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Articles 1 - 30 of 36
Full-Text Articles in Systems Science
Breaking The Build: Detecting Software Supply Chain Vulnerabilities In Ci/Cd Pipelines, Mercedes R. Wahl, Dr. Benjamin Yankson
Breaking The Build: Detecting Software Supply Chain Vulnerabilities In Ci/Cd Pipelines, Mercedes R. Wahl, Dr. Benjamin Yankson
Military Cyber Affairs
This study examines whether integrating structured DevSec- Ops security controls into CI/CD pipelines can reduce software supply chain risk by preventing vulnerable components from progressing through the software development lifecycle. Software supply chain attacks frequently originate from weaknesses or compromises within dependencies, build environments, and trusted development stages, making early detection essential. A controlled sandbox experiment compared two pipeline configurations: a baseline CI/CD pipeline with no automated security enforcement and a secure DevSecOps pipeline integrating automated vulnerability scanning, SBOM generation, and artifact integrity verification. A known vulnerable dependency, the Python requests package (version 2.19.0) associated with CVE-2018-18074, was intentionally introduced …
Hybrid Deep (Cnn-Bilstm) Intrusion Detection For Defense And Mission-Critical Networks, Corey A Cheng, Jermaine Anim-Addo, Asma Jakir Hussain, Zion O Smith-Fox, Sanjay Goel, Yuksel Celik
Hybrid Deep (Cnn-Bilstm) Intrusion Detection For Defense And Mission-Critical Networks, Corey A Cheng, Jermaine Anim-Addo, Asma Jakir Hussain, Zion O Smith-Fox, Sanjay Goel, Yuksel Celik
Military Cyber Affairs
This article examines how hybrid deep learning can strengthen intrusion detection for military and defense networks. Using the CSE-CIC-IDS2018 dataset, the study evaluates a CNN-BiLSTM model designed to detect benign traffic and multiple attack categories, including DDoS, DoS, botnet, brute-force, web attack, and infiltration activity. The model achieved strong multi-class detection performance, with 0.9893 accuracy and 0.9979 ROC-AUC. The findings suggest that AI-supported intrusion detection can improve cyber defense operations, analyst triage, and protection of mission-critical networks.
Foreward, Todd Arnold
Letter From The Director: Mastery In Practice, Joseph Schafer
Letter From The Director: Mastery In Practice, Joseph Schafer
Military Cyber Affairs
No abstract provided.
Balancing Innovation And Integrity: Ethical Implications Of Ai Use In Higher Education, Petronella Muziti, Ntando S. Sibanda
Balancing Innovation And Integrity: Ethical Implications Of Ai Use In Higher Education, Petronella Muziti, Ntando S. Sibanda
African Conference on Information Systems and Technology
Artificial intelligence (AI) is rapidly transforming higher education, creating opportunities while raising ethical concerns such as bias, privacy violations, academic misconduct and reduced human-centred teaching. This study examined how institutions can balance AI innovation with academic integrity and equity, focusing on lecturers’ ethical dilemmas and institutional readiness. A triangulation design incorporating quantitative and qualitative methods was used. Twelve semi-structured interviews and two focus group discussions involving eighteen participants were conducted across five universities, while 150 questionnaires were distributed, yielding 128 valid responses. Descriptive statistics and thematic analysis were applied. Findings showed that lecturers reported student misuse and plagiarism (78%), AI …
Physics-Guided Deep Learning For Predictive Modeling Of Spatiotemporal Dynamical Systems, Niharika Deshpande
Physics-Guided Deep Learning For Predictive Modeling Of Spatiotemporal Dynamical Systems, Niharika Deshpande
Engineering Management & Systems Engineering Theses & Dissertations
Many physical and networked systems evolve under continuously changing spatial and temporal conditions. Transportation networks respond to fluctuating demand, atmospheric fields reorganize as storms intensify, and coastal response depends on localized forcing pathways. Modeling such systems requires learning formulations that adapt to evolving structure, operate on irregular geometries, and provide interpretable measures of predictive uncertainty. This dissertation develops a physics-guided spatiotemporal learning framework designed for structured dynamical systems whose governing interactions are neither static nor Euclidean. The central premise is that spatial relationships in these systems are dynamic and geometry-dependent. To represent this behavior, system states are modeled on time-varying …
Improving Urban Search And Rescue Team Coordination Through Adaptive Context Awareness, Daniel Reyes Duran
Improving Urban Search And Rescue Team Coordination Through Adaptive Context Awareness, Daniel Reyes Duran
Doctoral Dissertations and Master's Theses
Modern multi-agent Urban Search and Rescue (USAR) operations heavily rely on mobile geospatial Common Operating Pictures (COPs) to maintain team coordination and Situational Awareness (SA). However, the proliferation of high-frequency sensor telemetry at the tactical edge has introduced a data saturation paradox challenge: while information theoretically drives informed decision-making, unmanaged data surges induce increased operator cognitive overload and alert fatigue on mobile End-User Devices (EUDs), while downstream data-broadcasting models inherently strain edge processing and viewport environments.
To resolve these constraints, this dissertation presents a context-aware Value of Information (VoI) data-management framework integrated directly with a custom, event-driven Android Team Awareness …
Ai-Scm Cmm: A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines, Omar F. El-Gayar, Patti Brooks, Insu Park
Ai-Scm Cmm: A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines, Omar F. El-Gayar, Patti Brooks, Insu Park
Annual Research Symposium
Artificial intelligence is increasingly deployed in supply chain management, yet many organizations struggle to align adoption efforts with process readiness, data quality, governance, and workforce capabilities, and they still lack validated supply chain specific roadmap for assessing readiness, sequencing investments, and reducing implementation risk. This study develops and evaluates a Capability Maturity Model for Artificial Intelligence Integration in Supply Chain Management to address that gap. Using a design science research approach, the study synthesizes prior literature and practitioner knowledge to define maturity dimensions, capability indicators, and staged progression levels for AI integration in supply chain contexts. The artifact and assessment …
A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines
A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines
Dissertations
Artificial Intelligence (AI) is transforming Supply Chain Management (SCM), yet many organizations struggle to assess their readiness for AI adoption and to understand how AI capabilities develop across maturity stages. This dissertation addresses this gap by developing a Capability Maturity Model (CMM) for AI integration in SCM, grounded in Organizational Information Processing Theory (OIPT), the Resource-Based View, and related capability frameworks. The model provides a structured approach for evaluating an organization's information-processing requirements, resource configurations, and alignment needed for effective AI-enabled supply chain operations.
Using a design science research approach, the AI-SCM CMM and its associated assessment instrument were derived …
A Transition Framework For Hybrid Tls In Enterprise-Level Systems, William Hadd
A Transition Framework For Hybrid Tls In Enterprise-Level Systems, William Hadd
Cybersecurity Undergraduate Research Showcase
Enterprises face an immediate need to protect long-lived data against harvest-now, decrypt-later threats while maintaining interoperability across layered systems. With NIST’s first post-quantum standards finalized (ML-KEM, ML-DSA, SLH-DSA) and TLS hybridization drafts defining concrete ECDHE + ML-KEM groups, adoption can begin at the TLS termination layer even before full ecosystem support for post-quantum signatures arrives (NIST, 2024; IETF, 2025). In this paper, we propose an enterprise-oriented transition framework and maturity model for hybrid TLS across email, internal API gateways, and object storage. We specify where to enforce, which hybrid groups to select, and how to prevent silent downgrade with policy …
Director, Military Cyber Institute, Joseph Schafer
Director, Military Cyber Institute, Joseph Schafer
Military Cyber Affairs
No abstract provided.
Throughput Of Ascon Compared With Popular Iot Encryption Algorithms, Mitchel R. Harvey (Ryan), Andrew M. Kaiser, Garrett W. Hoiness
Throughput Of Ascon Compared With Popular Iot Encryption Algorithms, Mitchel R. Harvey (Ryan), Andrew M. Kaiser, Garrett W. Hoiness
Military Cyber Affairs
No abstract provided.
Anomaly Detection Of Network Layer Attacks Against Cyber Physical Systems Using Machine Learning And Deep Learning Techniques, James Alger, Michael Tu
Anomaly Detection Of Network Layer Attacks Against Cyber Physical Systems Using Machine Learning And Deep Learning Techniques, James Alger, Michael Tu
Military Cyber Affairs
This research paper presents the analysis of using machine learning and deep learning algorithms on detecting anomalous network traffic in Cyber-Physical Systems (CPS). Using a real PLC CPS-based system, normal and anomalous network traffic will be captured using Wireshark. The research analyzes a DDoS attack. The focus of the research is to identify the most effective feature combinations and evaluate them on ML and DL models. The emphasis is on enhancing detection strategies rather than exploiting device vulnerabilities. The detection of network attacks often involves handling a vast array of high-level features. Previous studies (Li & Chasaki, 2022) apply machine …
Characterizing Caldera’S Cyber Attack Emulation Capabilities, Caleb Chang, Matthew Cao, Kenyou Teoh, Ekzhin Ear, Shouhuai Xu
Characterizing Caldera’S Cyber Attack Emulation Capabilities, Caleb Chang, Matthew Cao, Kenyou Teoh, Ekzhin Ear, Shouhuai Xu
Military Cyber Affairs
Autonomous cyber attack emulation can aid cyber defenders to identify and remediate cyber risks. MITRE’s Caldera software is the state-of-the-practice for automated attack emulation. Yet, it has not been systematically analyzed, putting its performance and effectiveness into question. This paper systematically characterizes Caldera’s architecture, abilities and use cases, and assesses its strengths and weaknesses. It draws useful insights, such as: Caldera excels in stealthy access and execution tactics to pilfer data against Windows operating systems. It also discusses two directions for Caldera improvement: module-level automation and end-to-end attack emulation.
The Digital Battlefield: Safeguarding Military Drones Against Cyberattacks, Jason Ashong, Arun Venkitanarayanan, Benjamin Yankson
The Digital Battlefield: Safeguarding Military Drones Against Cyberattacks, Jason Ashong, Arun Venkitanarayanan, Benjamin Yankson
Military Cyber Affairs
The Internet of Battlefield Things (IoBT) is an advanced network of interconnected devices that significantly enhance military operations through real-time data exchange and situational awareness. While IoBT offers tactical advantages like improved surveillance, reconnaissance, and operational effectiveness, it also introduces substantial cybersecurity risks. Adversaries can exploit vulnerabilities within these networks, potentially compromising mission integrity and national security. This research examines the cybersecurity measures of commercial drone controllers and their correlation with military devices. It aims to enhance future vulnerability assessments with advanced tools and approaches to better secure critical military operations. The study highlights the need for robust security architectures …
Using Blockchain Technology To Help Secure America's Defense Critical Infrastructure, Vimal Buck, Aerin Krebs, Brynn Hillard, Jakob Gerha, Joseph Lutma, Srikar Maduposu, Ted Allen
Using Blockchain Technology To Help Secure America's Defense Critical Infrastructure, Vimal Buck, Aerin Krebs, Brynn Hillard, Jakob Gerha, Joseph Lutma, Srikar Maduposu, Ted Allen
Military Cyber Affairs
Critical water infrastructure in the United States faces increasing cybersecurity threats from state-sponsored actors, with potentially devastating consequences for national security, economic stability, and public health. (Cybersecurity and Infrastructure Security Agency, 2025). This infrastructure supports defense critical assets and is actively being targeted by various state-sponsored hacking groups, which poses a major concern for civilians and military alike. K. Herath (personal communication, February 24, 2025) reported being aware of two attacks on Ohio water systems during his tenure as Cybersecurity Strategic Advisor to Ohio Governor Mike DeWine.
Water is essential to everyday life and defense and presents as a high-value …
Network And Multipath Traceroute Visualization, Cameron Makowski
Network And Multipath Traceroute Visualization, Cameron Makowski
Military Cyber Affairs
TraceCam introduces a new paradigm in network path analysis, leveraging GPU-accelerated WebGL visualization, advanced traceroute integrations, and AI-driven insights to transform complex routing data into actionable intelligence. Early prototypes have demonstrated significant improvements in performance, clarity, and multi-path discovery, overcoming traditional limitations in traceroute analysis. By incorporating retrieval-augmented language models and enriched metadata sources like IPinfo.io, TraceCam enables automated anomaly detection, contextual explanations, and rapid root-cause analysis, enhancing operational efficiency. The platform’s architecture ensures scalability and adaptability, supporting deeper investigations and real-time situational awareness. Future development will focus on clustering-based anomaly detection, expanded geographic visualizations, and enhanced AI-generated analysis to …
Quantifying Adversary Military Forces’ Susceptibility To Cognitive Attacks, Bonnie Rushing, Cole Nelson, Shouhuai Xu, Christofer “Raven” O’Keefe, Olga Karpoyan
Quantifying Adversary Military Forces’ Susceptibility To Cognitive Attacks, Bonnie Rushing, Cole Nelson, Shouhuai Xu, Christofer “Raven” O’Keefe, Olga Karpoyan
Military Cyber Affairs
This paper introduces a method to quantify international populations’ susceptibility to cyber cognitive attacks using press freedom and media trust metrics. We present the Cognitive Influence Calculator, a tool that estimates susceptibility (𝑆) based on Press Freedom Scores (PFS) and media trust levels. Findings show that while authoritarian regimes are harder to reach, successful cognitive attacks have greater impacts due to higher trust in state-controlled narratives. Using U.S. wargaming data and international trust metrics, we compute susceptibility scores for the U.S., Russia, China, Iran, and North Korea. Results show an inverse relationship between PFS and media susceptibility, with local/allied …
Forward, Amy Hamilton
Understanding Russia’S Cyber Policies, Strategies, And Doctrines, Bryan Hancock, Hanh Nguyen, Olga Karpoyan, Ekzhin Ear, Shouhuai Xu
Understanding Russia’S Cyber Policies, Strategies, And Doctrines, Bryan Hancock, Hanh Nguyen, Olga Karpoyan, Ekzhin Ear, Shouhuai Xu
Military Cyber Affairs
This study analyzes the strengths and weaknesses of Russia’s cyber policies, strategies, and doctrines through a systematic set of attributes, leading to key insights: (i) Russia has proactively adapted its cyber policies, strategies, and doctrines to its evolving environment; (ii) Russia actively conducts cognitive warfare, but remains equally vulnerable to it; and (iii) Russia’s cyber posture faces significant challenges, including a limited technological base, shortage of skilled personnel, and restrictive approach to information control, all of which undermine the effectiveness of its strategies. These insights offer valuable implications for US Cyber Command and the Department of Defense.
Characterizing Cyberattacks Against Operational Technology Infrastructures Through The Lens Of Attack Flows, Sherman Kettner, Caleb Chang, Ekzhin Ear, Shouhuai Xu
Characterizing Cyberattacks Against Operational Technology Infrastructures Through The Lens Of Attack Flows, Sherman Kettner, Caleb Chang, Ekzhin Ear, Shouhuai Xu
Military Cyber Affairs
Operational Technology (OT) infrastructures play a critical role in modern society and economy. However, their increasing connectivity with public networks such as the Internet has made them vulnerable to cyberattacks, much like traditional Information Technology (IT) systems. In particular, cyberattacks against OT infrastructures remain relatively underexplored and little understood. In this paper, we aim to deepen our understanding of cyberattacks against OT infrastructures. For this purpose, we propose a methodology, including novel cybersecurity metrics to analyze the attack flows of these attacks in an end-to-end fashion, which allows us to draw useful insights. We demonstrate the utility of the methodology …
Detecting Wireless Security Threats Through Ieee 802.11 Frame Field Anomalies, Aria Young
Detecting Wireless Security Threats Through Ieee 802.11 Frame Field Anomalies, Aria Young
Williams Honors College, Honors Research Projects
It is not uncommon for most public spaces to offer Wi-Fi, while it is convenient and affordable, there are significant security risks due to its open nature. Rogue access points pose a security threat to many networks because they have the potential to bypass security measures and intercept traffic containing sensitive information. The attempt to formulate a method that one hundred percent guarantees the detection of a rogue access point has proven to be an intricate and complex problem for many to tackle, as there are numerous ways a rogue access point can be configured. This project aims to demonstrate …
Faids: Artificial Intelligence Developmental Systems Framework For Predicting And Preventing Cyberattacks In Supply Chain Networks, Lordt Becklines
Faids: Artificial Intelligence Developmental Systems Framework For Predicting And Preventing Cyberattacks In Supply Chain Networks, Lordt Becklines
Research & Publications
Cyber threats and attacks disrupt and damages supply chain networks (SCNs), which are complex and interlinked. Current methods to predict and prevent cyberattacks are inadequate and ineffective. This research proposes an AI developmental systems framework (FAIDS) to protect SCNs from cyberattacks. The framework has four components: (1) an AI threat intelligence system; (2) an AI risk assessment system; (3) an AI decision support system; and (4) an AI learning and adaptation system. The framework is tested on a simulated retail SCN. The results show that the framework can predict and prevent cyberattacks and improve the network's resilience and security. The …
Improving Ethics Surrounding Collegiate-Level Hacking Education: Recommended Implementation Plan & Affiliation With Peer-Led Initiatives, Shannon Morgan, Dr. Sanjay Goel
Improving Ethics Surrounding Collegiate-Level Hacking Education: Recommended Implementation Plan & Affiliation With Peer-Led Initiatives, Shannon Morgan, Dr. Sanjay Goel
Military Cyber Affairs
Cybersecurity has become a pertinent concern, as novel technological innovations create opportunities for threat actors to exfiltrate sensitive data. To meet the demand for professionals in the workforce, universities have ramped up their academic offerings to provide a broad range of cyber-related programs (e.g., cybersecurity, informatics, information technology, digital forensics, computer science, & engineering). As the tactics, techniques, and procedures (TTPs) of hackers evolve, the knowledge and skillset required to be an effective cybersecurity professional have escalated accordingly. Therefore, it is critical to train cyber students both technically and theoretically to actively combat cyber criminals and protect the confidentiality, integrity, …
Using Digital Twins To Protect Biomanufacturing From Cyberattacks, Brenden Fraser-Hevlin, Alec W. Schuler, B. Arda Gozen, Bernard J. Van Wie
Using Digital Twins To Protect Biomanufacturing From Cyberattacks, Brenden Fraser-Hevlin, Alec W. Schuler, B. Arda Gozen, Bernard J. Van Wie
Military Cyber Affairs
Understanding of the intersection of cyber vulnerabilities and bioprocess regulation is critical with the rise of artificial intelligence and machine learning in manufacturing. We detail a case study in which we model cyberattacks on network-mediated signals from a novel bioreactor, where it is important to control medium feed rates to maintain cell proliferation. We use a digital twin counterpart reactor to compare glucose and oxygen sensor signals from the bioreactor to predictions from a kinetic growth model, allowing discernment of faulty sensors from hacked signals. Our results demonstrate a successful biomanufacturing cyberattack detection system based on fundamental process control principles.
Characterizing Advanced Persistent Threats Through The Lens Of Cyber Attack Flows, Logan Zeien, Caleb Chang, Ltc Ekzhin Ear, Dr. Shouhuai Xu
Characterizing Advanced Persistent Threats Through The Lens Of Cyber Attack Flows, Logan Zeien, Caleb Chang, Ltc Ekzhin Ear, Dr. Shouhuai Xu
Military Cyber Affairs
Effective cyber defense must build upon a deep understanding of real-world cyberattacks to guide the design and deployment of appropriate defensive measures against current and future attacks. In this abridged paper (of which the full paper is available online), we present important concepts for understanding Advanced Persistent Threats (APTs), our methodology to characterize APTs through the lens of attack flows, and a detailed case study of APT28 that demonstrates our method’s viability to draw useful insights. This paper makes three technical contributions. First, we propose a novel method of constructing attack flows to describe APTs. This abstraction allows technical audiences, …
Machine Learning Security For Tactical Operations, Dr. Denaria Fields, Shakiya A. Friend, Andrew Hermansen, Dr. Tugba Erpek, Dr. Yalin E. Sagduyu
Machine Learning Security For Tactical Operations, Dr. Denaria Fields, Shakiya A. Friend, Andrew Hermansen, Dr. Tugba Erpek, Dr. Yalin E. Sagduyu
Military Cyber Affairs
Deep learning finds rich applications in the tactical domain by learning from diverse data sources and performing difficult tasks to support mission-critical applications. However, deep learning models are susceptible to various attacks and exploits. In this paper, we first discuss application areas of deep learning in the tactical domain. Next, we present adversarial machine learning as an emerging attack vector and discuss the impact of adversarial attacks on the deep learning performance. Finally, we discuss potential defense methods that can be applied against these attacks.
Securing The Void: Assessing The Dynamic Threat Landscape Of Space, Brianna Bace, Dr. Unal Tatar
Securing The Void: Assessing The Dynamic Threat Landscape Of Space, Brianna Bace, Dr. Unal Tatar
Military Cyber Affairs
Outer space is a strategic and multifaceted domain that is a crossroads for political, military, and economic interests. From a defense perspective, the U.S. military and intelligence community rely heavily on satellite networks to meet national security objectives and execute military operations and intelligence gathering. This paper examines the evolving threat landscape of the space sector, encompassing natural and man-made perils, emphasizing the rise of cyber threats and the complexity introduced by dual-use technology and commercialization. It also explores the implications for security and resilience, advocating for collaborative efforts among international organizations, governments, and industry to safeguard the space sector.
Cybersecurity Awareness And Risks Among Students, Staff & Faculty At The University Of North Alabama, Jerry Lwamba
Cybersecurity Awareness And Risks Among Students, Staff & Faculty At The University Of North Alabama, Jerry Lwamba
Theses
As individuals and organizations become significantly connected to the internet, cybercriminals find an increasing number of ways to exploit their targets (Broadhurst, 2018). This study explores the world of cybersecurity awareness of risks associated with online activities within the University of North Alabama (UNA). This research aims to assess the level of cybersecurity awareness of risks university stakeholders face, and to also understand behaviors that expose them to cybercrime and emphasize the urge for comprehensive cybersecurity best practices. When cybercriminals employ tactics such as spam, phishing, or spear phishing in their attempts to break into network systems, distribute malware, or …
Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia
Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia
Journal of Nonprofit Innovation
Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.
Imagine Doris, who is …