California State University, San Bernardino
California Polytechnic State University at San Luis Obispo
University Of New Orleans
University of Tennessee, Knoxville
University of Arkansas, Fayetteville
Harrisburg University of Science and Technology
Technological University Dublin
Security-Enhanced Serial Communications,
2023
University of South Florida
Security-Enhanced Serial Communications, John White, Alexander Beall, Joseph Maurio, Dane Fichter, Dr. Matthew Davis, Dr. Zachary Birnbaum
Military Cyber Affairs
Industrial Control Systems (ICS) are widely used by critical infrastructure and are ubiquitous in numerous industries including telecommunications, petrochemical, and manufacturing. ICS are at a high risk of cyber attack given their internet accessibility, inherent lack of security, deployment timelines, and criticality. A unique challenge in ICS security is the prevalence of serial communication buses and other non-TCP/IP communications protocols. The communication protocols used within serial buses often lack authentication and integrity protections, leaving them vulnerable to spoofing and replay attacks. The bandwidth constraints and prevalence of legacy hardware in these systems prevent the use of modern message authentication and …
Targeted Adversarial Attacks Against Neural Network Trajectory Predictors,
2023
Washington University in St. Louis
Targeted Adversarial Attacks Against Neural Network Trajectory Predictors, Kaiyuan Tan
McKelvey School of Engineering Theses & Dissertations
Trajectory prediction is an integral component of modern autonomous systems as it allows for envisioning future intentions of nearby moving agents. Due to the lack of other agents' dynamics and control policies, deep neural network (DNN) models are often employed for trajectory forecasting tasks. Although there exists an extensive literature on improving the accuracy of these models, there is a very limited number of works studying their robustness against adversarially crafted input trajectories. To bridge this gap, in this paper, we propose a targeted adversarial attack against DNN models for trajectory forecasting tasks. We call the proposed attack TA4TP for …
Detection Of Crypto-Ransomware Attack Using Deep Learning,
2023
Kennesaw State University
Detection Of Crypto-Ransomware Attack Using Deep Learning, Muna Jemal
Master of Science in Computer Science Theses
The number one threat to the digital world is the exponential increase in ransomware attacks. Ransomware is malware that prevents victims from accessing their resources by locking or encrypting the data until a ransom is paid. With individuals and businesses growing dependencies on technology and the Internet, researchers in the cyber security field are looking for different measures to prevent malicious attackers from having a successful campaign. A new ransomware variant is being introduced daily, thus behavior-based analysis of detecting ransomware attacks is more effective than the traditional static analysis. This paper proposes a multi-variant classification to detect ransomware I/O …
Is Realt Reality? Investigating The Use Of Blockchain Technology And Tokenization In Real Estate Transactions,
2023
University of Minnesota Law School
Is Realt Reality? Investigating The Use Of Blockchain Technology And Tokenization In Real Estate Transactions, Caroline Moriarty
Minnesota Journal of Law, Science & Technology
No abstract provided.
Operationalizing Deterrence By Denial In The Cyber Domain,
2023
University of South Florida
Operationalizing Deterrence By Denial In The Cyber Domain, Gentry Lane
Military Cyber Affairs
No abstract provided.
Enhancing The Battleverse: The People’S Liberation Army’S Digital Twin Strategy,
2023
University of South Florida
Enhancing The Battleverse: The People’S Liberation Army’S Digital Twin Strategy, Joshua Baughman
Military Cyber Affairs
No abstract provided.
What Senior U.S. Leaders Say We Should Know About Cyber,
2023
National Defense University, College of Information and Cyberspace
What Senior U.S. Leaders Say We Should Know About Cyber, Dr. Joseph H. Schafer
Military Cyber Affairs
On April 6, 2023, the Atlantic Council’s Cyber Statecraft Initiative hosted a panel discussion on the new National Cybersecurity Strategy. The panel featured four senior officials from the Office of the National Cyber Director (ONCD), the Department of State (DoS), the Department of Justice (DoJ), and the Department of Homeland Security (DHS). The author attended and asked each official to identify the most important elements that policymakers and strategists must understand about cyber. This article highlights historical and recent struggles to express cyber policy, the responses from these officials, and the author’s ongoing research to improve national security cyber policy.
Lignin Copolymer Property Prediction Using Machine Learning,
2023
University of Arkansas
Lignin Copolymer Property Prediction Using Machine Learning, Collin Larsen
Chemical Engineering Undergraduate Honors Theses
Lignin, an abundant biopolymer, is a waste byproduct of the paper and pulp industry. Despite its renewable nature and potential applicability in various products, such as plastics and composites, the development of lignin-based materials has been impeded by the cumbersome, Edisonian process of trial and error. This research proposes a novel approach to forecasting the properties of lignin-based copolymers by utilizing a recurrent neural network (RNN) based on the Keras models previously created by Tao et al. Example units of modified lignin were synthesized via esterification and amination functional group modifications. To increase the efficiency and accuracy of the prediction …
Fuel Prediction: Determining The Desirable Stops For The Cheapest Road Trips,
2023
University of Arkansas, Fayetteville
Fuel Prediction: Determining The Desirable Stops For The Cheapest Road Trips, Maxx Smith
Computer Science and Computer Engineering Undergraduate Honors Theses
Current technology has given rise to many advanced route-planning applications that are available for use by the general public. Gone are the days of preparing for road trips by looking at a paper map for hours on end trying to determine the correct exits or calculate the distance to be traveled. However, with the use of modern technology, there is a certain aspect of forward-thinking that is now lost with planning a road trip. One of the biggest constraints that often gets left on the backburner is deciding when and where to stop to refuel the car. This report is …
Svar: A Virtual Machine For Portable Code On Reconfigurable Accelerators,
2023
University of Arkansas, Fayetteville
Svar: A Virtual Machine For Portable Code On Reconfigurable Accelerators, Nathaniel Fredricks
Computer Science and Computer Engineering Undergraduate Honors Theses
The SPAR-2 array processor was designed as an overlay architecture for implementation on Xilinx Field Programmable Gate Arrays (FPGAs). As an overlay, the SPAR-2 array processor can be configured to take advantage of the specific resources available on different FPGAs. However once configured, the SPAR-2 requires programmer’s to have knowledge of the low level architecture, and write platform-specific code. In this thesis SVAR, a hardware/software co-designed virtual machine, is proposed that runs on the SPAR-2. SVAR allows programmers to write portable, platform-independent code once and have it interpreted for any specific configuration. Results are presented that verify the virtual machine …
Culture In Computing: The Importance Of Developing Gender-Inclusive Software,
2023
University of Arkansas, Fayetteville
Culture In Computing: The Importance Of Developing Gender-Inclusive Software, Creighton France
Computer Science and Computer Engineering Undergraduate Honors Theses
The field of computing as we know it today exists because of the contributions of numerous female mathematicians, computer scientists, and programmers. While working with hardware was viewed as “a man’s job” during the mid-20th century, computing and programming was viewed as a noble and high-paying field for women to occupy. However, as time has progressed, the U.S. has seen a decrease in the number of women pursuing computer science. The idea that computing is a masculine discipline is common in the U.S. today for reasons such as male-centered marketing of electronics and gadgets, an inaccurate representation of what it …
A Long-Term Funds Predictor Based On Deep Learning,
2023
California State University, San Bernardino
A Long-Term Funds Predictor Based On Deep Learning, Shuiyi Kuang
Electronic Theses, Projects, and Dissertations
Numerous neural network models have been created to predict the rise or fall of stocks since deep learning has gained popularity, and many of them have performed quite well. However, since the share market is hugely influenced by various policy changes or unexpected news, it is challenging for investors to use such short-term predictions as a guide. In this paper, we try to find a suitable long-term predictor for the funds market by testing different kinds of neural network models, including the Long Short-Term Memory(LSTM) model with different layers, the Gated Recurrent Units(GRU) model with different layers, and the combination …
Analyzing The Impact Of Automation On Employment In Different Us Regions: A Data-Driven Approach,
2023
California State University, San Bernardino
Analyzing The Impact Of Automation On Employment In Different Us Regions: A Data-Driven Approach, Thejaas Balasubramanian
Electronic Theses, Projects, and Dissertations
Automation is transforming the US workforce with the increasing prevalence of technologies like robotics, artificial intelligence, and machine learning. As a result, it is essential to understand how this shift will impact the labor market and prepare for its effects. This culminating experience project aimed to examine the influence of computerization on jobs in the United States and answer the following research questions: Q1. What factors affect how likely different jobs will be automated? Q2. What are the possible effects of automation on the US workforce across states and industries? Q3. What are the meaningful predictors of the likelihood of …
Pillow Based Sleep Tracking Device Using Raspberry Pi,
2023
California State University, San Bernardino
Pillow Based Sleep Tracking Device Using Raspberry Pi, Venkatachalam Seviappan
Electronic Theses, Projects, and Dissertations
Almost half of all people have sleep interruptions at some point in their lives, making sleep disorders a common issue that affects a sizeable section of the population. Both their physical and emotional well-being may suffer as a result of this.Insomnia, which is a prevalent sleep disorder, is identified by symptoms including insufficient sleep duration and quality, trouble initiating sleep, multiple nighttime awakenings, early morning awakenings, and non-restorative sleep. It is essential to employ sleep monitoring systems to detect sleeping disorders as soon as possible for prompt diagnosis and treatment. To avoid sleep related health issues, there are plenty of …
Ott Subscriber Churn Prediction Using Machine Learning,
2023
California State University - San Bernardino
Ott Subscriber Churn Prediction Using Machine Learning, Needhi Devan Senthil Kumar
Electronic Theses, Projects, and Dissertations
Subscriber churn is a critical issue for companies that rely on recurring revenue from subscription-based services like the OTT platform. Machine Learning algorithms can be used to predict churn and develop targeted retention strategies to address the specific needs and concerns of at-risk subscribers. The research questions are 1) What Machine Learning algorithms are used to overcome subscriber churn? 2) How to predict subscribers’ churn in the OTT platform using Machine Learning? 3) How to retain subscribers and improve customer targeting? The dataset was collected from the Kaggle repository and implemented it into the various prediction algorithms used in previous …
Bridging The Gap Between Public Organizaions And Cybersecurity,
2023
California State University, San Bernardino
Bridging The Gap Between Public Organizaions And Cybersecurity, Christopher Boutros
Electronic Theses, Projects, and Dissertations
Cyberattacks are a major problem for public organizations across the nation, and unfortunately for them, the frequency of these attacks is constantly growing. This project used a case study approach to explore the types of cybersecurity public organization agencies face and how those crimes can be mitigated. The goal of this paper is to understand how public organization agencies have prepared for cyberattacks and discuss additional suggestions to improve their current systems with the current research available This research provides an analysis of current cyber security systems, new technologies that can be implemented, roadblocks public agencies face before and during …
Infrastructure-As-Code: Automating The Deployment On Aws Using Terraform,
2023
Grand Valley State University
Infrastructure-As-Code: Automating The Deployment On Aws Using Terraform, Srikar Pratap
Culminating Experience Projects
In my master’s project, I used Terraform to create a scalable infrastructure on Amazon Web Services (AWS) for my personal website. Terraform is an open-source infrastructure-as-code (IAC) tool that allows you to create, manage and provision infrastructure resources, such as virtual machines, storage accounts, networks, and more, across multiple cloud providers and on-premises data centers using a declarative configuration language. A scalable infrastructure is important because it enables a system or application to handle increasing amounts of traffic or workload without experiencing performance issues or downtime. It ensures that the system remains responsive, available, and reliable as an organization grows …
Ransomware: Evaluation Of Mitigation And Prevention Techniques,
2023
Kennesaw State University
Ransomware: Evaluation Of Mitigation And Prevention Techniques, Juanjose Rodriguez-Cardenas
Symposium of Student Scholars
Ransomware is classified as one of the main types of malware and involves the design of exploitations of new vulnerabilities through a host. That allows for the intrusion of systems and encrypting of any information assets and data in order to demand a sum of payment normally through untraceable cryptocurrencies such as Monero for the decryption key. This rapid security threat has put governments and private enterprises on high alert and despite evolving technologies and more sophisticated encryption algorithms critical assets are being held for ransom and the results are detrimental, including the recent Colonial Pipeline ransomware attack in 2021 …
Ransomware: What Is Ransomware, And How To Prevent It,
2023
Old Dominion University
Ransomware: What Is Ransomware, And How To Prevent It, Brandon Chambers
Cybersecurity Undergraduate Research Showcase
This research paper answers the question, “What is Ransomware, and How to prevent it?”. This paper will discuss what ransomware is, its history about ransomware, how ransomware attacks Windows systems, how to prevent ransomware, how to handle ransomware once it is already on the network, ideas for training professionals to avoid ransomware, and how anti-virus helps defend against ransomware. Many different articles, case studies, and professional blogs will be used to complete the research on this topic.
Region-Specified Inverse Design Of Absorption And Scattering In Nanoparticles By Using Machine Learning,
2023
Chapman University
Region-Specified Inverse Design Of Absorption And Scattering In Nanoparticles By Using Machine Learning, Alex Vallone, Nooshin M. Estakhri, Nasim Mohammadi Estrakhri
Engineering Faculty Articles and Research
Machine learning provides a promising platform for both forward modeling and the inverse design of photonic structures. Relying on a data-driven approach, machine learning is especially appealing for situations when it is not feasible to derive an analytical solution for a complex problem. There has been a great amount of recent interest in constructing machine learning models suitable for different electromagnetic problems. In this work, we adapt a region-specified design approach for the inverse design of multilayered nanoparticles. Given the high computational cost of dataset generation for electromagnetic problems, we specifically investigate the case of a small training dataset, enhanced …
