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Characterizing Advanced Persistent Threats Through The Lens Of Cyber Attack Flows, Logan Zeien, Caleb Chang, LTC Ekzhin Ear, Dr. Shouhuai Xu 2024 University of Colorado, Colorado Springs (UCCS)

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 2024 Virginia Tech

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 2024 University at Albany

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.


Commercial Enablers Of China’S Cyber-Intelligence And Information Operations, Ethan Mansour, Victor Mukora 2024 Virginia Tech

Commercial Enablers Of China’S Cyber-Intelligence And Information Operations, Ethan Mansour, Victor Mukora

Military Cyber Affairs

In a globally commercialized information environment, China uses evolving commercial enabler networks to position and project its goals. They do this through cyber, intelligence, and information operations. This paper breaks down the types of commercial enablers and how they are used operationally. It will also address the CCP's strategy to gather and influence foreign and domestic populations throughout cyberspace. Finally, we conclude with recommendations for mitigating the influence of PRC commercial enablers.


Rgb Root Matriz Color Dance, Danielle E. Gauthier 2024 CUNY Hunter College

Rgb Root Matriz Color Dance, Danielle E. Gauthier

Theses and Dissertations

RGB Root Matriz Color Dance (Color Dance) is an immersive, interactive experience that combines poetic phrases and color filters to create a womb-like environment. Designed by Danielle Gauthier, this artistic piece uses a webcam to respond to users’ movements in real time, allowing them to confront and express their emotions through metaphor and dance. Color Dance creates a unique platform for self-discovery and empowerment by fostering a connection between the body and discomforting emotions.


Simulating Information And Communication Applications In Employee Interaction Network Models, Matthew Kanter 2024 University of Mary Washington

Simulating Information And Communication Applications In Employee Interaction Network Models, Matthew Kanter

Departmental Honors & Graduate Capstone Projects

Information and communication technology (ICT) use has been identified throughout its development and evolution with the Internet boom as a net positive tool for most employees and organizations in the working world. Only recently have studies regarding employees’ well-being begun to come to the forefront of research regarding these rapidly evolving technologies, however these are important issues to discuss in the context of work-life boundary management, emotional exhaustion, overwhelming stress levels, and moral disengagement among other employee well-being dimensions. To explore how employees’ well being might be influenced by ICT use, this study conducted a quantitative survey and analyzed a …


Analyzing Information Cascades Through Machine Learning And Data Analytics, Betul Agirman 2024 University of Connecticut

Analyzing Information Cascades Through Machine Learning And Data Analytics, Betul Agirman

Honors Scholar Theses

In today's digital age, social media platforms have become pivotal in influencing public opinion and behavior, with information spreading being both beneficial and detrimental. This rapid spread is typically called an information cascade, and they are important in further understanding social influence, managing misinformation, and even predicting potential trends of public responses. With social media, people are connected so easily to one another like a network, wherein it becomes possible for them to influence each other’s behavior and decisions. Utilizing a dataset from Weibo that spans critical periods of the COVID-19 outbreak, this study integrates machine learning and data analytics …


Investigating Autonomous Ground Vehicles For Weed Elimination, Abraham Mitchell 2024 University of Arkansas, Fayetteville

Investigating Autonomous Ground Vehicles For Weed Elimination, Abraham Mitchell

Computer Science and Computer Engineering Undergraduate Honors Theses

The management of weeds in crop fields is a continuous agricultural problem. The use of herbicides is the most common solution, but herbicidal resistance decreases effectiveness, and the use of herbicides has been found to have severe adverse effects on human health and the environment. The use of autonomous drone systems for weed elimination is an emerging solution, but challenges in GPS-based localization and navigation can impact the effectiveness of these systems. The goal of this thesis is to evaluate techniques for minimizing localization errors of drones as they attempt to eliminate weeds. A simulation environment was created to model …


Enhancing Cybersecurity In Wireless Sensor Networks: Machine Learning, Blockchain And Future Perspectives, Ilemona solomon Atawodi 2024 University of Southern Mississippi

Enhancing Cybersecurity In Wireless Sensor Networks: Machine Learning, Blockchain And Future Perspectives, Ilemona Solomon Atawodi

Dissertations

Security in the Industrial Internet of Things encounters various security issues but the main issues can be broken down into three core issues: Availability, Integrity, and Confidentiality. Security challenges generally tend to be caused by a failure of the system in one of these areas or cause a failure in one of these areas. Therefore researching scalable solutions to these security issues is prudent to explore methods that could be applied to large-scale industrial IIoT with tens to hundreds of devices as well as small-scale systems on a tiny factory floor comprising of just a few devices. In our research, …


Detection Of Deficiencies And Data Analysis Of Bridge Members With Deep Convolutional Neural Networks, Bennett Jackson 2024 University of Nebraska-Lincoln

Detection Of Deficiencies And Data Analysis Of Bridge Members With Deep Convolutional Neural Networks, Bennett Jackson

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

Concrete cracks and structural steel corrosion are two of the most common defects in bridges. Quantifying and classifying these defects provide bridge inspectors and engineers with valuable data for assessing deterioration levels. However, the bridge inspection process is typically a subjective, time intensive, and tedious task, as defects can be overlooked or in locations not easily accessible. Previous studies have investigated deep learning-based inspection methods, implementing popular models such as Mask R-CNN and U-Net. The architectures of these models offer certain advantages depending on the required task. This thesis aims to evaluate and compare Mask R-CNN and U-Net regarding their …


Cloud Computing Integration Into Mixed-Reality: Physical To Abstraction, Yassine Chahid, Patrick Slattery 2024 CUNY New York City College of Technology

Cloud Computing Integration Into Mixed-Reality: Physical To Abstraction, Yassine Chahid, Patrick Slattery

Publications and Research

This research evaluates the progression of cloud computing and mixed-reality technologies, and to identify how these technologies influence advancements in the latter. Both cloud computing and mixed reality have significantly impacted the IT field and the services available to the public and various institutions. Cloud computing provides a valuable way to process information or allocate computational resources on otherwise limited hardware. Augmented or virtual reality hardware would greatly benefit from this by offloading resource-intensive tasks to other machines. The research methodology involves analyzing essential components of both innovations, divided into multiple categories. These components range from physical, hardware-based elements to …


Multi-Domain Secure Dds Networks For Aerial And Ground Vehicle Communications, Daniel Pendleton 2024 Clemson University

Multi-Domain Secure Dds Networks For Aerial And Ground Vehicle Communications, Daniel Pendleton

All Theses

none


4-Channel Spatially Multiplexed Communication System In Single-Core Optical Fibers, Ce Su 2024 Florida Institute of Technology

4-Channel Spatially Multiplexed Communication System In Single-Core Optical Fibers, Ce Su

Theses and Dissertations

This dissertation delves into exploring and advancing spatial domain / space division multiplexing (SDM) technologies within single-core optical fibers, a frontier in optical fiber communications poised to meet the burgeoning global demand for data transmission. At the heart of this research is the pursuit to significantly enhance the capacity and efficiency of optical fiber communication systems without necessitating additional fiber infrastructure. This work unveils a new paradigm in optical fiber communications characterized by a pioneering 4-channel SDM system through a meticulous process encompassing theoretical modeling, computational simulations, design innovations, and rigorous experimental validations. Theoretical contributions include the development of refined …


Hybrid Method Neighbor Node Discovery In Wireless Sensor Networks: A Framework, Sagar Mekala, Shahu Chatrapati Kaila, Jyothi Rani Matang 2024 Department of Computer Science and Engineering, CVR College of Engineering, Telangana 501510, India

Hybrid Method Neighbor Node Discovery In Wireless Sensor Networks: A Framework, Sagar Mekala, Shahu Chatrapati Kaila, Jyothi Rani Matang

Makara Journal of Technology

Wireless devices are now being adapted for diverse purposes, such as healthcare, agriculture, transportation, and tactical operations, which present challenges in network formation owing to high device mobility. Current methods rely on discovery techniques for forming wireless sensor networks (WSNs); however, the existing research has been criticized for its high time complexity and redundant neighbor discovery process. In this study, we provide a hybrid strategy to effectively handle the difficulties of locating neighboring nodes in WSNs. Our method combines several strategies to produce precise and effective neighbor detection. Herein, shared memory–based discovery, a beacon technique, and range and distance overlap …


The Next Threat Landscape: Securing America’S Cyber-Physical Systems, Grayson Thomas 2024 Murray State University

The Next Threat Landscape: Securing America’S Cyber-Physical Systems, Grayson Thomas

Honors College Theses

The goal of this research is to explore, identify, and enumerate the security threats that exist to industry current industrial controls systems (ICS) and supervisory control and data acquisition systems (SCADA). A scale lab similar to industry standard will be built and developed for research purposes. The Purdue Model for ICS and the Cyber Kill Chain will be referenced as frameworks for attack sequences, and the MITRE ATT&CK framework will be referenced for attack types. Attempts will be made to compromise the various pieces of our built SCADA system via configuration errors, software vulnerabilities, and deployment mistakes common with industrial …


A Design Science Approach To Investigating Decentralized Identity Technology, Janelle Krupicka 2024 William & Mary

A Design Science Approach To Investigating Decentralized Identity Technology, Janelle Krupicka

Cybersecurity Undergraduate Research Showcase

The internet needs secure forms of identity authentication to function properly, but identity authentication is not a core part of the internet’s architecture. Instead, approaches to identity verification vary, often using centralized stores of identity information that are targets of cyber attacks. Decentralized identity is a secure way to manage identity online that puts users’ identities in their own hands and that has the potential to become a core part of cybersecurity. However, decentralized identity technology is new and continually evolving, which makes implementing this technology in an organizational setting challenging. This paper suggests that, in the future, decentralized identity …


Enhancing Cybersecurity Learning Efficiency: Leveraging Spaced Repetition Systems For Rapid Adaptation, Takudzwanashe Nyabadza 2024 Collin College

Enhancing Cybersecurity Learning Efficiency: Leveraging Spaced Repetition Systems For Rapid Adaptation, Takudzwanashe Nyabadza

Research Week

No abstract provided.


Secure Cislunar Communication Architecture: Cryptographic Capabilities And Protocols For Lunar Missions, Michael Hamblin, Bilal Abu Bakr 2024 Collin College

Secure Cislunar Communication Architecture: Cryptographic Capabilities And Protocols For Lunar Missions, Michael Hamblin, Bilal Abu Bakr

Research Week

The surge in lunar missions intensifies concerns about congestion and communication reliability. This study proposes a secure cislunar architecture for real-time, cross-mission information exchange. We focus on cryptographic protocols and network design for a native IPv6 cislunar transit system.

Through a review of internet and space communication advancements, we emphasize the need for a secure network, exemplified by LunaNet. A robust data transit system with encryption is crucial for a common communication infrastructure. Traditional protocols face latency challenges. We advocate for user-friendly encryption methods to address confidentiality within the CIA Triad. Integrity is maintained through cryptographic message authentication codes. Availability …


Chatting With Online Agent, Guoxi Robert Zhang 2024 Andrews University

Chatting With Online Agent, Guoxi Robert Zhang

Honors Theses

This study investigates trust in AI-generated language fluency. Participants engaged with both human and AI-generated content, varying in fluency. Findings were to favor trust in fluent human and AI interactions over disfluent ones. Understanding fluency's impact can inform AI design and encourage critical thinking when dealing with AI-generated content. By using qualitative analysis of think-aloud reports, we examined strategies that people use to assess texts labeled as human-generated and AI-generated content.


Objective.Gg: Uniting Scholastic Esports, Douglas Beirne 2024 St. Mary's University

Objective.Gg: Uniting Scholastic Esports, Douglas Beirne

Posters - 2024

Objective.gg is a startup recruitment platform within the scholastic esports scene that seeks to unite esports prospects with collegiate esports programs in an effective manner. Objective.gg seeks to accomplish its mission by operating an online platform that allows prospects and collegiate coaches to create their own profiles and connect with one another, building a community in the process. This platform will begin with a free tier, but additional features will be offered through a subscription-based model with two additional pricing tiers to choose from. The online platform will be supported by free online and paid in-person tournaments for Objective.gg platform …


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