Digital Communications and Networking Commons^™

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

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

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

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

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

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

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

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

Military Cyber Affairs

No abstract provided.

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

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 …

Context-Switch Attacks: Understanding And Mitigating The Threat To Llm Applications, Sydney Holder, Bivin Sadler

SMU Data Science Review

Large Language Models (LLMs) are transforming conversational AI, yet their dependence on prompt-supplied context exposes them to context-switch attacks that covertly steer dialogue toward sensitive or malicious ends. A 70 one-sided conversation transcript evaluation set was constructed spanning various fraudulent scenarios. Each transcript embeds adversarial patterns drawn while preserving natural conversational flow. We introduce a hybrid defense that pairs a BERT-based semantic-drift detector (cosine-similarity threshold = 0.70) with a curated keyword and hack-phrase scanner to counter these threats. In aggregate, the system delivered 100 % recall, intercepting every simulated phishing or data-harvesting attempt. The keyword layer achieved perfect precision, generating …

How’S It Growing? Tools For Observing Snow And Sea Ice In A Changing Arctic Ocean, Ian Alexander Raphael

Dartmouth College Ph.D Dissertations

September Arctic sea ice extent has diminished by roughly 50% in the 45 years since satellite observations began. The Arctic Ocean may experience ice-free summers within the next decade, with implications for habitat, resource extraction, geopolitics, and local and global climate change. To predict how Arctic sea ice will change in the future, we need to understand its behavior in the present. In situ sea ice mass balance measurements (snow accumulation, ice growth, snow and ice surface melt, and bottom melt) are essential for studying the processes driving rapid changes in the ice pack, and for validating remote sensing measurements …

A Machine Learning-Driven Framework For Real Time Detection And Prevention Of Replica Node Attacks In Wireless Sensor Networks, Maram Pavani, Tanguturi Sharani, Amutha Jeevakumari S A

Northeast Journal of Complex Systems (NEJCS)

Mobile devices and wireless sensor networks (WSNs) are increasingly vulnerable to security threats such as unauthorized access and replica node attacks. Mobile devices face risks from replication and anomalous behavior, while attackers compromise WSNs by cloning legitimate nodes, thus threatening network integrity. Traditional security mechanisms often fall short in detecting such sophisticated threats, especially in resource-constrained environments. This research proposes a dual-component security system. A Machine Learning-Based Intrusion Detection System (IDS) for WSNs leverages Graph Neural Networks (GNNs) to detect replica nodes through structural network analysis and applies Federated Learning to preserve data privacy. The Sequential Probability Ratio Test (SPRT) …

Spy Bot, Nathanael Bruce Farris

Computer Engineering

This project set out to develop a compact, mobile-controlled robotic platform designed for remote video surveillance and control via a smartphone. Using a Raspberry Pi as the core controller, the robot integrates a Flask-based server, HTML/JavaScript-based user interface, and an infrared-capable camera to provide real-time video streaming and directional control through a web browser. Key design challenges included managing power delivery, integrating motor control with live video, and modernizing web technologies to ensure smooth communication between client and server. The final system demonstrates a responsive and portable proof of concept that highlights the potential for future upgrades, such as night …

Sla Evaluation And Composition In Reconfigurable Cloud-Based Services, Michael Iannelli

Dissertations, Theses, and Capstone Projects

Given the business model of offering data and computing services in a cloud setting, a major question arises: How do the services of one cloud provider compare to those of others? With the ubiquitous use of smartphones and tablets, the ability of a cloud provider to support QoS and client mobility becomes paramount. This research proposes a methodology for evaluating service-level agreements (SLAs) between cloud providers and their consumers, with a particular focus on dynamic SLA composition to adapt to changes in the application requirements and the external environment—such as traffic surges, security threats, or evolving business models.

In one …

Selected Artificial Intelligence Provisions In U.S. Fiscal Year 2025 National Defense Authorization Act, Bert Chapman

Libraries Faculty and Staff Presentations

The 2025 Fiscal Year National Defense Authorization Act contains multiple provisions relating to artificial intelligence (AI). These congressionally mandated provisions direct various sections of the Department of Defense (DOD) and individual U.S. armed service branches to execute congressional intent for AI policymaking. Examples of such intent include identifying and planning DOD's AI workforce, demonstrating AI biotechnology applications for national security, improving the human usability of AI systems, and establishing an AI security center. This presentation will note that reports on these initiatives must be prepared for relevant congressional oversight committees, and, in many cases, are in many cases, publicly released …

A Data-Driven Approach To Smart Shopping: Optimizing Grocery Trips Using Geolocation And Store Inventory Data, Kien T. Giang

Honors Theses

This project presents a data-driven web-based application, Smart Shopping, designed to help customers optimize their grocery purchases based on location and store inventory information. The application allows users to add items to a shopping list and either enter an address or use their browser’s location services to identify nearby stores. It then retrieves product availability and prices from a mock database representing stores at user’s selected locations. The program compares prices across stores to provide users with two optimized options: the cheapest shopping bill from a single store, and the lowest individual item prices across multiple stores. Additionally, the …

Frontlines Of Influence: State Vs. Nonstate Disinformation Campaigns, Lily Wershbale

Cybersecurity Undergraduate Research Showcase

This paper examines the evolution of disinformation campaigns conducted by state and nonstate actors, focusing specifically on Russia and the Islamic State as representative case studies. Through historical examples and qualitative comparative analysis, this research identifies the similarities and differences in disinformation’s role in actors’ core missions, resource allocation, and targeting decisions. This paper further explores the implications of artificial intelligence on disinformation campaigns, investigating how emerging technology will impact the influence operations of state governments and nonstate organizations alike. The findings reveal that while the ultimate intent of both state and non-state actors is to destabilize societies, their approaches …

Algorithms & Design Behind Autonomous Uavs And Ugvs Coordinated System, Aashish Dhakal

Honors Theses

Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs), when coordinated effectively, offer substantial potential for automating large-scale tasks—from search and rescue operations to precision agriculture. However, synchronizing these autonomous systems remains challenging, especially in time-sensitive missions requiring precision. This thesis investigates the design and algorithmic coordination of autonomous UAVs and UGVs, examining both single-vehicle scenarios and multi-agent (swarming) approaches. Using the Robot Operating System (ROS) as a communication backbone, I integrate GPS positioning with computer vision techniques through OpenCV, enabling accurate localization and object detection. During the development phase, I validate my methods using ArduPilot Software-in-the-Loop (SITL) simulations within …