Cybersecurity Commons^™

Bringing Different Disciplines And Competitions In Your Classroom, Eric Chan-Tin, Mohammed Abuhamad

Computer Science: Faculty Publications and Other Works

It is well-known that cybersecurity does not belong only to computer science/engineering. Other disciplines such as Psychology, Criminal Justice, Sociology, and Political Science can have a great impact in cybersecurity research and education. Students taking only courses are at a disadvantage and should be encouraged to participate in cybersecurity competitions to obtain real-world skills. This lightning talk will look at incorporating two aspects in an interdisciplinary cybersecurity program/curriculum: 1) different disciplines and majors such as Psychology, Criminal Justice, Political Science, Sociology into the cybersecurity program; and 2) including cybersecurity competitions as an integral part of the cybersecurity classroom and curriculum. …

48 - Improving Worship Experience: A Secure Application For Generating Worship Questions Using Ai, Hind Aldabagh, Rhys Ferris

Undergraduate Research Symposium

Improving worship Experience: A Secure application for generating worship questions using AI

Rhys Ferris

Under the direction of Hind Aldabagh, School of Cybersecurity

Generating discussion questions for family worship time during the week based on sermon notes presents an innovative and helpful tool to assist pastors in developing worship questions. Instead of using ChatGPT, hosting a small AI model with Mistral provides an alternative solution that better suits our project.

Using prompt engineering, a custom prompt was created within the statement of faith to guide the AI in reading the text file of the sermon notes. The front end consists …

47 - Enhancing Patient Experience: A Secure Self-Service Kiosk For Prescription Status In Pharmacies, Raneem Alarian

Undergraduate Research Symposium

Creating secure and dependable pharmacy kiosk systems is essential for improving both patient satisfaction and the overall efficiency of pharmacy operations. Patients often experience frustration due to long wait times at the pharmacy counter, especially when prescriptions are not ready. As a licensed pharmacy technician, I have witnessed this issue firsthand, which led me to develop a software solution developed to improve pharmacy workflow. This project focuses on the design and execution of a client-server application for a self-service pharmacy kiosk, enabling patients to securely check the status of their prescriptions before they reach the counter. Developed using Visual Studio …

From Adversarial Attacks To Robust Classifiers - A Study In Social Media Spam Detection - Black Box & White Box, Jonathan Jose Penaloza Rumie

Undergraduate Theses

Adversarial attacks pose a significant threat to the reliability of machine learning-based spam detection systems in social media. This undergraduate thesis, "From Adversarial Attacks to Robust Classifiers: A Study in Social Media Spam Detection – Black Box & White Box," systematically examines the impact of both black-box and white-box adversarial attacks on a range of spam classifiers, including Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Bagging, Gradient Boosting, and Support Vector Machines. Leveraging a novel dataset derived from Twitter spam messages and enhanced with adversarial perturbations such as synonym replacement and character-level modifications, this study evaluates classifier performance under …

Optimizing Llm X86 Assembly Code Comprehension Through Fine-Tuning, Darrin Michael Lea

LSU Master's Theses

Reverse engineering is a cybersecurity process that focuses on understanding the underlying functionality of software or malware. This is an arduous process that demands large amounts of time and effort from cybersecurity practitioners. Large Language Models (LLMs) offer a potential solution to this problem. LLMs have worked their way into various fields of cybersecurity in recent years, including incident response and malware classification. However, LLMs have historically struggled with low-level code comprehension: a necessary part of reverse engineering. While LLMs can generate code and explain its function on the surface level, they struggle to grasp the wider context. In this …

Ceker: A Generalizable Llm Framework For Literature Analysis With A Case Study In Unikernel Security, Alex Wollman, John Hastings

Research & Publications

Literature reviews are a critical component of formulating and justifying new research, but are a manual and often time-consuming process. This research introduces a novel, generalizable approach to literature analysis called CEKER which uses a three-step process to streamline the collection of literature, the extraction of key insights, and the summarized analysis of key trends and gaps. Leveraging Large Language Models (LLMs), this methodology represents a significant shift from traditional manual literature reviews, offering a scalable, flexible, and repeatable approach that can be applied across diverse research domains. A case study on unikernel security illustrates CEKER's ability to generate novel …

Impact Of Data Snooping On Deep Learning Models For Locating Vulnerabilities In Lifted Code, Gary Mccully, John Hastings, Shengjie Xu

Research & Publications

This study examines the impact of data snooping on neural networks used to detect vulnerabilities in lifted code, and builds on previous research that used word2vec and unidirectional and bidirectional transformer-based embeddings. The research specifically focuses on how model performance is affected when embedding models are trained with datasets, which include samples used for neural network training and validation. The results show that introducing data snooping did not significantly alter model performance, suggesting that data snooping had a minimal impact or that samples randomly dropped as part of the methodology contained hidden features critical to achieving optimal performance. In addition, …

Cybermapping Solutions: A Unified Approach In Us/Nato Military Applications And Development, Nicholas Macrino

Electrical & Computer Engineering Projects for D. Eng. Degree

[First paragraph] Cyber threats are evolving in complexity and frequency, posing significant challenges for cybersecurity professionals in identifying, categorizing, and responding to attacks in real time. Unlike traditional warfare, where battlefield awareness is based on fixed geographic warfare, cyber operations involve abstract attack vectors, non-linear threat escalation, and rapidly changing network conditions. Modern cyber threats, such as advanced persistent threats (APTs), polymorphic malware, and distributed denial-of-service (DDoS) attacks, require adaptive visualization techniques that provide real-time awareness and facilitate rapid decision-making. However, existing symbology standards, such as MIL-STD-2525D, were not designed to accommodate the dynamic nature of cyber warfare. The inability …

Resilient Learning For Anomaly Detection In Smart Living Systems, Sahar Abedzadeh

Dissertations

Cyber-Physical Systems (CPS) rely on anomaly-based detection methods to ensure the integrity and security of critical infrastructures such as smart grids, smart water metering systems, and advanced metering infrastructures (AMI). Anomaly detection methods are commonly used to identify deviations from normal system behavior by establishing learned profiles and thresholdbased distinctions between benign and anomalous events. However, conventional frameworks often fail to account for adversarial data poisoning attacks, unlabeled unsafe events, and environmental noise—factors that distort training data, degrade detection accuracy, and increase false alarms. This dissertation proposes a resilient learning framework that mitigates these biases by integrating quantile regression, M-estimation …

Cyber Safe, Hiram Franco, Laurene Robinson, Joshua Do, Enrique Martinez, Han Vu

Posters - 2025

With the rapid rise of cyber threats, understanding malware behavior is more crucial than ever. Millions of new malware variants emerge annually, compromising personal data, financial information, and entire networks. While no system is entirely immune, cybersecurity education can help mitigate risks. CYBERSAFE is a sandbox malware analyzer designed to enhance malware detection and analysis skills. By running malware samples in a controlled virtual environment, users can observe real-time file modifications, network activity, and system changes. The tool also includes interactive exercises and quizzes to reinforce learning. CYBERSAFE bridges the gap between theory and practice, providing hands-on experience to help …

Advancing Devsecops In Smes: Challenges And Best Practices For Secure Ci/Cd Pipelines, Jayaprakashreddy Cheenepalli, John Hastings, Khandaker Mamun Ahmed, Chad Fenner

Research & Publications

This study evaluates the adoption of DevSecOps among small and medium-sized enterprises (SMEs), identifying key challenges, best practices, and future trends. Through a mixed methods approach backed by the Technology Acceptance Model (TAM) and Diffusion of Innovations (DOI) theory, we analyzed survey data from 405 SME professionals, revealing that while 68% have implemented DevSecOps, adoption is hindered by technical complexity (41%), resource constraints (35%), and cultural resistance (38%). Despite strong leadership prioritization of security (73%), automation gaps persist, with only 12% of organizations conducting security scans per commit. Our findings highlight a growing integration of security tools, particularly API security …

Enhancing Iot Security Using Lightweight Machine Learning Algorithms: A Comprehensive Approach Using Ensemble Learning, Feature Selection, And Federated Transfer Learning, Khawlah Harahsheh

Electrical & Computer Engineering Theses & Dissertations

The rapid expansion of the Internet of Things (IoT) has introduced significant security vulnerabilities due to the resource-constrained nature of IoT devices and their exposure to cyber threats. Traditional security solutions are often infeasible due to the high computational and storage demands they impose. This dissertation presents a lightweight, AI-driven security framework that enhances IoT network resilience by integrating feature selection, ensemble learning, and federated transfer learning while maintaining data privacy and minimizing computational overhead.

The proposed framework consists of three primary components: Feature Selection for Intrusion Detection, which optimizes performance by reducing redundant data and improving detection accuracy with …

Weapons Of Mass Disruption: How Small States Use Cyber To Resist Larger Powers, Russell Alexander Korb

Graduate Program in International Studies Theses & Dissertations

This paper examines the ways in which small states can engage larger actors using cyber- attacks. Since the end of both World Wars, small states have increased in both numbers and relevance, with strong international institutions and norms against military aggression allowing small states to gain legitimacy by the very act of participating in the international system. However, although small states can now do more than simply choose a larger, stronger benefactor to ward off their enemies, they still cannot defy larger powers outright due to the still- dramatic difference in capabilities between them. Those small states interested in confronting …

Ransomware In Healthcare: Threats, Impacts, And Mitigation Strategies, Mackenzie Dotson, Kasi Gorli, Alberto Coustasse

Management Faculty Research

Excerpt: The growing digitalization of healthcare has exposed hospitals to significant cybersecurity threats, particularly ransomware attacks. The Health Sector Cybersecurity Coordination Center (HC3) reported that as of mid-2024, there were 730 cyber-attacks worldwide against healthcare institutions, with 530 targeting the U.S. (AHA, 2024). Half of these incidents involved ransomware, a type of malware that restricts access to critical data until a ransom is paid (HHS, 2021). Hospitals are attractive targets for cybercriminals due to their essential role in patient care. Cybercriminals exploit vulnerabilities in hospital networks, often causing severe operational and financial damage. Factors such as understaffed IT teams, outdated …

Cyber Threats In Healthcare: The Ransomware Epidemic, Mackenzie Dotson, Kasi Gorli, Alberto Coustasse

Management Faculty Research

In this presentation, we will delve into the growing ransomware crisis in healthcare, examining how these cyber threats disrupt hospital operations, jeopardize patient safety, and impose significant financial burdens. From understanding how ransomware infiltrates hospital systems to exploring real-world case studies, we will uncover the devastating impact of these attacks. Our discussion will also focus on mitigation strategies, cybersecurity best practices, and policy recommendations to safeguard healthcare institutions from future threats.

Robust Spacecraft Autonomy For Deep Space Exploration In Special Euclidean Group Se(3), Matthew Wittal

Doctoral Dissertations and Master's Theses

Over the past half-century, humanity has gained extensive experience conducting manned spaceflight near Earth. Arguably, "near Earth" could even include the Moon — the most distant destination humans have reached. However, "near" in this work primarily refers low Earth orbit (LEO). One could argue that we have not truly left Earth since the Apollo, as spacecraft in some LEOs remain subject to atmospheric drag thus emphasizing their continued connection to Earth's immediate environment. Reflecting on this, it becomes clear that humanity has largely remained bound to Earth’s immediate vicinity since the Apollo missions reached the Moon. However, that is set …

Advanced Techniques In Symmetric Key Cryptanalysis, Debasmita Chakraborty

Doctoral Theses

Symmetric key cryptographic primitives are essential tools used extensively in daily digital interactions. These primitives are mainly designed to provide three key services: ensuring data confidentiality, maintaining data integrity, and verifying the authenticity of data sources. The primary types of symmetric key primitives that deliver these services include block ciphers, stream ciphers, hash functions, message authentication codes, and authenticated encryption with associated data. This thesis mainly explores the security analysis of hash functions, several block ciphers, and stream ciphers using some advanced cryptanalytic techniques. We begin by examining the collision security of a hash function, specifically under the assumption that …

Leveraging Artificial Intelligence To Strengthen Human Resilience Against Phishing Attacks, Muhammad Mavins

Cybersecurity Undergraduate Research Showcase

Phishing attacks are a major cybersecurity threat, tricking people with fake emails, scam websites, and social engineering tactics. As these attacks become more advanced, traditional security measures are no longer enough to stop them. This paper looks at how Artificial Intelligence (AI) can help detect and prevent phishing while also making people more aware of these threats. Using machine learning (ML), natural language processing (NLP), and behavioral analysis, AI can examine email content, sender behavior, and metadata to spot phishing attempts. AI-powered cybersecurity training can also teach people to recognize and respond to phishing by using personalized phishing tests and …

The Future Of Ai: Join The Conversation, Jennifer Wojton, Cassandra Branham, Vijay Tummala, Laxima Niure Kandel, Kayla D. Taylor

Publications

Join the Conversation! The Future is AI? There is so much conflicting information about what AI is capable of, how it could/should be used, by whom and for what purpose. In this panel discussion, we hope to provide a baseline of information that will help all participants think critically and articulate thoughtful questions about the mechanics of AI, ethical use or non-use of AI in particular contexts (school, industry, business, art, etc.), and the impacts we are currently experiencing or are likely to experience. Hear from ERAU faculty of different disciplines to discuss what the current state of AI technology …

Evaluating Educational Benefits Of A Custom Cyber Game: ‘Hvac Attack!’, Jillian S. Valente

Theses and Dissertations

Cyber competition and conflict remain an enduring concern for the Department of Defense (DoD). Positive control of cyberspace is crucial across the vast diversity of military operations and supporting activities. Military members play an important role in cyber prevention, detection, and remediation, but most receive relatively little training outside of the annual Cyber Awareness Challenge. Particular career fields within the DoD may benefit from specialized training in cybersecurity, in particular the civil engineering (CE) community supporting critical infrastructure protection. Prior research has suggested that game-based learning (GBL) can be beneficial for teaching cyber concepts.