier stages of considering, planning, or deploying these systems to know what to expect from recent developments in practice. We draw our analysis from 24 case studies that we have recently completed on AI system usage in actual operational settings.

Privacy Is Infringed In Plain Sight And How To Dissapear, Zachary Taylor

Electronic Theses, Projects, and Dissertations

This culminating project explored how Amazon, Apple, Facebook, Google, and Microsoft infringe on their user's information privacy. Focus was on tools and techniques one can use to strengthen their information privacy. Privacy or information privacy was defined as the right to have some control over how your personal information is collected and used. This project will also introduce a verity of open-source tools and techniques that would help the unsuspected user to maintain their privacy.The questions asked were: what are some common techniques that Amazon, Apple, Facebook, Google, or Microsoft use to gain personal information?, At what cost would it …

Cybersecurity Risk Assessment Using Graph Theoretical Anomaly Detection And Machine Learning, Goksel Kucukkaya

Engineering Management & Systems Engineering Theses & Dissertations

The cyber domain is a great business enabler providing many types of enterprises new opportunities such as scaling up services, obtaining customer insights, identifying end-user profiles, sharing data, and expanding to new communities. However, the cyber domain also comes with its own set of risks. Cybersecurity risk assessment helps enterprises explore these new opportunities and, at the same time, proportionately manage the risks by establishing cyber situational awareness and identifying potential consequences. Anomaly detection is a mechanism to enable situational awareness in the cyber domain. However, anomaly detection also requires one of the most extensive sets of data and features …

J Mich Dent Assoc April 2021

The Journal of the Michigan Dental Association

In the April 2021 issue of the Journal of the Michigan Dental Association, we offer a comprehensive range of original feature content showcasing the latest developments in dental practice and knowledge, including:

1. AI in Dental Care Delivery: Explore the groundbreaking role of Artificial Intelligence (AI) and Machine Learning in dental care, revolutionizing efficiency, safety, care outcomes, and treatment planning consistency.
2. AI in Dental Claims Processing: Discover how AI is employed by third-party payers to streamline dental claims processing, resulting in cost containment and the proactive identification of potential fraud, waste, and abuse.
3. Evidence-Based Dentistry: As part of …

Powered By Ai, Christopher J. Smiley

The Journal of the Michigan Dental Association

Artificial Intelligence (AI) is revolutionizing dental practice through its ability to process vast amounts of data, enhance diagnosis, and improve patient care. However, AI introduces the challenge of bias and ethical considerations. Dentists and dental benefit providers are utilizing AI for early disease detection and efficient data management, but transparency and fairness in AI algorithms are vital. The Rome Call for AI Ethics emphasizes ethical, non-biased AI development. In the broader context, AI-driven marketing and predictive behavior raise concerns about privacy and ethical data use. The dental community must embrace AI's power while upholding ethical standards and transparency.

Network-Based Analysis Of Early Pandemic Mitigation Strategies: Solutions, And Future Directions, Pegah Hozhabrierdi, Raymond Zhu, Maduakolam Onyewu, Sucheta Soundarajan

Northeast Journal of Complex Systems (NEJCS)

Despite the large amount of literature on mitigation strategies for pandemic spread, in practice, we are still limited by naive strategies, such as lockdowns, that are not effective in controlling the spread of the disease in long term. One major reason behind adopting basic strategies in real-world settings is that, in the early stages of a pandemic, we lack knowledge of the behavior of a disease, and so cannot tailor a more sophisticated response. In this study, we design different mitigation strategies for early stages of a pandemic and perform a comprehensive analysis among them. We then propose a novel …

Multi-Step-Ahead Exchange Rate Forecasting For South Asian Countries Using Multi-Verse Optimized Multiplicative Functional Link Neural Networks, Kishore Kumar Sahu, Sarat Chandra Nayak, Himansu Sekhar Behera

Karbala International Journal of Modern Science

The dynamic nonlinearity approach, coupled with the exchange rate data series, makes its future predictions difficult. Sophisticated methods are highly desired for effective prediction of such data. Artificial neural networks (ANNs) have shown their ability to model and predict such data. This article presents a multi-verse optimizer (MVO) based multiplicative functional link neural network (MV-MFLN) model to forecast the exchange rate data. Functional link neural network (FLN) makes use of functional expansion for input data with a fewer number of adjustable neuron weights, which makes it capable of learning the uncertainties accompanying the exchange rate data. In contrast to the …

Can We Classify Cashless Payment Solution Implementations At The Country Level?, Dennis Ng, Robert J. Kauffman, Paul Robert Griffin

Research Collection School Of Computing and Information Systems

This research commentary proposes a 3-D implementation classification framework to assist service providers and business leaders in understanding the kinds of contexts in which more or less successful cashless payment solutions are observed at point-of-sale (PoS) settings. Three constructs characterize the framework: the digitalization of the local implementation environment; the relative novelty of a given payment technology solution in a country at a specific point in time; and the development status of the country’s national infrastructure. The framework is motivated by a need to support cross-country research in this domain. We analyze eight country mini-cases based on an eight-facet (2 …

3d Printing Of Human Microbiome Constituents To Understand Spatial Relationships And Shape Parameters In Bacteriology, Jacques Izard, Teklu Kuru Gerbaba, Shara R. P. Yumul

Department of Food Science and Technology: Faculty Publications

Effective laboratory and classroom demonstration of microbiome size and shape, diversity, and ecological relationships is hampered by a lack of high-resolution, easy-to-use, readily accessible physical or digital models for use in teaching. Three-dimensional (3D) representations are, overall, more effective in communicating visuospatial information, allowing for a better understanding of concepts not directly observable with the unaided eye. Published morphology descriptions and microscopy images were used as the basis for designing 3D digital models, scaled at 20,000×, using computer-aided design software (CAD) and generating printed models of bacteria on mass-market 3D printers. Sixteen models are presented, including rod-shaped, spiral, flask-like, vibroid, …

How Do Monetary Incentives Influence Giving? An Empirical Investigation Of Matching Subsidies On Kiva, Zhiyuan Gao, Zhiling Guo, Qian Tang

Research Collection School Of Computing and Information Systems

Matching subsidies, through which third-party institutions provide a dollar-for-dollar match of private contributions made through selected campaigns, have served as effective tools to boost fundraising. We utilize a quasi-experiment on a prosocial crowdfunding platform to examine the effectiveness of matching subsidies in shaping funding outcomes and lender behaviors. Although matching subsidies offer matched loans competitive advantages over unmatched loans, we find that total private contributions made to both matched and unmatched loans increase compared to their prematching counterparts, suggesting a positive spillover effect on unmatched loans. However, matching subsidies lead to decreased private contributions made on the platform after a …

Explainable Recommendation With Comparative Constraints On Product Aspects, Trung-Hoang Le, Hady W. Lauw

Research Collection School Of Computing and Information Systems

To aid users in choice-making, explainable recommendation models seek to provide not only accurate recommendations but also accompanying explanations that help to make sense of those recommendations. Most of the previous approaches rely on evaluative explanations, assessing the quality of an individual item along some aspects of interest to the user. In this work, we are interested in comparative explanations, the less studied problem of assessing a recommended item in comparison to another reference item.

In particular, we propose to anchor reference items on the previously adopted items in a user's history. Not only do we aim at providing comparative …

Outsourcing Life Cycle Model For Financial Services In The Fintech Era, Tristan Lim, Patrick Thng

Research Collection School Of Computing and Information Systems

In today’s financial services landscape, staying ahead of the innovation curve and being disciplined at enhancing core service offerings entail careful resource planning. A well-structured outsourcing arrangement can go a long way towards enhancing long term organizational strategic growth. In the post-2014 FinTech era, (i) strategic management with an innovation focus and (ii) financial technology-associated risks, have brought about changes to outsourcing in the financial services industry. Presently, most outsourcing life cycle models in existing literature seek to provide comprehensive, yet industry-neutral guidelines lacking industry context and depth of coverage. A newly licensed financial institution deciding to embark on outsourcing …

Traceable Monero: Anonymous Cryptocurrency With Enhanced Accountability, Yannan Li, Guomin Yang, Wily Susilo, Yong Yu, Man Ho Au, Dongxi Liu

Research Collection School Of Computing and Information Systems

Monero provides a high level of anonymity for both users and their transactions. However, many criminal activities might be committed with the protection of anonymity in cryptocurrency transactions. Thus, user accountability (or traceability) is also important in Monero transactions, which is unfortunately lacking in the current literature. In this paper, we fill this gap by introducing a new cryptocurrency named Traceable Monero to balance the user anonymity and accountability. Our framework relies on a tracing authority, but is optimistic, in that it is only involved when investigations in certain transactions are required. We formalize the system model and security model …

Factors Influencing Small Construction Businesses From Implementing Information Security: A Case Study, Carl Andrew Mayes

Doctoral Dissertations and Projects

This qualitative study described the influence of small businesses’ failure to properly implement information security technologies resulting in the loss of sensitive and proprietary business information. A collective case study approach was used to determine the most effective way to gain a holistic picture of how small construction businesses make security technology implementation decisions to support their workforce. The theory guiding this study was the Unified Theory of Acceptance and Use of Technology (UTAUT) model which is related to the Theory of Planned Behavior and the Technology Acceptance Model which helped explain the intentions of individuals to use information systems. …

Revman: Revenue-Aware Multi-Task Online Insurance Recommendation, Yu Li, Yi Zhang, Lu Gan, Gengwei Hong, Zimu Zhou, Qiang Li

Research Collection School Of Computing and Information Systems

Online insurance is a new type of e-commerce with exponential growth. An effective recommendation model that maximizes the total revenue of insurance products listed in multiple customized sales scenarios is crucial for the success of online insurance business. Prior recommendation models are ineffective because they fail to characterize the complex relatedness of insurance products in multiple sales scenarios and maximize the overall conversion rate rather than the total revenue. Even worse, it is impractical to collect training data online for total revenue maximization due to the business logic of online insurance. We propose RevMan, a Revenue-aware Multi-task Network for online …

Portfolio Diversification Using Shape-Based Clustering, Tristan Lim, Chin Sin Ong

Research Collection School Of Computing and Information Systems

Portfolio diversification involves lowering the correlation between portfolio assets to achieve improved risk–return exposure. It is reasonable to infer from the classic Anscombe quartet that relying on descriptive statistics, and specifically, correlation, to achieve portfolio diversification may not derive the most optimal multiperiod portfolio risk-adjusted return because stocks in a portfolio can exhibit different price trends over time, even with the same computed pairwise correlation. This research applied a shape-based time-series clustering technique of agglomerative hierarchical clustering using dynamic time-series warping as a distance measure to aggregate stocks into like-trending clusters across time as a portfolio diversification tool. Results support …

Gophish: Implementing A Real-World Phishing Exercise To Teach Social Engineering, Andy Luse, Jim Burkman

Journal of Cybersecurity Education, Research and Practice

Social engineering is a large problem in our modern technological world, but while conceptually understood, it is harder to teach compared to traditional pen testing techniques. This research details a class project where students implemented a phishing exercise against real-world targets. Through cooperation with an external corporate partner, students learned the legal, technical, behavioral, analysis, and reporting aspects of social engineering. The outcome provided both usable data for a real-world corporation as well as valuable educational experience for the students.

Applying High Impact Practices In An Interdisciplinary Cybersecurity Program, Brian K. Payne, Lisa Mayes, Tisha Paredes, Elizabeth Smith, Hongyi Wu, Chunsheng Xin

Journal of Cybersecurity Education, Research and Practice

The Center for Cybersecurity Education and Research at Old Dominion University has expanded its use of high impact practices in the university’s undergraduate cybersecurity degree program. Strategies developed to promote student learning included learning communities, undergraduate research, a robust internship program, service learning, and electronic portfolios. This paper reviews the literature on these practices, highlights the way that they were implemented in our cybersecurity program, and discusses some of the challenges encountered with each practice. Although the prior literature on high impact practices rarely touches on cybersecurity coursework, the robust evidence of the success of those practices provides a sound …

An Assessment Of Internet Use And Cyber-Risk Prevalence Among Students In Selected Nigerian Secondary Schools, Adeola O. Opesade Dr, Abiodun O. Adetona Mr

Journal of Cybersecurity Education, Research and Practice

The use of the Internet has become highly pervasive among adolescents. While these people derive numerous benefits from their use of this technology, they are also faced with a challenge of being exposed to many cyber risks. Nigeria is a developing country with a teeming population of adolescents who are regular users of the Internet, but with inadequate research on adolescent Internet safety. There is therefore, a need to conduct studies on child online risks in Nigeria, to help evaluate the enormity of child online abuses. The present study investigated Internet use and cyber-risk prevalence among four hundred secondary school …

Hybrid Models As Transdisciplinary Research Enablers, Andreas Tolk, Alison Harper, Navonil Mustafee

Computational Modeling & Simulation Engineering Faculty Publications

Modelling and simulation (M&S) techniques are frequently used in Operations Research (OR) to aid decision-making. With growing complexity of systems to be modelled, an increasing number of studies now apply multiple M&S techniques or hybrid simulation (HS) to represent the underlying system of interest. A parallel but related theme of research is extending the HS approach to include the development of hybrid models (HM). HM extends the M&S discipline by combining theories, methods and tools from across disciplines and applying multidisciplinary, interdisciplinary and transdisciplinary solutions to practice. In the broader OR literature, there are numerous examples of cross-disciplinary approaches in …

Measurement Study Of Energy Impact On Blockchain Technologies: Cryptocurrency Mining, Qaylin Holliman

Cybersecurity: Deep Learning Driven Cybersecurity Research in a Multidisciplinary Environment

Blockchain technology facilitates the flow of information and the speed of information through a faster and more decentralized network. It has its advantages as compared to more centralized networks and legacy networks. With the evolution of mainstream technology, blockchains is predicted to be more effective and sufficient to consumers and commercial companies. In this paper, blockchains will be scaled to cryptocurrency mining, where cryptocurrencies utilize blockchain technology to record transactions and orders. Mining will also be examined through energy consumption, the algorithms behind some cryptocurrencies, their sustainability issue, and resolutions to combat high energy consumption. While the pace of energy …

Blockchain For A Resilient, Efficient, And Effective Supply Chain, Evidence From Cases, Adrian Gheorghe, Farinaz Sabz Ali Pour, Unal Tatar, Omer Faruk Keskin

Engineering Management & Systems Engineering Faculty Publications

In the modern acquisition, it is unrealistic to consider single entities as producing and delivering a product independently. Acquisitions usually take place through supply networks. Resiliency, efficiency, and effectiveness of supply networks directly contribute to the acquisition system's resiliency, efficiency, and effectiveness. All the involved firms form a part of a supply network essential to producing the product or service. The decision-makers have to look for new methodologies for supply chain management. Blockchain technology introduces new methods of decentralization and delegation of services, which can transform supply chains and result in a more resilient, efficient, and effective supply chain. This …

Strategies Project Managers Use That Reduce Information Technology Project Failures In The Insurance Industry, Jamarcus Snipes

Walden Dissertations and Doctoral Studies

The worldwide failure rate of information technology (IT) projects is approximately 65%. Insurance project managers who fail to successfully implement IT projects negatively impact organizational performance and profitability. Grounded in the management by objectives theory, the purpose of this qualitative multiple case study was to explore strategies project managers use to reduce IT project failures in the insurance industry. The participants comprised four IT project managers in Alabama who successfully used strategies to reduce IT project failures in the insurance industry. Data were collected from virtual semistructured interviews, company documents, existing literature, and journal notes. Thematic analysis was used to …

Leverage Psychological Factors Associated With Lapses In Cybersecurity In Organizational Management, Chad Holm

Cybersecurity Undergraduate Research Showcase

With computers being a standard part of life now with the evolution of the internet, many aspects of our lives have changed, and new ways of thinking must come. One of the biggest challenges in most cyber security problems is not related to the software or the hardware; it is the people that are using the computers to access the data and communicate with others, where the hackers could simply find a weak entry point that naturally exists and a weak link caused by human hands. The human factor as an “insider threat” will affect unauthorized access, credentials stealing, and …

A Monte-Carlo Analysis Of Monetary Impact Of Mega Data Breaches, Mustafa Canan, Omer Ilker Poyraz, Anthony Akil

Engineering Management & Systems Engineering Faculty Publications

The monetary impact of mega data breaches has been a significant concern for enterprises. The study of data breach risk assessment is a necessity for organizations to have effective cybersecurity risk management. Due to the lack of available data, it is not easy to obtain a comprehensive understanding of the interactions among factors that affect the cost of mega data breaches. The Monte Carlo analysis results were used to explicate the interactions among independent variables and emerging patterns in the variation of the total data breach cost. The findings of this study are as follows: The total data breach cost …

Generic Design Methodology For Smart Manufacturing Systems From A Practical Perspective, Part I—Digital Triad Concept And Its Application As A System Reference Model, Zhuming Bi, Wen-Jun Zhang, Chong Wu, Chaomin Luo, Lida Xu

Information Technology & Decision Sciences Faculty Publications

Rapidly developed information technologies (IT) have continuously empowered manufacturing systems and accelerated the evolution of manufacturing system paradigms, and smart manufacturing (SM) has become one of the most promising paradigms. The study of SM has attracted a great deal of attention for researchers in academia and practitioners in industry. However, an obvious fact is that people with different backgrounds have different expectations for SM, and this has led to high diversity, ambiguity, and inconsistency in terms of definitions, reference models, performance matrices, and system design methodologies. It has been found that the state of the art SM research is limited …

Image Source Identification Using Convolutional Neural Networks In Iot Environment, Yan Wang, Qindong Sun, Dongzhu Rong, Shancang Li, Li Da Xu

Information Technology & Decision Sciences Faculty Publications

Digital image forensics is a key branch of digital forensics that based on forensic analysis of image authenticity and image content. The advances in new techniques, such as smart devices, Internet of Things (IoT), artificial images, and social networks, make forensic image analysis play an increasing role in a wide range of criminal case investigation. This work focuses on image source identification by analysing both the fingerprints of digital devices and images in IoT environment. A new convolutional neural network (CNN) method is proposed to identify the source devices that token an image in social IoT environment. The experimental results …

Improving Stock Trading Decisions Based On Pattern Recognition Using Machine Learning Technology, Yaohu Lin, Shancun Liu, Haijun Yang, Harris Wu, Bingbing Jiang

Information Technology & Decision Sciences Faculty Publications

PRML, a novel candlestick pattern recognition model using machine learning methods, is proposed to improve stock trading decisions. Four popular machine learning methods and 11 different features types are applied to all possible combinations of daily patterns to start the pattern recognition schedule. Different time windows from one to ten days are used to detect the prediction effect at different periods. An investment strategy is constructed according to the identified candlestick patterns and suitable time window. We deploy PRML for the forecast of all Chinese market stocks from Jan 1, 2000 until Oct 30, 2020. Among them, the data from …