Information Security Commons^™

Bridging The Gap: Understanding And Mitigating Csrf Threats In Service Worker Environments, Sivakanesan Dhanushkanda, Mustafa A. Ibrahim

Graduate Student Government Association Research Conference

Progressive Web Applications (PWAs) are gaining popularity due to their rich features. Service Workers (SWs), one of its integral components, make this possible by providing users with offline functionality, improved performance, and effective caching techniques. SWs act as proxies positioned between the client browser and the web server, capable of intercepting requests and responses. Recent research has revealed that, despite being designed with security in mind, there are ways to circumvent these security precautions and launch various attacks.

Sensitive functions in JavaScript are functions that can introduce security vulnerabilities if not properly coded or validated. These functions can manipulate the …

Exploring School Teachers' Cyber Security Awareness, Experiences, And Practices In The Digital Age, R Ravichandran, Sonam Singh, P Sasikala

Journal of Cybersecurity Education, Research and Practice

This study investigates the awareness and practices of cyber security among school teachers, exploring their understanding of cyber threats, online behaviours, and response mechanisms to cyber incidents. A structured questionnaire was administered to gather data on demographic information, cyber security training, online practices, and experiences with cybercrime. The findings reveal varying levels of awareness among teachers, with many reporting limited knowledge of prevalent cyber threats such as phishing and identity theft. Despite the increasing reliance on digital tools for teaching, a significant number of respondents indicated a lack of formal training in cyber security. The study highlights the necessity for …

"It's Definitely New And Different...It's Really Engaging": Understanding The Power Of Storytelling Towards Secure Password Creation, Rizu Paudel, Mahdi Nasrullah Al-Ameen

Computer Science Student Research

There is a dearth in existing literature to attain systematic understanding of leveraging digital storytelling in security designs. As we begin to address this gap, we focused on user authentication where the existing password composition policies and password meters often fail to help users around creating a strong and memorable password. To this end, we conducted a lab study with 19 participants, where we updated our initial designs in an iterative manner based on their feedback. We then conducted a between-subject online study with 104 participants over Amazon Mechanical Turk to evaluate our designs. We found that all of our …

Computing In The Commonwealth: Specialized Education In Computer Science And Information Technology For High School Students In Virginia – An Environmental Scan, Amy Corning, Jonathan D. Becker, Jon Graham, James Carrigan, Keisha Tennessee

ICRE Publications

Over the past two decades, Virginia has invested substantially in STEM education, in part through specialized programs focused on computer science and information technology (CS/IT). This study represents the first effort to identify Virginia’s specialized secondary CS/IT programs and examine them collectively. Findings from the statewide environmental scan indicate that the programs are delivered through a wide variety of institutional structures, including Governor’s STEM Academies, Governor’s Schools, specialty centers, and academies, but most often through Career and Technical Education (CTE) centers. Programs tend to be concentrated in metropolitan areas, and some rural divisions may not be served. The programs provide …

A Survey-Based Quantitative Analysis Of Stress Factors And Their Impacts Among Cybersecurity Professionals, Sunil Arora, John D. Hastings

Research & Publications

This study investigates the prevalence and underlying causes of work-related stress and burnout among cybersecurity professionals using a quantitative survey approach guided by the Job Demands-Resources model. Analysis of responses from 50 cybersecurity practitioners reveals an alarming reality: 44% report experiencing severe work-related stress and burnout, while an additional 28% are uncertain about their condition. The demanding nature of cybersecurity roles, unrealistic expectations, and unsupportive organizational cultures emerge as primary factors fueling this crisis. Notably, 66% of respondents perceive cybersecurity jobs as more stressful than other IT positions, with 84% facing additional challenges due to the pandemic and recent high-profile …

Technology-Facilitated Abuse (Tfa): Analyzing Trends, Tactics, And Victim Responses On Reddit, Solomon G. Dandekar

Computer Science and Engineering Theses - Archive

The increasing integration of technology into daily life has provided numerous benefits but also significant risks, particularly when exploited by malicious actors in cases of technology facilitated abuse (TFA). Per- petrators can misuse technology to monitor, control, and intimidate their partners, random strangers, etc. exacerbating cycles of abuse. From location tracking and cellphone surveillance to smart device manipula- tion, spyware, and doxing, digital tools have become powerful instruments for coercion and control. This research project investigates the role of technology in stalking and harassment by analyzing discussions on a relevant subreddit where victims share their experiences, strategies for coping, and …

Scalable Approaches Towards Characterizing And Mitigating Emerging Phishing Scams, Sayak Saha Roy

Computer Science and Engineering Dissertations - Archive

Phishing scams are among the most dangerous and persistent forms of cybercrime, leveraging social engineering to exploit human behavior and obtain sensitive information, leading to widespread identity theft and data breaches. In the past year, these attacks have resulted in financial losses exceeding $10 billion in the United States alone. As phishing scams continue to evolve, they have not only expanded in scale but also grown in sophistication, spreading rapidly across social media and employing adversarial techniques to evade detection by anti-scam tools. The situation is further exacerbated by the availability of advanced phishing kits, and more recently, generative AI, …

Towards Smart Farming: Image-Based Crop Health Assessment And Disease Diagnosis Using Deep Learning Techniques, Kristina Botova

Master's Theses or Doctor of Nursing Practice

Accurate crop monitoring is essential for optimizing agricultural productivity and ensuring food security. This study presents a comprehensive deep learning framework for image crop type recognition, health status prediction, and disease detection using multiple Convolutional Neural Network (CNN) models. The proposed approach uses open-source datasets consisting of five crop types (apple, corn, grape, potato, tomato), varying health conditions, and common diseases. By deploying specialized CNN architecture focused on each task, the system achieves a high accuracy of 99.25% in classifying crop types, identifying health status, and detecting specific diseases. Compared to a single CNN model, the use of the proposed …

The Gradient Puppeteer: Adversarial Domination In Gradient Leakage Attacks Through Model Poisoning, Kunlan Xiang, Haomiao Yang, Meng Hao, Shaofeng Li, Haoxin Wang, Zikang Ding, Wenbo Jiang, Tianwei Zhang

Research Collection School Of Computing and Information Systems

In Federated Learning (FL), clients share gradients with a central server while keeping their data local. However, malicious servers could deliberately manipulate the models to reconstruct clients' data from shared gradients, posing significant privacy risks. Although such Active Gradient Leakage Attacks (AGLAs) have been widely studied, they suffer from two severe limitations: 1) coverage: no existing AGLAs can reconstruct all samples in a batch from the shared gradients; 2) stealthiness: no existing AGLAs can evade principled checks of clients. In this paper, we address these limitations with two core contributions. First, we introduce a new theoretical analysis approach, which uniformly …

Joint 3d Beamforming-And-Trajectory Design For Uav-Satellite Uplink Covert Communication, Jihong Yu, Yuting Cai, Shihao Yan, Yun Li, Jingjing Wang, Jiahao Liu, Jianping An

Research outputs 2022 to 2026

In this paper,we study uplink covert communication in a space-air system,where an unmanned aerial vehicle (UAV) transmits sensitive data to a Geosynchronous Earth Orbit (GEO) satellite while preventing the transmission action from being discovered by a warden. We derive the optimal decision threshold of the warden. We investigate the 3-dimensional (3D) beamformer and 3D trajectory design for the transmitter UAV against this optimum warden to maximize the covert transmission rate in the presence of imperfect channel state information and uncertain noise. Due to the non-convex structure and dependence between beamforming vectors and locations of the transmitter UAV,we develop a decoupling …

Zero Day Ransomware Detection With Pulse: Function Classification With Transformer Models And Assembly Language, Matthew Gaber, Mohiuddin Ahmed, Helge Janicke

Research outputs 2022 to 2026

Finding automated AI techniques to proactively defend against malware has become increasingly critical. The ability of an AI model to correctly classify novel malware is dependent on the quality of the features it is trained with and the authenticity of the features is dependent on the analysis tool. Peekaboo, a Dynamic Binary Instrumentation tool defeats evasive malware to capture its genuine behaviour. The ransomware Assembly instructions captured by Peekaboo, follow Zipf's law, a principle also observed in natural languages, indicating Transformer models are particularly well-suited to binary classification. We propose Pulse, a novel framework for zero day ransomware detection with …

Tedvil: Leveraging Transformer-Based Embeddings For Vulnerability Detection In Lifted Code, Gary Mccully, John Hastings, Shengjie Xu

Research & Publications

Ransomware and other malware inflict devastating financial and operational damage on organizations worldwide by exploiting deeply embedded, hard-to-detect vulnerabilities in their systems. Detecting these vulnerabilities in compiled code before malicious actors exploit them remains a critical challenge in cybersecurity. This research introduces TEDVIL (Transformer-based Embeddings for Discovering Vulnerabilities in Lifted Code), a novel framework which uses transformer-based embeddings to train neural networks to detect vulnerabilities in lifted code. The framework was implemented using bidirectional (BERT and RoBERTa) and unidirectional (GPT-1 and GPT-2) transformer-based models to generate embeddings for training Long Short-Term Memory (LSTM) neural networks to detect stack-based buffer overflows …

Insights In Cybersecurity Of A Smart Campus - A Review, Mircea Ţălu

Journal of Cybersecurity Education, Research and Practice

The profound impact of the Internet of Things (IoT) on various fronts, is driven by technological advancements, the ubiquitous spread of information, and the emergence of transformative events. IoT presents a diverse array of possibilities within university environments, fostering a more connected and enhanced educational experience. This research undertakes a comprehensive review of existing literature to provide context to the IoT and underscore its crucial significance in the realm of smart campuses. Additionally, the paper explores the intricate connections between IoT and key concepts such as cybersecurity and wireless sensor networks to present a holistic perspective. It delves into the …

Signal-Based Error Handling: Case Study Using The Bathymetric Attributed Grid Library, Anthony R. Papetti

Honors Theses and Capstones

No abstract provided.

A Trust-By-Learning Framework For Secure 6g Wireless Networks Under Native Generative Ai Attacks, Md Shirajum Munir, Sravanthi Proddatoori, Manjushree Muralidhara, Trinidad Mario Dena, Walid Saad, Zhu Han, Sachin Shetty

Center for Secure and Intelligent Critical Systems (CSICS) Publications

Sixth-generation (6G) wireless networks will become vulnerable due to native generative AI (GenAI)-driven intelligent poisoning attacks in both the radio unit and the core network. In particular, network parameters and metrics in cross-layer design pose fundamentally uncertain conditions and can be compromised through the native GenAI mechanism, which leverages data augmentation and reconstruction capabilities. This work investigates the capabilities of native GenAI to create novel poisoning attacks in wireless networks, while investigating their impact through uncertainty-informed root analysis. Then, detected attacks are mitigated by developing a trustworthy service aggregation in the wireless network. First, a joint decision problem is formulated …

A Systematic Review And Taxonomy For Privacy Breach Classification: Trends, Gaps, And Future Directions, Clint Fuchs, John Hastings

Research & Publications

In response to the rising frequency and complexity of data breaches and evolving global privacy regulations, this study presents a comprehensive examination of academic literature on the classification of privacy breaches and violations between 2010-2024. Through a systematic literature review, a corpus of screened studies was assembled and analyzed to identify primary research themes, emerging trends, and gaps in the field. A novel taxonomy is introduced to guide efforts by categorizing research efforts into seven domains: breach classification, report classification, breach detection, threat detection, breach prediction, risk analysis, and threat classification. An analysis reveals that breach classification and detection dominate …

Dynamic Analysis Of Malware Detection Using Customized Payloads: Examining The Effectiveness Of Manual And Automated Approaches In Web Applications, Jiban Krisna Das

College of Graduate Studies: Theses & Dissertations

Web applications are becoming the prime targets for cyber-attacks, where SQL injection (SQLi) and Cross Site Scripting (XSS) are the most exploited vulnerabilities. The study explores a novel approach using customized payloads to examine the effectiveness of manual and automated techniques of malware detection. This dynamic approach can effectively generate attack payloads and identify the vulnerabilities in a website thereby strengthening website security measures. This research focuses on dynamic analysis in a controlled environment while testing and analyzing SQL and XSS payloads under varying security conditions. This quantitative analysis involves crafting targeted payloads to bypass Web Application Firewall (WAF) filters …

Digital Evidence In Cybersecurity: Legal Constraints And Technical Hurdles, Steffany Butler

Master's Theses and Doctoral Dissertations

The increasing use of digital technologies such as Internet of Things devices, cloud computing, and networked information systems has made digital evidence essential to modern cybersecurity investigations. Digital evidence supports the reconstruction of cyber incidents, identification of responsible parties, and legal proceedings. However, its collection and preservation pose substantial technical and legal challenges. Rapid technological change, strong encryption, data volatility, cloud-based and distributed storage, and variations in jurisdictional privacy and evidentiary laws complicate the timely, reliable, and legally admissible acquisition of digital evidence. This study addresses how investigators can effectively collect and preserve digital evidence while maintaining data integrity, legal …

Digital Forensics & Artificial Intelligence: Senior Honors Project Research Report, Noah Shelton Kasir

Senior Honors Theses and Projects

This project studied how current artificial intelligence large language models could be used to learn digital forensics and anti-forensics techniques compared to traditional search engines such as Google Search. This project aimed to answer the question “Can an ordinary person use AI to learn both anti-forensics and traditional digital forensics skills effectively and efficiently?”. The project research was divided into two distinct phases. Phase one consisted of the creation of a fictional case by acting as a layperson using the help of the Microsoft Copilot AI tool. This case consisted of a layperson “suspect” attempting to learn multiple anti-forensics techniques …

Charge Your Clients: Payable Secure Computation And Its Applications, Cong Zhang, Liqiang Peng, Weiran Liu, Shuaishuai Li, Meng Hao, Lei Zhang, Dongdai Lin

Research Collection School Of Computing and Information Systems

The online realm has witnessed a surge in the buying and selling of data, prompting the emergence of dedicated data marketplaces. These platforms cater to servers (sellers), enabling them to set prices for access to their data, and clients (buyers), who can subsequently purchase these data, thereby streamlining and facilitating such transactions. However, the current data market is primarily confronted with the following issues. Firstly, they fail to protect client privacy, presupposing that clients submit their queries in plaintext. Secondly, these models are susceptible to being impacted by malicious client behavior, for example, enabling clients to potentially engage in arbitrage …

Exploring Research And Tools In Ai Security: A Systematic Mapping Study, Sidhant Narula, Mohammad Ghasemigol, Javier Carnerero-Cano, Amanda Minnich, Emil Lupu, Daniel Takabi

School of Cybersecurity Faculty Publications

With the pervasive integration of artificial intelligence (AI) in various facets of modern technology, the importance of AI security has been thrust into the spotlight. The field is rapidly evolving, with new challenges and solutions emerging at a swift pace. However, the breadth and depth of AI security research have not been comprehensively mapped in recent times, presenting a crucial need for an extensive review and synthesis of existing literature. Given the increasing reliance on AI in critical domains such as healthcare, finance, and national security, ensuring the resilience and trustworthiness of these systems is imperative. This survey fulfills the …

Privacy-Preserved And Incentivized Knowledge Sharing For Reinforced-Learning Based Iot Platform Security, Weichao Wang, Md Morshed Alam, Yu Wang

School of Cybersecurity Faculty Publications

With the fast development and deep penetration of IoT devices and smart environments, using localized machine learning models to detect malicious activities has also been developed and deployed. However, these isolated learning models and results cannot be effectively federated together because of privacy concerns and lack of incentivization. This paper proposed several mechanisms to solve the problem. A verification method was designed for phased learning results to protect user privacy and prevent individual parties from manipulating the verification selection. The paper also presented an incentive method based on delay of distribution of the latest federated learning results. Extensive simulations were …

Zero Trust Architecture As A Risk Countermeasure In Small-Medium Enterprises And Advanced Technology Systems, Ahmed M. Abdelmagid, Rafael Diaz

Engineering Management & Systems Engineering Faculty Publications

The growing sophistication of cyberattacks exposes small- and medium-sized businesses (SMBs) to a widening range of security risks. As these threats evolve in complexity, the need for advanced security measures becomes increasingly pressing. This necessitates a proactive approach to defending against potential cyber intrusions. Emerging technologies, such as blockchain, artificial intelligence, and Zero Trust security framework, offer crucial tools for strengthening the digital infrastructure of SMBs. The Zero Trust architecture (ZTA) holds significant promise as a critical strategy for protecting SMBs. While existing literature explores the implementation of ZTA in various business settings, discussions specifically addressing the financial, human resource, …

Secure Federated Learning Via Neural Cryptography With Homomorphic Operations, Espen Sele, Ferhat Ozgur Catak, Jungwon Seo, Murat Kuzlu

Engineering Technology Faculty Publications

This study examines neural cryptography with homomorphic operations as an alternative secure aggregation method for federated learning (FL). It proposes a novel neural cryptographic system supporting homomorphic addition on fixed-point encrypted data, and consisting of three networks, namely (1) an encryption network (Alice), (2) a homomorphic network (HO), and (3) a decryption network (Bob), along with an adversarial Eve network. Using the MNIST dataset, the proposed Neural Homomorphic Operation System (NHOS) is evaluated against a plaintext baseline and the CKKS scheme, a widely used public-key homomorphic encryption method. The results show that the proposed NHOS approach offers a satisfying performance, …

Silent Sabotage: Identifying And Preventing Cyber Attacks From Inside Actors, Autumn Groen

Williams Honors College, Honors Research Projects

Cyber-attacks are becoming increasingly common and damaging as technology advances each year. Many businesses cannot afford the latest security technologies, and even with the highest security measures, there can still be room for employee error or insider threats that are not taken into account. It is crucial to keep these factors in mind when securing a business network of any size or financial standing.This project will aim to simulate a business environment by first building a small network with three routers and a switch, and implementing some of the common best practices for network hardening from credible organizations like NIST …

A Governance-Centric Framework For Strengthening Healthcare Cybersecurity: A Systems Perspective, Sujatha Alla, Sai Gireesh Komaragiri, Teresa Duvall, Satluk Karahan, Nagesh Bheesetty, Vijay Kumar Chattu

Engineering Management & Systems Engineering Faculty Publications

Healthcare systems face unprecedented security and privacy challenges due to increasing digitization and interconnectedness. This paper provides a comprehensive analysis of these challenges by examining various cyberattacks, defensive mechanisms, and governance frameworks within modern healthcare infrastructure. The research systematically categorizes prevalent security threats, such as ransomware, insider threats, and data breaches, identifying vulnerabilities specific to healthcare systems. Furthermore, the study evaluates current defensive strategies, including encryption techniques, access control systems, and intrusion detection tools, assessing their effectiveness against complex cyber threats. A key focus is placed on governance structures and their role in cybersecurity resilience. The research explores how regulatory …

Potsdam: Pareto Optimization Targeting Security, Data, And Mediation, J Peter Brady

Dartmouth College Ph.D Dissertations

Given the growing amount and variety of data handled by modern systems, it is crucial to guarantee the accuracy and protection of input data without errors or malicious intentions. The need to improve security in software programs often conflicts with the assurance of maximum performance, making developers and maintainers hesitant to incorporate more testing.

LangSec (Language-Theoretic Security) is a security approach that treats input validation as a formal language recognition problem, ensuring that only well-defined, unambiguous inputs are processed to eliminate exploitable parsing flaws. This dissertation explores integrating LangSec principles with Pareto optimization to enhance safety and robustness in digital …

Cyberattacks On Port Infrastructures: A Decade Of Trends, Incidents, And Mitigation Strategies (2011-2024), Minodora Badea, Olga Bucovetchi, Adrian V. Gheorghe, Gabriel Raicu

Engineering Management & Systems Engineering Faculty Publications

Port infrastructures are critical to global trade, handling over 80% of the world's cargo by volume. However, their increasing reliance on digital technologies has exposed them to a wide range of cyber threats. This paper provides a comprehensive analysis of cyberattacks targeting port infrastructures from 2011 to the present. We examine the types of attacks, geographical distribution, notable incidents, and underlying vulnerabilities. Additionally, we discuss mitigation strategies and future directions for enhancing cybersecurity in the maritime sector. Our findings highlight the urgent need for robust regulatory frameworks, advanced technological solutions, and collaborative efforts to safeguard critical port operations.

The Effectiveness Of Tech Support Fraud In Damaging Older Individual’S Financial Security, Vanessa Perera

Theses : Honours

This study discovers the tactics employed to create detrimental effects upon older people impacted from fraudulent tech-support incidents. It examines social engineering, and financial confusion of older people. This is significant considering adaptations towards digital banking and payment management. This research looked at online and active over 65s. Using largely qualitative approaches over 65s were interviewed and responses validated against cyber-professionals’ responses. This identified three key findings: older adults feel confused and misunderstand tech support scams; threat actors build trust by pretending to offer technical help but use this to deceive their victims; and older adults face serious social and …

Building Cyber Resilience: Educational Programs In K-12 Education, Mildred Jones, Vukica Jovanovic, Petros Katsioloudis

Engineering Technology Faculty Publications

The article discusses the challenges of teaching cybersecurity in K-12 education. Topics mentioned include the lack of access to resources and appropriate professional development, the career and technical education cybersecurity pathways, the fundamental pathways for cybersecurity and information technology and the results of program evaluation in several local community high schools from 2021 and 2022.