Digital Commons Network^™

Automated, Modular, Agentless Adversarial Emulation In Cloud Environments For Higher Education And Student Training, Doc Harley

Senior Honors Theses

Currently, the leading technologies in the market of adversarial emulation are MITRE Caldera, Atomic Red Team by IBM, and multiple proprietary products that come with support packages for different vendors like AttackIQ, Cymulate, SafeBreach, and many more. While it is clear that much work has been done in the broad category of adversarial emulation, when it comes to open source solutions, there are no agentless options with built in automation and modularity that have good support for cloud environments. Agentless adversarial emulation provides a unique advantage in that it can be both simpler and a better representation of the true …

Rosenzweig's Elements And Universal History, Martin Zwick

Complex Systems Faculty Publications and Presentations

This paper uses Rosenzweig’s conception of the three elements of God, World, and Human from The Star of Redemption in a model of universal history. The model also has some relation to Rosenzweig’s geopolitical essay, Globus, which is very different from the meta-historical Star. Based on a systems-theoretic schema of events and processes, the model views human history in terms of three linked processes: a primary process labeled “World” – the origin and development of human society embedded in nature, a secondary process labeled “God” – the origin and development of the Axial religions and philosophies, and a …

Assessment Of Goose-Beaked Whale Responsesto Mid-Frequency Active Sonar Usinga Hierarchical Hidden Markov Model, Stacy L. De Ruiter, Erin A. Falcone, Shannon N. Coates, Brenda K. Rone, David A. Sweeney, Karin A. Dolan, Susan M. Jarvis, Russel D. Andrews, Stephanie L. Watwood, Gregory S. Schorr

University Faculty Publications and Creative Works

Background

Acoustic disturbance is increasingly recognized as an ecological concern, particularly at sea. In light of marine mammal stranding events associated with use of naval mid-frequency active sonar (MFAS), which often involve goose-beaked whales (Ziphius cavirostris), research has sought to detect and characterize Ziphius behavioral responses to MFAS.

Methods

We deployed Sound and Motion Recording and Telemetry (SMRT) tags on 13 Ziphius in the Southern California Bight. The study area includes the United States Navy’s Southern California Anti-submarine Warfare Range (SOAR), and deployments overlapped temporally with training exercises including MFAS use. We used hierarchical hidden Markov models (HHMMs), which provided …

Modeling And Simulation Of Target Characteristic Architecture Of Target Missile Based On Dodaf, Tuo Zhao, Yuqiao Liu, Yuan Ma, Yun Cheng, Shen Li

Journal of System Simulation

Abstract: In view of the problems of incomplete elements and missing architecture in the research of target characteristics of target missiles, this paper introduced the panoramic view, operational view, and capability view models in the DoDAF from the perspective of system engineering. According to the view development sequence of "panoramic description, operational decomposition, and capability matching", a target characteristic architecture of the target missile was constructed, which included target elements such as maneuvering characteristics and infrared radiation characteristics. The mapping relationship among "operational layer, capability layer, and target characteristic layer" of the target missile was obtained, and the architecture was …

Threat-Analysis Oriented Digital Twinning Of Ml-Powered Future Autonomous Weapon Systems, Thomas Neubert

Doctoral Dissertations and Master's Theses

Warfare is undergoing a rapid transformation with the integration of artificial intelligence (AI) and machine learning (ML) into autonomous weapon systems (AWS) for perception, decision support, and control. As these systems become more software-defined, their cyber attack surface expands across sensing, communications, autonomy logic, and human-machine interfaces. As human oversight diminishes, ensuring the cybersecurity, resilience, and reliability of these systems becomes critical to mission success. This thesis investigates how a digital twin-driven threat modeling framework that integrates system-centric analysis with adversary-informed methodologies can support structured cybersecurity vulnerability evaluation and defensive strategy development associated with ML-powered AWS. First, the study analyzes …

Next-Generation Democratic Cyber Statecraft - Balancing The Signal: Shutdown Shocks And Democratic Digital Governance, Scott M. Di Panni

School of Public Policy Capstones

This paper develops Next-Generation Democratic Cyber Statecraft (NG-DCS), a unified strategic doctrine for democratic governments to contest the cognitive domain against authoritarian adversaries. Drawing on twenty-six years of cross-national panel data (1999–2024) spanning 213 countries, game-theoretic modeling, and qualitative case analysis, the paper establishes three interconnected empirical and theoretical foundations. First, cross-national OLS regression across 160+ countries demonstrates that regime type is the dominant structural determinant of internet freedom (R²=0.615, β=2.513, p< 0.001), explaining more than twice the variance attributable to per-capita wealth (R²=0.268). Democratic governance, not economic development, produces open digital environments. Second, a two-way fixed effects (TWFE) difference-in-differences study exploiting government-ordered internet shutdowns as discrete policy interventions finds that digital restrictions causally degrade V-Dem governance quality by 0.21–0.38 standard deviations (p< 0.001 across all specifications). Treatment effects are immediate (β=−0.302 at k=0) and persist through five post-treatment years (β=−0.246 at k=+5), indicating structural rather than transitory governance damage. Parallel trends validation (p=0.352) and Callaway–Sant’Anna heterogeneity-robust estimation (ATT=−0.230, SE=0.077) support causal identification. Instrumental variable triangulation (2SLS β=−0.949, p=0.005) confirms that simultaneity was attenuating, not inflating, the primary estimates. Third, formal game-theoretic analysis reveals that the current U.S.–adversary equilibrium is (Restrain, Escalate)—the risk-dominant but Pareto-inferior outcome of a Stag Hunt structure. China, Russia, North Korea, and Venezuela each occupy structurally distinct positions (Stackelberg commitment, asymmetric two-level, autarky, and reactive trigger, respectively), requiring differentiated doctrinal responses rather than a uniform strategic playbook. Generative AI and algorithmic governance are shown to accelerate cognitive vulnerability by collapsing influence operation costs and exploiting engagement-optimized platform architectures that systematically degrade deliberative capacity in democratic populations.

Synthesis And Photophysical Studies Of Coumarin-Quinoline Derivatives, Nishrenika Pokhrel

Honors Theses

A new family of oxime-functionalized coumarin-quinoline derivatives, 5a and 5b, has been synthesized through a five-step procedure in high yields (45-98%). Compound 5a is designed as the sensing probe, while 5b serves as a model system to support mechanistic understanding. The sensing approach is based on the reactivity of the oxime group, which can undergo phosphorylation in the presence of organophosphate nerve agents. Based on this behavior, it is hypothesized that 5a can react irreversibly with a nerve agent mimic. The structures were fully characterized by NMR, FTIR, and HRMS. Photophysical properties of 5a were studied in various solvents, …

Analysis Of Traditional Wisdom For Ecological Sustainability In Tanzania: A Case Study Of Metaphorical Source Domains In Pangwa Ritual Texts, Winne Stephen Mtega, Angelus Mnenuka

Journal of Humanities and Social Sciences

Campaigns for ecological sustainability have gained a great currency in the contemporary academic discourse. Nonetheless, from time immemorial, Africans have pushed the ecological sustainability agenda through cultural taboos and regulated resource harvesting. Many African societies have embedded ecological consciousness in daily life expressions, and have intricately expressed it through literary and ritual texts. This study focuses on ecological awareness in the ritual texts of the Pangwa community. It analyses how environmental domains—such as land, seeds, and fruits—serve as the basis for metaphors in the Pangwa community to prove the use of wisdom to promote and sustain ecological practices (ecocriticism). The …

Sentisec: Combining Keyword Heuristics And Sentiment Modeling For Ai-Powered Threat Detection, Ridho Surya Kusuma, Erum Ashraf, Selvakumar Manickam, Shankar Karuppayah

Turkish Journal of Electrical Engineering and Computer Sciences

This work presents SENTISEC, a hybrid LLM-based threat detection framework designed to classify security logs by integrating keyword heuristics, domain-adapted sentiment scoring, and Retrieval-Augmented Generation (RAG). The system achieves an overall accuracy of 93.67%, with 91.46% macro recall, 89.07% macro F1, and 95.15% threat recall, while maintaining a low false-positive rate of 1.68%. Its methodology incorporates strict keyword and IOC matching, a domain-tuned DistilBERT sentiment module, hybrid BM25–MiniLM retrieval enhanced with BGE reranking, adaptive quantile-based threshold calibration, and SHAP-based explainability. Comparative evaluations against keyword-only, sentiment-only, classical machine-learning models, and DistilBERT-only baselines show that SENTISEC consistently improves both true-positive and true-negative …

On Message Encryption And Enhanced Security Using Protein Structure Information, Daniel Graham

Chemistry: Faculty Publications and Other Works

This is a lecture packet focused on several well-established encryption procedures. Included is a discussion of security enhancements brought about by incorporating protein structure information into the procedures.

Co-Electrospinning Polyacrylonitrile (Pan) / Polymer Of Intrinsic Microporosity-1 (Pim-1) For Electrochemical-Based Sensor For Pyridine Detection And Absorption, Samar A. Salim

Nanotechnology Research Centre

The electrospinning of the polymer of intrinsic microporosity-1 (PIM-1) poses challenges due to its limited solubility and tendency to form bead-like structures at high concentrations. This work details the synthesis and analysis of electrospun composite fibers made from polyacrylonitrile (PAN) and PIM-1 for electrochemical applications. The data analysis confirmed the successful incorporation of PIM-1 into the PAN matrix. The fiber characteristics were significantly influenced by PIM-1 loading (1–10%), resulting in fiber diameters ranging from 0.8 to 1.7 μm. A 10% concentration of PIM-1 results in the formation of macropores with diameters ranging from 0.5 to 1.7 μm. Optical analysis using …

Molecular Lung Imaging Following Exposure To Radiation Predicts Long-Term Survival In Rats, Anne V. Clough, Kathrina Mpala, Taheri Pardis, Laura Norwood Toro, Andreas M. Beyer, Tracy Gasperetti, Ming Zhao, Sarah Kerns, Heather A. Himburg, Said H. Audi

Mathematical and Statistical Science Faculty Research and Publications

Delayed effects of acute radiation exposure (DEARE), including radiation pneumonitis (lung-DEARE), develop weeks to months after radiation exposure. Pathway-targeted biomarkers that capture early oxidative stress and cell death could improve risk stratification and provide objective measures of mitigator efficacy. The objective was to test whether molecular lung imaging predicts long-term survival and mitigator response after irradiation. Rats received 13.5 Gy leg-out partial-body irradiation with a subset treated with the radiation-injury mitigator lisinopril. Rats underwent lung imaging at weeks 2 and 4 post-irradiation with ^99mTc-duramycin (cell death) and ^99mTc-HMPAO (oxidative stress). Plasma mitochondrial damage-associated molecular patterns (mtDAMPs) were also …

Intelligent Air Combat Decision-Making Method Based On Bigru And Priority Dynamic Sampling, Zhengkun Ding, Jiaqi Liu, Junzheng Xu, Yuezhu Xu, Xingmei Wang

Journal of System Simulation

Abstract: Current multi-agent reinforcement learning algorithms suffer from low efficiency in utilizing experience data and difficulties in setting appropriate learning rates. To address these issues, this paper proposed a BiGRU multi-agent PPO with priority sampling and dynamic learning rate. The algorithm incorporated a BiGRU network to enhance the policy network's ability to model temporal information. A priority partial sampling mechanism was introduced to improve the utilization efficiency of high-value experience data. Additionally, an improved Adam optimizer with dynamic learning rate adjustment was employed to address the challenge of learning rate configuration. Simulation experiment results demonstrate that the algorithm significantly …

Project Risk Management In Ai-Enabled Systems: Managing Ethical, Privacy, And Governance Risks, Onome Cynthia Anakanire

Harrisburg University Dissertations and Theses

This research examined how Artificial intelligence (AI) has been embedded in project-based work, particularly in finance and software industries, where it enables efficiency and assists in complex decision-making. However, these innovations introduce significant ethical, privacy, and governance risks that traditional project risk management frameworks fail to adequately address. This study investigated how project managers can systematically integrate the management of these emerging risks into AI-enabled projects. Using a qualitative research design, the study drew on semi-structured interviews with project managers, compliance officers, and AI developers in finance, software and related sectors. Supplementary data included internal project documentation and risk registers. …

The Tool/Weapon Duality Of Mathematics, Alexandre Borovik

Journal of Humanistic Mathematics

This paper outlines the principal moral and ethical issues of mathematics and existential choices a mathematician may face in his professional life. My text is a manifesto; it is a list of declarations rather than a systematic development of the theme. Indeed each section could be expanded into a paper on its own. I hope to write fairly soon a more detailed exposition.

Design Of Nanomaterial-Based Sensors For Enhanced Halogen Bonding, Ben H. Edelman, Charles W. Sheppard, Lucas A. Chuidian, Arielle Vinnikov, Felix Bevc, Lillian B. Hughes, Carol A. Parish, Michael C. Leopold

Chemistry Faculty Publications

Halogen bonding is a highly directional, noncovalent, intermolecular interaction which has been harnessed for a variety of applications, including sensor design. A halogen bond (XB) is formed between a region of positive electrostatic potential on a halogen atom (X) and electron rich portions of target molecules. The strength of XB interactions relies on shorter XB bond distances and more linear R–X···B bond angles, which facilitate stronger, more negative binding energies. While prior studies have sought to maximize interactions, few have explored or experimentally demonstrated how geometries and bond angles can enhance XB interactions. Herein, fundamental studies are conducted at self-assembled …

Bridging The Gap: A Systematic Review Of Cyber Conflict Forecasting Models And The Case For Ai-Driven Dynamic Frameworks, Salim Arfaoui, Youssef Harrath, Omar El-Gayar

Research & Publications

Cyber conflict forecasting remains constrained by static models that overlook the integration of geopolitical context with technical indicators. This systematic literature review examines 58 studies (2010–2025) using PRISMA guidelines and an InputProcess-Output framework to classify approaches and identify key gaps. Quantitative methods dominate (67%), yet only 14% incorporate geopolitical variables, despite the political nature of cyber conflict. Major limitations include adversarial adaptation blindness (85% assume static behavior), coarse temporal granularity (72% use daily+ intervals), lack of uncertainty quantification (75%), and minimal modeling of cross-domain escalation (92% cyber-only focus). Strategic forecasting is rare, with just 14% providing long-term insights and 16% …

Big Tech As Transnational Spyware Regulator, Natalie R. Davidson

Fordham Intellectual Property, Media and Entertainment Law Journal

Spyware has emerged as a potent tool for leaders to shrink dem- ocratic contestation. In response to calls for constraints on the trade in spyware, states have updated the principal multilateral agree- ment on export controls, civil society groups have employed strate- gic litigation, and the European Union has altered its regulation, in each case with the aim of limiting exports where there is a risk of human rights violations. Yet, scandals involving the Israeli company NSO, among others, have made clear that even the updated regula- tory landscape is inadequate. Many actors are currently debating the reasons for existing …

Ransomware As Organization: A Comparative Analysis Of Corporate And Criminal Structures In Conti, George Urling

Theses, Dissertations and Capstones

Cybercriminal groups continue to pose major threats to global cybersecurity. One of the most common types of cybercriminal groups are, “Ransomware-as-a-Service (RaaS)" groups, who create and sell ransomware. While research is conducted into the development of ransomware, there is limited reporting on the organizational structure and habits of RaaS groups. In 2022, prominent RaaS group Conti had their chat logs leaked, with the logs ranging from 2020 to 2022. This study seeks to provide a deeper understanding of RaaS group structures by utilizing the Conti leaked logs as a case study. The study, entitled “Ransomware as Organization: A Comparative Analysis …

Rf-Attennet: A Hybrid Attention-Enhanced Network For Mixed Signal Classification In Uav Swarm Detection, Prajoy Podder, Mohammad Atikur Rahman, Maciej Zawodniok, Sanjay Madria

Electrical and Computer Engineering Faculty Research & Creative Works

The continuous increase of UAVs, particularly in swarms, creates significant challenges for security and airspace regulation. Traditional RF fingerprinting methods struggle to detect and classify UAV swarms due to overlapping signals and interference. This study introduces RF-AttenNet, a hybrid deep learning model designed to classify mixed UAV signals by analyzing composite RF spectrograms. RF-AttenNet uses dual attention mechanisms, channel and spatial attention to focus on critical spectral features, enabling the model to effectively separate and identify overlapping UAV signals. We have developed custom composite UAV datasets that simulate real-world swarm interference, incorporating both single and mixed UAV classes. RF-AttenNet achieves …

Law Librarianship And Legal Information Science In The Age Of Genai, Paul D. Callister

Faculty Works

This article examines the relationship between law librarianship and legal information science in the age of generative AI (GenAI), arguing that closer integration between the two is essential to navigating a rapidly evolving legal information landscape. It contends that law librarianship—long grounded in stable classification systems and cognitive authority—must adopt the analytical methods of legal information science to remain effective in the digital era. Together, these fields can reinforce the rule of law by improving the organization, retrieval, and stability of legal information. The article identifies emerging subfields of legal information science that support this integration and develops several concepts …

Artificial Intelligence, Fundamental Motives, And Evolutionary Mismatch, Amy J. Lim, Jose. C. Yong, Edison Sora Tan

Research Collection School of Social Sciences

In recent years, the intersection of artificial intelligence (AI) and psychology has garnered unprecedented attention, particularly following the advent of generative AI tools in 2022. These tools, capable of producing human-like text, images, and even deepening our understanding of cognitive processes, have not only captured the public imagination but also sparked new concerns and debates within the psychological community. While AI has been a subject of research for decades, the emergence of its generative capabilities has truly thrust AI into the spotlight. This article explores how these advancements are reshaping our understanding of human cognition and behavior, as well as …

Application Of Paper Spray Mass Spectrometry For Screening Acetylcholinesterase Inhibitors, Diksha Gautam

Graduate Research Theses & Dissertations

Paper spray mass spectrometry (PS-MS) is a novel ambient ionization method that allows chemical and biological samples to be rapidly analyzed with little preparation being required. In this paper, PS-MS was set up and streamlined as an acetylcholinesterase (AChE)-monitoring platform in addition to screening an existing and newly produced AChE-inhibitors. The detection of the substrate, acetylcholine (m/z 146), and the AChE catalysis product, choline (m/z 104) was performed without applying chromatographic separation or derivatization to the dried paper substrates. Assay conditions were optimized in a systematic way, to develop a robust MS-compatible enzymatic workflow.

Calibration curves for both, acetylcholine and …

Biosecure-Llm Framework: Protecting Llms From Cyberbiosecurity Threats And The Case For Independent Ai Safety Governance, Xavier-Lewis Palmer, Lucas Potter, Srdjan Lesaja, Sotirios Karathanasis, Mohammad Ghasemigol

Computer Science Faculty Publications

Large Language Models (LLMs) are becoming critical infrastructure in scientific, healthcare, and governmental contexts. As frontier AI laboratories increasingly partner with government agencies, a fundamental question arises: Who should control the safety and policy-enforcement layers that constrain model behavior? Current safety mechanisms (LLM guardrails) are typically designed for generic "harmlessness" and operate by detecting semantic patterns and refusing requests. However, they are inadequate governance instruments because they cannot implement auditable, domain-specific controls tied to external regulatory policy objects (e.g., control lists or rules governing personally identifying information). Even a perfectly aligned model is not able to express institution-specific policy without …

When Helpfulness Becomes Harmful: Jailbreaking Llms For Malicious Code Generation, Noelle Capodieci

Electronic Theses & Dissertations (2024 - present)

Generative AI (GenAI) and Large Language Models (LLMs) have made large strides in coding task capabilities, with many software developers integrating agentic engineering into their workflow. While GenAI has largely benefited professional software engineers who can automate their work, it has also created room for those with little coding expertise to also create fully fledged programs and applications. It is commonly noted that GenAI is trained with two major goals in mind: to be as helpful as possible, and be as harmless as possible. There exist moments where helpfulness may be prioritized over harmlessness when these goals conflict. LLMs may …

A Knowledge-Driven, Ai-Assisted Cyber Defence Framework For Iomt Remote Patient Monitoring, Kulsoom S. Bughio, David M. Cook, Abdul M. Unar

Research outputs 2022 to 2026

The rapid adoption of Internet Medical Things (IoMT) technologies in remote patient monitoring has reshaped healthcare delivery by enabling continuous, real-time clinical observation outside traditional care settings. However, this shift has also expanded the cyber-attack surface across heterogeneous, resource-constrained medical devices, wireless networks, cloud services, and third-party platforms. In cyber warfare, healthcare has become an incorporated target of geopolitics, with hospitals, remote monitoring systems, and emergency health systems being used to broaden the attack surface for adversaries to exploit. Existing security approaches for IoMT environments remain largely manual, fragmented, and reactive, limiting their effectiveness in dynamically assessing vulnerabilities and supporting …

Full Issue, The Mcnair Team

McNair Scholars Research Journal

No abstract provided.

Free Radical Reactions Of Electron Rich Alkenes, David A. May Jr

Graduate Theses and Dissertations

Radical reactions have known for over a century but have only been thought of as useful synthetic strategies for the last 70 years. During this period, much work has been done to develop theoretical explanations for their reactivity and modes of termination, resulting in them becoming a fundamental type of organic reaction in academia and industry. Previous studies by the McIntosh group have shown that a radical [1,3]-Rearrangement occurs when N-substituted pyridines are heated. Here, the scope of this new reaction is expanded to include polycyclic pyridines including neocuproine (2,9-dimethylphenanthroline) and 2-methylquinoline while also expanding the range of reactions available …

Experts’ Validation Of The Fundamental Cybersecurity Competency Index (Fcci) Using A Commercial Cyber Range Through Human-Generative Artificial Intelligence (Genai) Teaming, Dariusz Witko, Yair Levy, Catherine Neubauer, Greg Simco, Laurie P. Dringus, Melissa Carlton

Journal of Cybersecurity Education, Research and Practice

The increasing volume of cyber threats, combined with a critical shortage of skilled professionals and rising burnout among practitioners, highlights the urgent need for innovative solutions in cybersecurity operations. Generative Artificial Intelligence (GenAI) offers promising potential to augment human analysts in cybersecurity, but its integration requires rigorous validation of the fundamental competencies that enable effective collaboration of human-GenAI teams. This research study employed a mixed-methods research project designed to evaluate human-GenAI teams, emphasizing the role of expert consensus in shaping the experimental assessment of the Fundamental Cybersecurity Competency Index (FCCI) in a commercial cyber range. We engaged 20 Subject Matter …

Systematic Review Of Elementary Cybersecurity Education: Curriculum, Pedagogy, And Barriers, Na Liu, Siyu Long, Florence Martin

Journal of Cybersecurity Education, Research and Practice

Abstract -As children increasingly engage with digital platforms, the need for effective cybersecurity education has become urgent. This systematic review synthesizes 81 studies published between 2017 and 2024 to examine global curricula research focus and topics, pedagogical approaches and assessment methods, and key challenges in elementary cybersecurity education. The findings reveal six major thematic categories: student awareness, parental mediation, teacher engagement, curriculum design, community and policy support, and pedagogical innovation. Among instructional strategies, game-based learning and narrative storytelling emerge as the most frequently explored. Despite this growth, major gaps remain in curriculum consistency, teacher preparation, assessment rigor, and stakeholder coordination. …