Cybersecurity Commons^™

Improving Image Quality In Electrical Capacitance Tomography Using Otsu Thresholding, Josiah Nombo

Tanzania Journal of Engineering and Technology (TJET)

Electrical Capacitance Tomography (ECT) is an imaging technique used in industrial process monitoring, particularly for monitoring and measuring the composition of multiphase flows. Despite its widespread application, the commonly used Linear Back Projection (LBP) algorithm often produces low-quality images due to its limited ability to handle high permittivity contrasts and nonlinearities. This study investigates the use of Otsu thresholding as a post-processing technique to enhance ECT image quality. By maximizing inter-class variance in the image histogram, Otsu thresholding improves contrast, clarity, and structural definition, enabling more effective segmentation of oil and gas components in multiphase flows. The proposed Otsu-based reconstruction …

Cyber Safety: Protecting Yourself Online, Laxima Niure Kandel, Kayla D. Taylor, Bhawana Poudel, Helen Hernandez

Graduate Student Works

The IEEE Women in Engineering (WIE) Affinity Group of Daytona hosted a cybersecurity awareness event on Saturday, April 26, 2025, at the Port Orange Regional Library. The session was designed specifically to help seniors in Volusia County learn how to protect themselves online, avoid scams, create strong passwords, and safely navigate the digital world.

"Exploring The Training Data Landscape For Ai Based Threathunting For Protecting Intellectual Property", Manzi Siibo, Christopher Kreider

Cybersecurity Undergraduate Research Showcase

This study provides a comprehensive evaluation of the effectiveness that would result in the integration of AI into traditional threat hunting systems. To do so, 10-15 scholarly articles and data sets were evaluated to see the results of AI and machine learning threat hunting versus traditional systems. With so many proven benefits of this integration, this paper also explores how it impacts the protection of Intellectual property which is some of the most important forms of information that threat hunting systems aim to protect.

Romance Scam Victimization: A Survey-Based Examination Of Financial, Psychological, And Reporting Factors, Ld Herrera

Research & Publications

Romance scams are a growing type of cybercrime in which perpetrators develop and exploit fraudulent romantic relationships with victims to obtain financial resources. These schemes cause substantial economic and psychological damage, yet they are significantly underreported. Official 2022 reports indicate only \$1.3 billion lost to romance scams in the US, but the true financial toll is likely much higher.

Using survey data from 366 victims, this study examines the financial and psychological toll of romance scams, reporting patterns, obstacles to seeking help, and victims' perceptions of received help. Most of the victims (60.9\%) did not seek help from any source, …

Fids: Accelerating Network Intrusion Detection Through Strategic Feature Selection, James Elmore

Cybersecurity Undergraduate Research Showcase

Network intrusion detection systems (IDS) typically analyze complete network flows to identify malicious traffic, requiring flows to conclude before classification. This approach creates detection delays for attacks like Slowloris that intentionally keep connections open for extended periods of time. This paper introduces a novel approach that classifies network traffic using only features available from the first few packets of a flow, enabling faster detection while maintaining high accuracy. We evaluate three random forest models on the CICIDS2017 dataset using expanding sets of features: the first-packet model trained on on features available from the first backward packet, the few-packet model which …

The Evolution Of Russian And Chinese Disinformation Tactics And The Threat They Pose To The U.S. Cybersecurity, Jehovani Sese

Cybersecurity Undergraduate Research Showcase

This paper aims to discuss how disinformation has become the most powerful tool used against the United State by foreign operatives. Of these foreign operatives, Russia and China have shown the ability to use advanced tactics to truly affect the United States security. Often these tools came in the form of state-sponsored media, influence campaigns and fake online identities. This literature review explores the evolution of Russian and Chinese disinformation tactics, examining how these approaches have changed over time and become more sophisticated. This paper will highlight major campaigns which use tools such as bot networks, and social media manipulation. …

Shaped Adversarial Patches And The Ability They Hold, Nathan Hallberg

Cybersecurity Undergraduate Research Showcase

In more recent years the development of computer vision has advanced to be more comprehensive than in the past, with newer applications ranging from autonomous vehicles to security systems. The main application I will be talking about throughout this paper is an object detection algorithm called YOLO (You only look once), this algorithm is particularly significant due to their real-time performance of being able to identify and localize objects within an image in quick timing. However, the strength of these computer vision models is increasingly challenged by adversarial attacks, which manipulate the computer's vision to block a certain part of …

Elder Fraud Metrics And Preventative Measures Of Chesapeake, Virginia, Joey J. Whitmore Jr.

Cybersecurity Undergraduate Research Showcase

Geriatric crime continues to escalate in the digital era, where older individuals are disproportionately being targeted because of their low digital literacy and high susceptibility to online frauds. In this paper, we examine the breadth of elder fraud in Chesapeake, Virginia using FBI Internet Crime Complaint Center (IC3) data and state-level cybersecurity initiatives and survey responses. Older adults aged 60 and up have reported losses of over $3.4 billion in 2023 alone, underscoring the importance of proactive measures. It assesses the public awareness from traditional and AI-based perspectives revealing significant gaps in digital safety literacy and fraud reporting mechanism among …

Analysis Of Cybersecurity Threats And Mitigation Strategies: Theory In To Practice, Project Proposal, Fransly Dutervil

Student Academic Conference

Cybersecurity threats pose significant risks to individuals and organizations, leading to data breaches, financial losses, and operational disruptions. This presentation explores key threats such as malware, phishing, DDoS attacks, insider threats, and zero-day exploits. It also discusses mitigation strategies, including network security measures, multi-factor authentication, encryption, and incident response planning. Through case studies of real-world cyber incidents, we highlight lessons learned and best practices to strengthen security defenses. The goal is to enhance awareness and promote proactive cybersecurity measures in an increasingly digital world.

Leveraging Benford’S Law And Machine Learning For Financial Fraud Detection, Benjamin R. Fu

Cybersecurity Undergraduate Research Showcase

Financial fraud, particularly credit card fraud, continues to pose substantial challenges to financial institutions due to its increasing frequency and impact on consumer trust. While traditional rule-based methods have provided foundational defenses, their limitations in scalability and adaptability have accelerated the adoption of machine learning (ML) techniques. Concurrently, Benford’s Law—a statistical principle often used in forensic accounting—has demonstrated efficacy in detecting anomalies within naturally occurring numerical datasets. This study explores a hybrid fraud detection approach that integrates Benford’s Law with supervised machine learning algorithms, including Logistic Regression, Random Forest, and k-Nearest Neighbors. Using the publicly available European credit card fraud …

Phishing Attacks And Prevention, Ruth Johnson

Cybersecurity Undergraduate Research Showcase

Phishing attacks have been the number one leading cause of identity theft and financial theft since 1990. The internet is one of the leading places where individuals’ identity is stolen. Many businesses and government agencies have been at risk of cyber phishing attacks from foreign countries. Attacks on Several U.S. federal government agencies have been hit in a global cyberattack by Russian cybercriminals that exploit a vulnerability in widely used software, according to a top us cybersecurity agency (Lyngaas, Government hit cyber-attacks, 2023).

Phishing attacks are cybercrimes where one or many individuals steal sensitive information like passwords, credit card information, …

How Can We Improve Our Security Measures To Safeguard Against Cyber Threats?, Mattea Trotter-Hicks

Cybersecurity Undergraduate Research Showcase

Many people face the issue of having their information stolen without their knowledge of what is happening. I understand that some people don’t pay attention to everything when it comes to making sure their information is being secured properly. There must be set stages for those who don’t know technology as well and will need help with knowing what to do. There are many stories of people going through issues with getting hacked or scammed out of their money or important information. We are going to dive into finding ways to fix the outcome of others knowing what to do …

Securing Biometric Data, Alyssa F. Carroll

Cybersecurity Undergraduate Research Showcase

Biometric data has been widely adopted across various sectors, including digital identity, artificial intelligence (AI), border control, digital wallets, and national identification systems. While biometric identifiers—such as fingerprints, retina scans, and facial recognition—offer reliable and convenient authentication, they also raise significant concerns regarding privacy and security. This paper examines how biometric data is stored, the vulnerabilities it faces, and the most effective methods for safeguarding it. By highlighting the critical importance of biometric data protection, this study reviews current research on approaches, strategies, and policies that enhance security while preserving the functionality and efficiency of biometric systems.

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, …