Information Security Commons^™

Phishing Restraint: University Simulated Phishing Campaigns, Alexander M. Abou Khir

Cybersecurity Undergraduate Research Showcase

Universities face heightened vulnerability to phishing attacks due to their open information-sharing culture and diverse user populations. This study examines how phishing exploits human factors within campus environments and evaluates three major training strategies: embedded phishing, microlearning, and role-based instruction to understand their individual and combined effectiveness. I explored studies that implement these strategies in pairs and use the strategies alone, identified trends in susceptibility reduction, behavioral reinforcement, and contextual relevance. I suggest that, while each method independently improves user awareness, multiple approaches offer stronger, more adaptable protection by addressing both psychological triggers and role-specific risks. The paper contributes a …

Hijacking The Prompt: A Survey Of Prompt Injection Attacks, Detection, And Defense In Large Language Models, Edward J. Griggs

Cybersecurity Undergraduate Research Showcase

Prompt injection attacks, ranked the number-one vulnerability in AI systems by OWASP's 2025 Top 10 for Large Language Model Applications, remain largely unsolved, and this survey examines why. As large language models (LLMs) are deployed across enterprise workflows, agentic systems, and consumer tools, their fundamental inability to distinguish trusted instructions from untrusted user data has created a persistent and expanding attack surface. This paper presents a structured taxonomy of prompt injection attack vectors, including direct injection, indirect injection, multimodal attacks, tool and agent exploitation, hybrid chained techniques, and autonomous propagating threats. These vectors are mapped across five impact categories (data …

Limitations Of Signature-Based Network Intrusion Detection Under Modern Traffic Conditions, Henry Guidry

Cybersecurity Undergraduate Research Showcase

Network Intrusion Detection Systems are tools used to monitor network traffic and alert to suspicious or harmful activity before it can cause harm. Signature-based versions of these systems are a foundation for intrusion detection, operating by finding common patterns and forming malicious signatures. However, three developments in modern network environments have greatly impacted the significance of Network Intrusion Detection Systems. These three developments are the near-complete adoption of end-to-end encryption, the use of sophisticated packet fragmentation techniques, and the processing demands of high-throughput networks. Encryption makes deep packet inspection practically infeasible by transforming inspectable payloads into ciphertext, forcing NIDS to …

Viability Of Widely Used Encryption Schemes In Drone Transmission, Emanuel Yasir Nelson

Cybersecurity Undergraduate Research Showcase

This paper presents throughout research on the security issues related to drone transmission. These topics were addressed and explained, in particular the aspects relating to cybersecurity, for utmost clarity. These include threats and vulnerabilities, drone transmission the impact of encryption on latency, and the details of the encryption methods AES-128, AES-256, and ChaCha20 that were used in the experiment described in the paper. Each encryption method performance was measured and outputted by the Python code developed and used in the experiment. Afterwards, the performance of each method was analyzed in relation to their decryption time, encryption time, end to end …

Behavioral Detection Methods For Automated Mcp Server Vulnerability Assessment, Christian Coleman

Cybersecurity Undergraduate Research Showcase

The Model Context Protocol (MCP) has emerged as a critical standard for connecting AI agents to external data sources and tools. Still, its adoption has introduced significant security vulnerabilities across multiple attack surfaces. While recent research has catalogued extensive vulnerability taxonomies and attack implementations, automated detection methodologies remain limited. Current detection tools primarily employ static code analysis, which fails to identify behavioral vulnerabilities that only manifest during runtime server interactions. This study explores behavioral detection approaches for identifying MCP server vulnerabilities through systematic query-based testing, with particular emphasis on context manipulation techniques. Preliminary analysis of existing vulnerability research reveals 48 …

"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.

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 …

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, …

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.

Digital Humanities: Using Computational Methods On Literature To Understand Human-Water Relations, Ariel Yang

Cybersecurity Undergraduate Research Showcase

By using computational techniques to analyze literature, deeper insights can be gained into human-water relationships across different historical and cultural contexts. Natural Language Processing (NLP) and other data science methods can explore applications of traditional ecological knowledge (TEK) and underlying emotions or beliefs in literature to help understand sustainability. Protecting this sensitive cultural data through ethical applications can further secure future implementations of policies, urban planning, and environmental relationships.

Security Vulnerabilities In Mobile Operating Systems Used In Iot Devices: An Examination Of Current Challenges And Countermeasures, Isain Cortes Jr.

Cybersecurity Undergraduate Research Showcase

No abstract provided.

A Dynamical Systems Approach For Modeling Malware Propagating Through A Network And Potential Solutions Towards Mitigating Spread, James Johnson

Cybersecurity Undergraduate Research Showcase

Many people draw close parallels between malware propagating through a network and an epidemic spreading through a population. Epidemics are often modeled by a Susceptible-Infected-Recovered (SIR) model, in which a similar system of equations can model the spread of a virus through a computer network, and can be simplified when making assumptions about the network itself and its fixed number of nodes and edges. In this instance, malware propagating in a network also should reflect the network it is propagating through, in which the dynamical system will factor in the nodes of the network and their properties. The system itself …

Phishing Emails: An Evolving Cyberattack, Brooke Waltz

Cybersecurity Undergraduate Research Showcase

This paper describes the history of phishing attacks and how they turned into cyberattacks, focusing on companies. Over the course of 34 years, phishing has been evolving at an alarming rate, especially with AI now coming into play. As phishing attacks have become more prominent towards companies, there has been an increase in financial loss and data breaches, resulting in a loss of trust in companies. With this loss, companies are trying to find solutions to this problem. Some notable attacks were the RSA breach in 2011, the Texas Energy Company in 2014, and the ILOVEYOU virus in 2000. They …

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 …

What Students Have To Say On Data Privacy For Educational Technology, Stephanie Choi

Cybersecurity Undergraduate Research Showcase

The literature on data privacy in terms of educational technology is a growing area of study. The perspective of educators has been captured extensively. However, the literature on students’ perspectives is missing, which is what we explore in this paper. We use a pragmatic qualitative approach with an experiential lens to capture students’ attitudes towards data privacy in terms of educational technology. We identified preliminary, common themes that appeared in the survey responses. The paper concludes by calling for more research on how students perceive data privacy in terms of educational technology.

A Case Study Of The Crashoverride Malware, Its Effects And Possible Countermeasures, Samuel Rector

Cybersecurity Undergraduate Research Showcase

CRASHOVERRIDE is a modular malware tailor-made for electric grid Industrial Control System (ICS) equipment and was deployed by a group named ELECTRUM in a Ukrainian substation. The malware would launch a protocol exploit to flip breakers and would then wipe the system of ICS files. Finally, it would execute a Denial Of Service (DOS) attack on protective relays. In effect, months of damage and thousands out of power. However, due to oversights the malware only caused a brief power outage. Though the implications of the malware are cause for researching and implementing countermeasures against others to come. The CISA recommends …

Investigating Vulnerabilities In The Bluetooth Host Layer In Linux, Jack Dibari

Cybersecurity Undergraduate Research Showcase

This paper investigates vulnerabilities within the Bluetooth host layer in Linux systems. It examines the Bluetooth protocol's evolution, focusing on its implementation in Linux, particularly through the BlueZ host software. Various vulnerabilities, including BleedingTooth, BLESA, and SweynTooth, are analyzed.

Data Profits Vs. Privacy Rights: Ethical Concerns In Data Commerce, Amiah Armstrong

Cybersecurity Undergraduate Research Showcase

In today’s digital age, the collection and sale of customer data for advertising is gaining a growing number of ethical concerns. The act of amassing extensive datasets encompassing customer preferences, behaviors, and personal information raises questions of its true purpose. It is widely acknowledged that companies track and store their customer’s digital activities under the pretext of benefiting the customer, but at what cost? Are users aware of how much of their data is being collected? Do they understand the trade-off between personalized services and the potential invasion of their privacy? This paper aims to show the advantages and disadvantages …

Tapped In: The Rise Of Mobile Malware, Chrystofuer Davenport

Cybersecurity Undergraduate Research Showcase

As the world of technology continues to evolve and become more advanced with our life, so do the dangers and threats that are determined to hinder that development. Malware continues to be a danger to internet surfers or people with access to technology. At first it was an issue that existed only with computers but since the evolution of smartphones in the early twenty-first century, mobile devices have been a target for multiple malware viruses. It’s important to be aware of what different viruses are capable of doing and how to avoid them when they are encountered. Even though computers …

The Transformative Integration Of Artificial Intelligence With Cmmc And Nist 800-171 For Advanced Risk Management And Compliance, Mia Lunati

Cybersecurity Undergraduate Research Showcase

This paper explores the transformative potential of integrating Artificial Intelligence (AI) with established cybersecurity frameworks such as the Cybersecurity Maturity Model Certification (CMMC) and the National Institute of Standards and Technology (NIST) Special Publication 800-171. The thesis argues that the relationship between AI and these frameworks has the capacity to transform risk management in cybersecurity, where it could serve as a critical element in threat mitigation. In addition to addressing AI’s capabilities, this paper acknowledges the risks and limitations of these systems, highlighting the need for extensive research and monitoring when relying on AI. One must understand boundaries when integrating …

The Vulnerabilities To The Rsa Algorithm And Future Alternative Algorithms To Improve Security, James Johnson

Cybersecurity Undergraduate Research Showcase

The RSA encryption algorithm has secured many large systems, including bank systems, data encryption in emails, several online transactions, etc. Benefiting from the use of asymmetric cryptography and properties of number theory, RSA was widely regarded as one of most difficult algorithms to decrypt without a key, especially since by brute force, breaking the algorithm would take thousands of years. However, in recent times, research has shown that RSA is getting closer to being efficiently decrypted classically, using algebraic methods, (fully cracked through limited bits) in which elliptic-curve cryptography has been thought of as the alternative that is stronger than …

The Underrepresentation Of Black Females In Cybersecurity, Makendra Latrice Crosby

Cybersecurity Undergraduate Research Showcase

The significance of cybersecurity methods, strategies, and programs in protecting computers and electronic devices is crucial throughout the technological infrastructure. Despite the considerable growth in the cybersecurity field and its expansive workforce, there exists a notable underrepresentation, specifically among Black/African American females. This study examines the barriers hindering the inclusion of Black women in the cybersecurity workforce such as socioeconomic factors, limited educational access, biases, and workplace culture. The urgency of addressing these challenges calls for solutions such as education programs, mentorship initiatives, creating inclusive workplace environments, and promoting advocacy and increased awareness within the cybersecurity field. Additionally, this paper …

Rising Threat - Deepfakes And National Security In The Age Of Digital Deception, Dougo Kone-Sow

Cybersecurity Undergraduate Research Showcase

This paper delves into the intricate landscape of deepfakes, exploring their genesis, capabilities, and far-reaching implications. The rise of deepfake technology presents an unprecedented threat to American national security, propagating disinformation and manipulation across various media formats. Notably, deepfakes have evolved from a historical backdrop of disinformation campaigns, merging with the advancements of artificial intelligence (AI) and machine learning to craft convincing but false multimedia content.

Examining the capabilities of deepfakes reveals their potential for misuse, evidenced by instances targeting individuals, companies, and even influencing political events like the 2020 U.S. elections. The paper highlights the direct threats posed by …

New Paths Of Attacks: Revealing The Adaptive Integration Of Artificial Intelligence In Evolving Cyber Threats Targeting Social Media Users And Their Data, Larry Teasley

Cybersecurity Undergraduate Research Showcase

The intersection between artificial intelligence tools and social media has opened doors to numerous opportunities and risks. This research delves into the escalating threat landscape in a society heavily dependent on social media. Despite the efforts by social media companies and cybersecurity professionals to mitigate cyber-attacks, the constant advancements of new technologies render social media platforms increasingly vulnerable. Malicious actors exploit generative AI to collect user data, enhancing cyber threats on social media. Notably, generative AI amplifies phishing attacks, disseminates false information, and propagates propaganda, posing substantial challenges to platform security. Ease access to large language models (LLMs) further complicates …

Privacy Concerns And Proposed Solutions With Iot In Wearable Technology, Hyacinth Abad

Cybersecurity Undergraduate Research Showcase

This paper examines the dynamic relationship between IoT cybersecurity and privacy concerns associated with wearable devices. IoT, with its exponential growth, presents both opportunities and challenges in terms of accessibility, integrity, availability, scalability, confidentiality, and interoperability. Cybersecurity concerns arise as diverse attack surfaces exploit vulnerabilities in IoT systems, necessitating robust defenses. In the field of wearable technology, these devices offer benefits like health data tracking and real-time communication. However, the adoption of these devices raises privacy concerns. The paper explores proposed solutions, including mechanisms for user-controlled data collection, the implementation of Virtual Trip Line (VTL) and virtual wall approaches, and …

A Review Of Threat Vectors To Dna Sequencing Pipelines, Tyler Rector

Cybersecurity Undergraduate Research Showcase

Bioinformatics is a steadily growing field that focuses on the intersection of biology with computer science. Tools and techniques developed within this field are quickly becoming fixtures in genomics, forensics, epidemiology, and bioengineering. The development and analysis of DNA sequencing and synthesis have enabled this significant rise in demand for bioinformatic tools. Notwithstanding, these bioinformatic tools have developed in a research context free of significant cybersecurity threats. With the significant growth of the field and the commercialization of genetic information, this is no longer the case. This paper examines the bioinformatic landscape through reviewing the biological and cybersecurity threats within …

Potential Security Vulnerabilities In Raspberry Pi Devices With Mitigation Strategies, Briana Tolleson

Cybersecurity Undergraduate Research Showcase

For this research project I used a Raspberry Pi device and conducted online research to investigate potential security vulnerabilities along with mitigation strategies. I configured the Raspberry Pi by using the proper peripherals such as an HDMI cord, a microUSB adapter that provided 5V and at least 700mA of current, a TV monitor, PiSwitch, SD Card, keyboard, and mouse. I installed the Rasbian operating system (OS). The process to install the Rasbian took about 10 minutes to boot starting at 21:08 on 10/27/2023 and ending at 21:18. 1,513 megabytes (MB) was written to the SD card running at (2.5 MB/sec). …

How Chatgpt Can Be Used As A Defense Mechanism For Cyber Attacks, Michelle Ayaim

Cybersecurity Undergraduate Research Showcase

The powers of OpenAI's groundbreaking AI language model, ChatGPT, startled millions of users when it was released in November. But for many, the tool's ability to further accomplish the goals of evil actors swiftly replaced their initial excitement with significant concerns. ChatGPT gives malicious actors additional ways to possibly compromise sophisticated cybersecurity software. Leaders in a sector that is currently suffering from a 38% global spike in data breaches in 2022 must acknowledge the rising influence of AI and take appropriate action. Cybercriminals are writing more complex and focused business email compromise (BEC) and other phishing emails with the assistance …

The Propagation And Execution Of Malware In Images, Piper Hall

Cybersecurity Undergraduate Research Showcase

Malware has become increasingly prolific and severe in its consequences as information systems mature and users become more reliant on computing in their daily lives. As cybercrime becomes more complex in its strategies, an often-overlooked manner of propagation is through images. In recent years, several high-profile vulnerabilities in image libraries have opened the door for threat actors to steal money and information from unsuspecting users. This paper will explore the mechanisms by which these exploits function and how they can be avoided.