Digital Communications and Networking Commons^™

Predicting Crises On The African Frontier Stock Markets With Investor Sentiment Indicators: A Machine Learning Approach, David Korsah, Lord Mensah

Journal of International Technology and Information Management

This study examined the predictive ability of machine learning algorithms in identifying crises within African stock markets. The study employed seven distinct machine-learning models, analyzing historical stock prices from eight stock markets, three major sentiment indicators, and the exchange rates of local currencies against the US dollar, with each data spanning from May 1, 2007, to April 1, 2023. Extreme Gradient Boosting (XGBoost) emerged as the most effective algorithm for predicting crises. Historical stock prices and exchange rates were identified as the most critical features for prediction. On the sentiment side, investors’ perceptions of potential volatility on the S&P 500, …

Pedagogy In The Age Of Ai: Exploring Generative Ai For Higher Education, Alison Munsch Phd

Journal of International Technology and Information Management

Generative Artificial Intelligence (AI) presents transformative opportunities for higher education, enabling personalized learning, enhanced student engagement, and efficient pedagogical practices. This tutorial-style article guides educators in integrating generative AI into their classrooms through hands-on activities, practical strategies, and reflective exercises. It explores the capabilities of AI tools such as ChatGPT, their applications across disciplines, and the ethical considerations for their use. By cultivating critical thinking and fostering student readiness for AI-driven futures, this article underscores the transformative potential of generative AI in higher education with an emphasis on the academic areas of business analytics, information systems, and computer science.

Surviving And Thriving In The Hybrid Cloud: A Review Of The Current Cloud Computing Landscape, Peter Munsch, Alison Munsch

Journal of International Technology and Information Management

Background and Purpose

Both academic and industry institutions have increasingly migrated essential services to public cloud providers (e.g., Microsoft, AWS, Google) with mixed outcomes. Some industry leaders attempted to fully replace their on-premises data centers with public cloud services, a move not advised without thorough performance and cost analyses (Potel, 2023). Despite some organizations pulling back from the “Cloud First” strategy, the public cloud services market continued to grow, with revenue increasing by approximately 20% year-over-year since 2020 and surpassing half a trillion dollars in 2022 (IDC Worldwide Semiannual Public Cloud Services Tracker, 2H 2022). Cloud technologists suggested that hybrid …

Predicting Global Healthcare Supply Chain Delays: A Machine Learning Approach Leveraging Country-Level Logistics Metrics, Jeevan Sai Gali, Nima Molavi, Sepideh Alavi

Journal of International Technology and Information Management

In global healthcare logistics, ensuring the timely delivery of medical commodities is critical, particularly in low- and middle-income countries characterized by infrastructural limitations and operational uncertainties. This research introduces an advanced, data-driven predictive framework designed to forecast delivery delays by synthesizing granular, internal shipment-level data from the USAID Global Health Supply Chain Program (GHSC-PSM) with external country-level logistics capabilities indicators derived from the World Bank’s Logistics Performance Index (LPI). Rather than relying on retrospective trend analyses, this study employs machine learning algorithms such as Random Forest, XGBoost, Support Vector Machines (SVM), and Multi-Layer Perceptron (MLP) to detect …

Funkcjonowanie Doręczeń Elektronicznych W Ujęciu Technicznym, Michał Tabor

internetowy Kwartalnik Antymonopolowy i Regulacyjny (internet Quarterly on Antitrust and Regulation)

The article provides a legal-technical and market analysis of electronic delivery in Poland, concluding that while the system complies with the basic requirements of the eIDAS Regulation, it needs significant organizational and technical improvements. The author reviews the National Electronic Delivery System, the role of the designated operator and qualified trust service providers, and highlights issues with interoperability, address registration and portability, delivery mailboxes, and the hybrid delivery service. Recommended legal reforms include granting the public delivery service qualified status, enabling multiple delivery addresses for public and complex organizations, partly opening the market to commercial qualified providers, and moving supervision …

Contextual Augmentation In Artificial Intelligence, Emmanuel Joshua Balogun

College of Graduate Studies: Theses & Dissertations

Contextual understanding is a significant challenge of Large Language Models (LLMs), which are typically trained on general-purpose datasets. Due to this, LLMs fail to capture nuanced or domain-specific information and may struggle to interpret user queries accurately. Consequently, prompt engineering can become complex in automating, and LLMs are prone to “hallucinating”—generating random or irrelevant texts—when they lack sufficient context. This undermines their ability to provide focused, accurate responses. Accordingly, this thesis seeks to enhance the contextual understanding capabilities of Artificial Intelligence systems to facilitate more precise and relevant answer generation. Study A looks into a new approach to combating misinformation …

Insider Threat Agent: A Behavioral Based Zero Trust Access Control Using Machine Learning Agent, Michael Fojude

College of Graduate Studies: Theses & Dissertations

Hybrid work, cloud adoption, and freely available AI‑enabled attack tools have exposed critical weaknesses in perimeter‑centric security. Current breach reports attribute more than one‑third of incidents to insider misuse or credential compromise, yet many organizations still depend on static Role‑ or Attribute‑Based Access Control that neither verifies intent continuously nor adapts to subtle behavioral change. This research addresses that gap by designing and validating a behavioral based Zero Trust Access Control (ZTAC) Agent. A five‑year enterprise log Dataset was extracted and cleansed to establish a high‑fidelity baseline of normal user behavior. Feature engineering captured temporal regularity (login sequence, session duration), …

Real-Time Congestion Control And Load Optimization In Cloud-Manets Using Predictive Algorithms, Preeti Rani, Mohammed Hussien Falaah

NJF Intelligent Engineering Journal

Cloud-MANET environments require a system to balance load and control congestion. As a result of integrating real-time network metrics with predictive traffic algorithms, the proposed model optimizes the management of dynamic topologies, network bandwidth constraints, and fluctuating traffic loads. In addition to energy-aware multi-path routing, the framework incorporates adaptive congestion control mechanisms to ensure data transmission is efficient and stable. This algorithm provides higher packet delivery ratios, reduces end-to-end delays, and increases throughput over existing algorithms, according to the evaluation results. Hybrid Cloud-MANET systems can benefit from this approach by optimizing resource utilization and network performance.

Exploring Smart Thermostat, Don P. Dang

2024 Fall Honors Capstone Projects - Archive

This study examines the security, privacy, and compatibility challenges associated with smart thermostats in smart home systems. Smart thermostats, as part of the growing Internet of Things (IoT) ecosystem, face vulnerabilities such as unauthorized access, data breaches, and inconsistent security protocols. Using a mixed-methods approach, this research evaluates encryption techniques, communication protocols (Zigbee, Z-Wave, Wi Fi), and user behaviors that impact system security and efficiency. Key findings indicate that 35% of users are concerned about hacking risks, while 25% express data privacy concerns. Many users lack awareness of security measures, such as firmware updates and password management, which increases vulnerabilities. …

Leveraging P4 Programmable-Hardware Switches For In-Network Pmu Packet Recovery, Evan Michael Bonar

Electrical Engineering and Computer Science Undergraduate Honors Theses

Phasor Measurement Unit (PMU) systems are essential for real-time power grid monitor- ing but often face data loss due to network delays, equipment malfunctions, or transmis- sion errors. Traditional centralized recovery solutions introduce significant latency and scalability challenges. This thesis presents a P4-based in-network recovery mechanism that embeds detection and recovery directly into the data plane of P4-enabled programmable switches, significantly reducing recovery time and infrastructure complexity. Using the Aurora 610 switch, the system detects missing packets via sequence number analysis and recovers magnitudes with an efficient register-based algorithm.

Evaluation demonstrates high accuracy and low latency, achieving a mean absolute …

Co-Emulation Of Robotics And Software-Defined Radio Based 5g Wireless Communications., Bhaskara Venkata Raju Garuda

Electronic Theses and Dissertations

The convergence of robotics and 5G wireless communication technologies has opened new avenues for real-time, dynamic robotic applications. This dissertation introduces a novel framework that integrates the Robot Operating System (ROS), Software-Defined Radios (SDRs), and 5G wireless networks to achieve seamless coemulation of robotic systems. The research emphasizes the unique features of 5G, such as ultra-low latency and high throughput, which enable critical applications like remote surgery, industrial automation, and autonomous vehicles. The methodology combines ROS for robotic control, SDRs for programmable communication channels, and 5G testbeds for high-speed, reliable data transmission. The experimental evaluation focuses on both position-based and …

Bonsai Merkle Tree Streams: Bulk Memory Verification Unit For Trusted Program Verification System, Richard J. Rios

Master's Theses

Today, all modern computing systems are undoubtedly vulnerable to numerous types of attacks that could be targeted toward any layer of the system from dedicated hardware to highly abstracted software. Unfortunately, many devices and systems naturally contain inadequately protected components or software modules that un- dermine their security as a whole. Additionally, security is heavily variable system to system, and has a huge dependence on adequate implementation and ongoing support from device and software manufacturers. To address these various security issues in a very general way, TrustGuard, a containment security system utilizing an external device called the Sentry that would …

Faids: Artificial Intelligence Developmental Systems Framework For Predicting And Preventing Cyberattacks In Supply Chain Networks, Lordt Becklines

Research & Publications

Cyber threats and attacks disrupt and damages supply chain networks (SCNs), which are complex and interlinked. Current methods to predict and prevent cyberattacks are inadequate and ineffective. This research proposes an AI developmental systems framework (FAIDS) to protect SCNs from cyberattacks. The framework has four components: (1) an AI threat intelligence system; (2) an AI risk assessment system; (3) an AI decision support system; and (4) an AI learning and adaptation system. The framework is tested on a simulated retail SCN. The results show that the framework can predict and prevent cyberattacks and improve the network's resilience and security. The …

Crowdstrike Cyber Incident Vs. Past Major Cyber Incidents: Analysis And Solutions, Priyant Banerjee

Himalayan Research Papers Archive

On July 19, 2024, a technical malfunction in CrowdStrike’s Falcon sensor software led to a global ITdisruption, affecting millions of devices across multiple sectors. This incident, although not a direct cyber-attack, caused significant operational upheavals reminiscent of major past cyber incidents. This paperexplores the CrowdStrike incident in detail, compares it with previous major cyber events, and proposescomprehensive solutions to mitigate such risks in the future.The faulty update from CrowdStrike resulted in widespread system crashes, notably the "Blue Screen ofDeath," paralyzing operations in critical sectors such as healthcare, finance, and transportation. The paperexamines the immediate and cascading effects of the incident, …

Industria 4.0. Internet De Las Cosas: Ciberseguridad Y Aplicaciones, Jairo Eduardo Márquez Díaz, Arles Prieto Moreno, Luz Jaddy Castañeda Rodríguez, Luis Gonzalo Benavides Ramírez

Ingeniería

Este libro explora cómo la Cuarta Revolución Industrial, también conocida como Industria 4.0, está transformando sectores industriales mediante tecnologías disruptivas como el internet de las cosas (IoT), la inteligencia artificial, el big data y la realidad aumentada, lo que ofrece una mayor eficiencia, productividad y seguridad. Aborda los riesgos de ciberseguridad asociados y propone soluciones basadas en la inteligencia artificial y el blockchain. Además, analiza el uso de drones y tecnologías como el LiDAR en la minería, lo que mejora la exploración, la seguridad y la sostenibilidad de operaciones complejas. Con un enfoque en la minería del carbón en Colombia, …

Welcome To Cheney App, Timothy Nelson, Nolan Posey, Tanner Stephenson, Daniel Palmer, Matthew Matriciano

2024 Symposium

Welcome to Cheney is a non-profit organization committed to fostering communication, connection, and action within the city of Cheney. Their primary purpose is to provide timely and accurate information to the residents of Cheney. Welcome to Cheney has tried utilizing other forms of social media such as Facebook and Instagram to share information, but their presence is being overshadowed amidst the noise on those platforms. Therefore, the intention of this project is to develop a mobile app with the sole purpose of being a reliable means of sharing important information with the residents of Cheney.

The information being shared on …

Authenticated Diagnosing Of Covid-19 Using Deep Learning-Based Ct Image Encryption Approach, Mohamed Attia Abdelgwad, Amira Hassan Abed, Mahmoud Bahloul

Future Computing and Informatics Journal

Researchers are motivated to use artificial intelligence in biometrics, medical imaging encryption, as well as cybersecurity due to its rapid progress. An encryption method for CT scans—which are used to diagnose COVID-19 disease—is proposed in this study. The suggested encryption method creates a connection among an individual's face picture and CT image to increase confidentiality. The simple CT picture is first enhanced with a host image. An encryption key is multiplied by the final result. This key is produced by applying a Convolutional Neural Network (CNN) to recognize characteristics from people's face photographs. Additionally, a straightforward CNN with three convolutional …

Comprehensive Network Redundancy Implementation And Cybersecurity Hardening Project: Ensuring Resilience And Defending Against Dhcp Starvation, Stp Man-In-The-Middle, And Brute Force Attacks, Seth Shaheen

Williams Honors College, Honors Research Projects

I have created a network topology that contains three Cisco routers, three Cisco switches, and three endpoints. The network has been built using the software GNS-3. The endpoints on the topology include one VPC, one Kali Linux VM, and one Ubuntu Server VM. The main purpose of this network topology is to show the skills I have learned during my tenure at The University of Akron. This will be done by hardening this network to ensure that the network is impervious to cyber-attacks. The Kali Linux VM will act as the attacker on the network and conduct three attacks: STP …

Communication Challenges In Underwater Wireless Networks: Mac Protocols And Software Solutions, Dmitrii Dugaev

Dissertations, Theses, and Capstone Projects

Underwater wireless networks (UWNs) represent a diverse and intriguing research domain, encompassing a wide array of scientific and industrial applications. This dissertation delves into the communication challenges at the Medium Access Control (MAC) layer within UWNs, stemming from the distinctive signal propagation conditions and the harshness of the deployment environment. The manuscript provides comprehensive coverage of key aspects of UWNs, including potential applications, communication protocols, methodologies employed in such networks, and existing software solutions that facilitate simulation, emulation, and real testbed scenarios for underwater research endeavors. Furthermore, this research introduces innovative software and communication solutions designed to facilitate the seamless …

A Study On Privacy Over Security And Privacy Enhancing Networks, Everett Lee Conway

Master's Theses

With rapid developments in communication technologies and awareness of security and privacy risks online, Security and Privacy Enhancing Networks (SPENs) have become increasingly popular. Especially during the COVID-19 pandemic, workplaces encouraged employees to take additional security measures, such as VPNs. In this work, we conduct a comprehensive study on website fingerprinting attacks. A comprehensive system model and threat model based on two types of SPENs (Virtual Private Networks and Tor Networks) are presented. Moreover, we demonstrate a website fingerprinting attack by ethically collecting website fetch data and analyzing the collected data using five different machine learning classification models including k …

Evaluating The Effect Of Noise On Secure Quantum Networks, Karthick Anbalagan

Master's Theses

This thesis focuses on examining the resilience of secure quantum networks to environmental noise. Specifically, we evaluate the effectiveness of two well-known quantum key distribution (QKD) protocols: the Coherent One-Way (COW) protocol and Kak’s Three-Stage protocol (Kak06). The thesis systematically evaluates these protocols in terms of their efficiency, operational feasibility, and resistance to noise, thereby contributing to the progress of secure quantum communications. Using simulations, this study evaluates the protocols in realistic scenarios that include factors such as noise and decoherence. The results illustrate each protocol’s relative benefits and limitations, highlighting the three-stage protocol’s superior security characteristics, resistance to interference, …

Machine Learning For Intrusion Detection Into Unmanned Aerial System 6g Networks, Faisal Alrefaei

Doctoral Dissertations and Master's Theses

Progress in the development of wireless network technology has played a crucial role in the evolution of societies and provided remarkable services over the past decades. It remotely offers the ability to execute critical missions and effective services that meet the user's needs. This advanced technology integrates cyber and physical layers to form cyber-physical systems (CPS), such as the Unmanned Aerial System (UAS), which consists of an Unmanned Aerial Vehicle (UAV), ground network infrastructure, communication link, etc. Furthermore, it plays a crucial role in connecting objects to create and develop the Internet of Things (IoT) technology. Therefore, the emergence of …

Improving Ethics Surrounding Collegiate-Level Hacking Education: Recommended Implementation Plan & Affiliation With Peer-Led Initiatives, Shannon Morgan, Dr. Sanjay Goel

Military Cyber Affairs

Cybersecurity has become a pertinent concern, as novel technological innovations create opportunities for threat actors to exfiltrate sensitive data. To meet the demand for professionals in the workforce, universities have ramped up their academic offerings to provide a broad range of cyber-related programs (e.g., cybersecurity, informatics, information technology, digital forensics, computer science, & engineering). As the tactics, techniques, and procedures (TTPs) of hackers evolve, the knowledge and skillset required to be an effective cybersecurity professional have escalated accordingly. Therefore, it is critical to train cyber students both technically and theoretically to actively combat cyber criminals and protect the confidentiality, integrity, …

Using Digital Twins To Protect Biomanufacturing From Cyberattacks, Brenden Fraser-Hevlin, Alec W. Schuler, B. Arda Gozen, Bernard J. Van Wie

Military Cyber Affairs

Understanding of the intersection of cyber vulnerabilities and bioprocess regulation is critical with the rise of artificial intelligence and machine learning in manufacturing. We detail a case study in which we model cyberattacks on network-mediated signals from a novel bioreactor, where it is important to control medium feed rates to maintain cell proliferation. We use a digital twin counterpart reactor to compare glucose and oxygen sensor signals from the bioreactor to predictions from a kinetic growth model, allowing discernment of faulty sensors from hacked signals. Our results demonstrate a successful biomanufacturing cyberattack detection system based on fundamental process control principles.

Characterizing Advanced Persistent Threats Through The Lens Of Cyber Attack Flows, Logan Zeien, Caleb Chang, Ltc Ekzhin Ear, Dr. Shouhuai Xu

Military Cyber Affairs

Effective cyber defense must build upon a deep understanding of real-world cyberattacks to guide the design and deployment of appropriate defensive measures against current and future attacks. In this abridged paper (of which the full paper is available online), we present important concepts for understanding Advanced Persistent Threats (APTs), our methodology to characterize APTs through the lens of attack flows, and a detailed case study of APT28 that demonstrates our method’s viability to draw useful insights. This paper makes three technical contributions. First, we propose a novel method of constructing attack flows to describe APTs. This abstraction allows technical audiences, …

Machine Learning Security For Tactical Operations, Dr. Denaria Fields, Shakiya A. Friend, Andrew Hermansen, Dr. Tugba Erpek, Dr. Yalin E. Sagduyu

Military Cyber Affairs

Deep learning finds rich applications in the tactical domain by learning from diverse data sources and performing difficult tasks to support mission-critical applications. However, deep learning models are susceptible to various attacks and exploits. In this paper, we first discuss application areas of deep learning in the tactical domain. Next, we present adversarial machine learning as an emerging attack vector and discuss the impact of adversarial attacks on the deep learning performance. Finally, we discuss potential defense methods that can be applied against these attacks.

Securing The Void: Assessing The Dynamic Threat Landscape Of Space, Brianna Bace, Dr. Unal Tatar

Military Cyber Affairs

Outer space is a strategic and multifaceted domain that is a crossroads for political, military, and economic interests. From a defense perspective, the U.S. military and intelligence community rely heavily on satellite networks to meet national security objectives and execute military operations and intelligence gathering. This paper examines the evolving threat landscape of the space sector, encompassing natural and man-made perils, emphasizing the rise of cyber threats and the complexity introduced by dual-use technology and commercialization. It also explores the implications for security and resilience, advocating for collaborative efforts among international organizations, governments, and industry to safeguard the space sector.

Commercial Enablers Of China’S Cyber-Intelligence And Information Operations, Ethan Mansour, Victor Mukora

Military Cyber Affairs

In a globally commercialized information environment, China uses evolving commercial enabler networks to position and project its goals. They do this through cyber, intelligence, and information operations. This paper breaks down the types of commercial enablers and how they are used operationally. It will also address the CCP's strategy to gather and influence foreign and domestic populations throughout cyberspace. Finally, we conclude with recommendations for mitigating the influence of PRC commercial enablers.

Analyzing Information Cascades Through Machine Learning And Data Analytics, Betul Agirman

Honors Scholar Theses

In today's digital age, social media platforms have become pivotal in influencing public opinion and behavior, with information spreading being both beneficial and detrimental. This rapid spread is typically called an information cascade, and they are important in further understanding social influence, managing misinformation, and even predicting potential trends of public responses. With social media, people are connected so easily to one another like a network, wherein it becomes possible for them to influence each other’s behavior and decisions. Utilizing a dataset from Weibo that spans critical periods of the COVID-19 outbreak, this study integrates machine learning and data analytics …

A Design Science Approach To Investigating Decentralized Identity Technology, Janelle Krupicka

Cybersecurity Undergraduate Research Showcase

The internet needs secure forms of identity authentication to function properly, but identity authentication is not a core part of the internet’s architecture. Instead, approaches to identity verification vary, often using centralized stores of identity information that are targets of cyber attacks. Decentralized identity is a secure way to manage identity online that puts users’ identities in their own hands and that has the potential to become a core part of cybersecurity. However, decentralized identity technology is new and continually evolving, which makes implementing this technology in an organizational setting challenging. This paper suggests that, in the future, decentralized identity …