Digital Commons Network^™

Small Business Cybersecurity: A Loophole To Consumer Data, Matthew R. Espinosa

The Scholar: St. Mary's Law Review on Race and Social Justice

Small businesses and small minority owned businesses are vital to our nation’s economy; therefore legislation, regulation, and policy has been created in order to assist them in overcoming their economic stability issues and ensure they continue to serve the communities that rely on them. However, there is not a focus on regulating nor assisting small businesses to ensure their cybersecurity standards are up to par despite them increasingly becoming a victim of cyberattacks that yield high consequences. The external oversight and assistance is necessary for small businesses due to their lack of knowledge in implementing effective cybersecurity policies, the fiscal …

Antenna Designs For Cubesat-Borne, Continuous-Waveform Radar, Logan E. Voigt, Reyhan Baktur

Utah Space Grant Consortium

CubeSat-borne radar has many potential applications in space exploration including tracking, imaging, and weather prediction. A continuous-waveform radar has advantages of compact size and low power consumption, making it suitable to implement on small platforms such as CubeSats. This paper demonstrates an isolation technique that overcomes the self-interference between the transmit and receive antennas inherent to continuous-waveform radar. The presented approach combines opposite circularly polarized antennas on two deployed solar panels to minimize the self-interference. The prototype antennas are tested on a 6U CubeSat frame and the results show more than 40 dB isolation, satisfying the power budget requirements.

The Impact Of Interactions Among Native Grassland Species: A Study Of Interactions Between Two Invasive Species (Bromus Tectorum And Setaria Faberi) And Two Native Species (Helianthus Annuus And Rudbeckia Hirta), Nash Leef

Department of Environmental Studies: Undergraduate Student Theses

Allelopathy is a description of an interaction between two plant species, usually negative, that impacts their growth or germination. There has been ample data published regarding the impact of allelopathic species in agricultural settings, but little attention has been given to the potential interactions between invasive and native species. Two culprits that have employed allelopathy to great effect in agricultural settings are cheatgrass (Bromus tectorum) and giant foxtail (Setaria faberi). This study posits that allelopathic interactions, similar to those found in agriculture, are occurring between native and invasive species on the Great Plains.

A set of greenhouse trials was established …

Evolution Of Combined Arms Tactics In Heterogeneous Multi-Agent Teams, Robert J. Wilson, David W. King, Gilbert L. Peterson

Faculty Publications

Multi-agent systems research is concerned with the emergence of system-level behaviors from relatively simple agent interactions. Multi-agent systems research to date is primarily concerned with systems of homogeneous agents, with member agents both physically and behaviorally identical. Systems of heterogeneous agents with differing physical or behavioral characteristics may be able to accomplish tasks more efficiently than homogeneous teams, via cooperation between mutually complementary agent types. In this article, we compare the performance of homogeneous and heterogeneous teams in combined arms situations. Combined arms theory proposes that the application of heterogeneous forces, en masse, can generate effects far greater than outcomes …

Machine Learning Classification Of Digitally Modulated Signals, James A. Latshaw

Electrical & Computer Engineering Theses & Dissertations

Automatic classification of digitally modulated signals is a challenging problem that has traditionally been approached using signal processing tools such as log-likelihood algorithms for signal classification or cyclostationary signal analysis. These approaches are computationally intensive and cumbersome in general, and in recent years alternative approaches that use machine learning have been presented in the literature for automatic classification of digitally modulated signals. This thesis studies deep learning approaches for classifying digitally modulated signals that use deep artificial neural networks in conjunction with the canonical representation of digitally modulated signals in terms of in-phase and quadrature components. Specifically, capsule networks are …

The Effects Of Metronomic And Maximum-Tolerated Dose Chemotherapy In Colorectal Cancer Angiogenesis: A Combined Approach Using Endoscopic Diffuse Reflectance Spectroscopy And Mrna Expression, Ariel Isaac Mundo Ortiz

Graduate Theses and Dissertations

Colorectal cancer (CRC) continues to be one of the most incident and deadliest types of cancer worldwide. Chemotherapy has proven effective to reduce tumor burden for CRC patients, but there are several disadvantages associated with the use of mainstay maximtolerated dose (MTD) chemotherapeutic strategies. Metronomic chemotherapy (MET) has been developed as an alternative that addresses the shortcomings of maximum-tolerated dose chemotherapy but so far its effectiveness as a neoadjuvant strategy for CRC has not been explored.

This dissertation uses a combined optics and molecular biology approach (using diffuse reflectance spectroscopy and mRNA expression) to study the changes in angiogenesis and …

Russia, Europe And Central Asia Energy Security And Pipeline Politics, Mehmet Kınacı

Graduate Program in International Studies Theses & Dissertations

Energy Security will continue to remain as one of the top security concerns for Europe. Depleting reserves and growing energy demand have increased European dependence on external energy resources. Today, Russia is by far the largest supplier of oil, coal and the natural gas to Europe. Oil and natural gas revenues have played a vital role to rebound the Russian economy and have supported Putin’s ambitions to reestablish Russia as a great power, increasing its influence over the former Soviet space. This complex energy relationship has increasingly been a cause of concern.

The main question this study seeks to answer …

The Iwar Range + 21 Years: Cyber Defense Education In 2022, Joseph H. Schafer, Chris Morrell, Ray Blaine

Military Cyber Affairs

Twenty-one years ago, The IWAR Range paper published by CCSC described nascent information assurance (now cybersecurity[1]) education programs and the inspiration and details for constructing cyber ranges and facilitating cyber exercises. This paper updates the previously published work by highlighting the dramatic evolution of the cyber curricula, exercise networks and ranges, influences, and environments over the past twenty years.

[1] In 2014, DoD adopted “cybersecurity” instead of “information assurance.” [34:1]

Hypergaming For Cyber: Strategy For Gaming A Wicked Problem, Joshua A. Sipper

Military Cyber Affairs

Cyber as a domain and battlespace coincides with the defined attributes of a “wicked problem” with complexity and inter-domain interactions to spare. Since its elevation to domain status, cyber has continued to defy many attempts to explain its reach, importance, and fundamental definition. Corresponding to these intricacies, cyber also presents many interlaced attributes with other information related capabilities (IRCs), namely electromagnetic warfare (EW), information operations (IO), and intelligence, surveillance, and reconnaissance (ISR), within an information warfare (IW) construct that serves to add to its multifaceted nature. In this cyber analysis, the concept of hypergaming will be defined and discussed in …

Data-Driven Design And Analysis Of Next Generation Mobile Networks For Anomaly Detection And Signal Classification With Fast, Robust And Light Machine Learning, Muhammed Furkan Küçük

USF Tampa Graduate Theses and Dissertations

This research focuses on machine (and deep) learning applications (including clustering,anomaly detection and signal classification) for self-organizing and next generation mobile networks in wireless communications. Specifically, this dissertation document will address the three different topics.

First, in the study titled “Performance analysis of neural network topologies and hyperparameters for deep clustering”, we explore the relationship between the clustering performance and network complexity. Deep learning found its initial footing in supervised applications such as image and voice recognition successes of which were followed by deep generative models across similar domains. In recent years, researchers have proposed creative learning representations to utilize …

Volume 13, Payton Davenport, Audrey Lemons, Jacob Shope, Haley Smith, Cassandra Poole, Rachel Cannon, Rachel Boch, Suzanne Stetson

Incite: The Journal of Undergraduate Scholarship

Introduction Dr. Roger A. Byrne, Dean

From the Editor Dr. Larissa “Kat” Tracy

From the Designers Rachel English, Rachel Hanson

The Effect of Compliment Type on the Estimated Value of the Compliment by Payton Davenport, Audrey Lemons, and Jacob Shope

The Imperial Japanese Military: A New Identity in the Twentieth Century, 1853–1922 by Haley Smith

Longwood University’s campus: Human-cultivated Soil has Higher Microbial Diversity than Soil Collected from Wild Sites by Cassandra Poole

Reminiscent Modernism: Poetry Magazine’s Modernist Nostalgia for the Past by Rachel Cannon

Challenges Faced by Healthcare Workers During the COVID-19 Pandemic: A Preliminary Study of Age and …

Gravimetric Determination Of The Adsorption Capacity Of Zirconium Hydroxide For Isopropanol, Riley Bennett

Symposium of Student Scholars

Zirconium hydroxide’s adsorption properties make it useful for the decomposition of chemical warfare agents and toxic industrial chemicals. In the current study, isopropanol is used to examine the adsorption behavior of the zirconium hydroxide surface sites through a series of microreactor experiments. Initially, the mass delivery of isopropanol is calibrated as a function of temperature and gas flow rate. Separate experiments can then be done by flowing the isopropanol mixture through a sample of zirconium hydroxide to quantitatively determine the amount of isopropanol that can adsorb onto a sample of zirconium hydroxide. FT-IR spectra of the gas mixtures flowing from …

Gas Phase Structure Characterization Of Host-Guest Systems Using Ion Mobility Spectrometry, Jamir Shrestha

Theses and Dissertations

This dissertation focuses on the investigation of gas-phase characteristics of cucurbituril host-guest systems using ion mobility spectrometry (IMS) and related techniques. Collision cross-sections (CCS) of alkylammonium complexes of cucurbit[n]uril (CB[n]) are measured to understand the allosteric interactions that induce conformational changes in the complex in the presence of metal cations on one of the portals of the cucurbit[6]uril (CB[6]) host. Cationic species on one CB[6] rim sterically force longer linear alkylammonium guests out of the cucurbituril cavity during complex formation. Similarly, rigid cucurbituril-metal complexes were studied using IMS to demonstrate the effect of long-range ion-neutral interactions on the gas phase …

Cybersecurity And Threat Modeling, Kumar Setty

Computer Science Research Seminars and Symposia

An introduction to cybersecurity and threat modeling.

Volume 8 Full Text, Bjur Staff

Butler Journal of Undergraduate Research

No abstract provided.

Circulation, Volume 27, No. 2, Center For Coastal Physical Oceanography, Old Dominion University

CCPO Circulation

Spring 2022 issue of CCPO Circulation featuring the article "Looking Back While Moving Forward," by Sönke Dangendorf.

A Damaged Reputation: Nuclear Depictions In Entertainment Media, Alexander Cannon

Chemistry & Biochemistry Student Scholarship

This paper, originally written for Dr. Adamus Liotta in an honors chemistry class, explores the possibility of a significant influence over public common sense found in the depictions of entertainment media. Through careful analysis and interpretation of Godzilla, The Simpsons, Fallout, and Call of Duty, this paper finds a synergy throughout this diverse range of audience, medium and historical origin, which culminates in an effect much greater than the sum of its parts. This effect frames nuclear science, of any kind, in a hyperbolically catastrophic and horrific light, reinforcing an excessively cautious, pessimistic public perspective on nuclear technology …

The Global Rise Of Online Devices, Cyber Crime And Cyber Defense: Enhancing Ethical Actions, Counter Measures, Cyber Strategy, And Approaches, Naresh Kshetri

Dissertations

The rise of online devices, online users, online shopping, online gaming, and online teaching has ultimately given rise to online attacks and online crimes. As cases of COVID-19 seem to increase day by day, so do online crimes and attacks (as many sectors and organizations went 100% online). Technological advancements and cyber warfare already generated many ethical issues, as internet users increasingly need ethical cyber defense strategies.

Individual internet users have challenges on their end; and on the other end, nation states (some secretly, some openly), are investing in robot weapons and autonomous weapons systems (AWS). New technologies have combined …

Analysis Of The Magnetic Signature Of Surface Waves Measured In A Laboratory Experiment, John Kluge, Alex Soloviev, Cayla W. Dean, Geoffrey K. Morrison, Brian K. Haus

Marine & Environmental Sciences Faculty Articles

A magnetic signature is created by secondary magnetic field fluctuations caused by the phenomenon of seawater moving in Earth’s magnetic field. A laboratory experiment was conducted at the SUrge STructure Atmosphere INteraction (SUSTAIN) facility to measure the magnetic signature of surface waves using a differential method: a pair of magnetometers, separated horizontally by one-half wavelength, were placed at several locations on the outer tank walls. This technique significantly reduced the extraneous magnetic distortions that were detected simultaneously by both sensors and additionally doubled the magnetic signal of surface waves. Accelerometer measurements and local gradients were used to identify magnetic noise …

Zero Trust And Advanced Persistent Threats: Who Will Win The War?, Bilge Karabacak, Todd Whittaker

All Faculty and Staff Scholarship

Advanced Persistent Threats (APTs) are state-sponsored actors who break into computer networks for political or industrial espionage. Because of the nature of cyberspace and ever-changing sophisticated attack techniques, it is challenging to prevent and detect APT attacks. 2020 United States Federal Government data breach once again showed how difficult to protect networks from targeted attacks. Among many other solutions and techniques, zero trust is a promising security architecture that might effectively prevent the intrusion attempts of APT actors. In the zero trust model, no process insider or outside the network is trusted by default. Zero trust is also called perimeterless …

Kinetics, Characterization, And Applications In The Development Of Next-Generation Cure-On-Demand Polymeric Materials Through Frontal Polymerization, Daniel Paul Gary

LSU Doctoral Dissertations

Frontal polymerization (FP) is a process in which a front propagates in a localized reaction zone converting monomer into polymer. This work explored the kinetics and applications of FP for the development of cure-on-demand materials.

The kinetic effects of fillers on frontal polymerization have not been thoroughly explored. In Chapter 2, various fillers were used, and their effects on front velocity and front temperature were determined. Clay minerals are primarily used, but the thermal conductive effects of milled carbon fiber were also explored. It was found that some fillers inhibit frontal polymerization through radical scavenging, while others increased the front …

Considerations For Radio Frequency Fingerprinting Across Multiple Frequency Channels, Jose A. Gutierrez Del Arroyo, Brett J. Borghetti, Michael A. Temple

Faculty Publications

Radio Frequency Fingerprinting (RFF) is often proposed as an authentication mechanism for wireless device security, but application of existing techniques in multi-channel scenarios is limited because prior models were created and evaluated using bursts from a single frequency channel without considering the effects of multi-channel operation. Our research evaluated the multi-channel performance of four single-channel models with increasing complexity, to include a simple discriminant analysis model and three neural networks. Performance characterization using the multi-class Matthews Correlation Coefficient (MCC) revealed that using frequency channels other than those used to train the models can lead to a deterioration in performance from …

A Critical Comparison Of Brave Browser And Google Chrome Forensic Artefacts, Stuart Berham, Sarah Morris

Journal of Digital Forensics, Security and Law

Digital forensic practitioners are tasked with the identification, recovery and analysis of Internet browser artefacts which may have been used in the pursuit of committing a civil or criminal offence. This research paper critically compares the most downloaded browser, Google Chrome, against an increasingly popular Chromium browser known as Brave, said to offer privacy-by-default. With increasing forensic caseloads, data complexity, and requirements for method validation to satisfy ISO 17025 accreditation, recognising the similarities and differences between the browsers, developed on the same underlying technology is essential. The paper describes a series of conducted experiments and subsequent analysis to identify artefacts …

Technical Analysis Of Thanos Ransomware, Ikuromor Ogiriki, Christopher Beck, Vahid Heydari

College of Science & Mathematics Departmental Research

Ransomware is a developing menace that encrypts users’ files and holds the decryption key hostage until the victim pays a ransom. This particular class of malware has been in charge of extortion hundreds of millions of dollars every year. Adding to the problem, generating new variations is cheap. Therefore, new malware can detect antivirus and intrusion detection systems and evade them or manifest in ways to make themselves undetectable. We must first understand the characteristics and behavior of various varieties of ransomware to create and construct effective security mechanisms to combat them. This research presents a novel dynamic and behavioral …

Malware Binary Image Classification Using Convolutional Neural Networks, John Kiger, Shen-Shyang Ho, Vahid Heydari

College of Science & Mathematics Departmental Research

The persistent shortage of cybersecurity professionals combined with enterprise networks tasked with processing more data than ever before has led many cybersecurity experts to consider automating some of the most common and time-consuming security tasks using machine learning. One of these cybersecurity tasks where machine learning may prove advantageous is malware analysis and classification. To evade traditional detection techniques, malware developers are creating more complex malware. This is achieved through more advanced methods of code obfuscation and conducting more sophisticated attacks. This can make the manual process of analyzing malware an infinitely more complex task. Furthermore, the proliferation of malicious …

Performance Of Heterogeneous Multi-Agent Systems With Applications In Combined Arms, Robert J. Wilson

Theses and Dissertations

Multi-agent systems show great potential for solving problems in complex and dynamic domains. Such systems comprise multiple individual entities called agents. Agents possessing the same behavior or physical form are called homogeneous while agents which differ in these respects are termed heterogeneous. The overall behavior of the system emerges from the many interactions of its component agents. Most multi-agent systems research to date focuses on systems of homogeneous agents, but recent work suggests that heterogeneous agents may improve system performance in certain tasks. This research examines the impact of heterogeneity on multi-agent system effectiveness and investigates the application of multi-agent …

Team Air Combat Using Model-Based Reinforcement Learning, David A. Mottice

Theses and Dissertations

We formulate the first generalized air combat maneuvering problem (ACMP), called the MvN ACMP, wherein M friendly AUCAVs engage against N enemy AUCAVs, developing a Markov decision process (MDP) model to control the team of M Blue AUCAVs. The MDP model leverages a 5-degree-of-freedom aircraft state transition model and formulates a directed energy weapon capability. Instead, a model-based reinforcement learning approach is adopted wherein an approximate policy iteration algorithmic strategy is implemented to attain high-quality approximate policies relative to a high performing benchmark policy. The ADP algorithm utilizes a multi-layer neural network for the value function approximation regression mechanism. One-versus-one …

Carbon Estimation And Decision Making In Usaf Acquisition, Robert F. Gray

Theses and Dissertations

Recent executive orders and international agreements require the United States to significantly reduce its carbon and greenhouse gas emissions. The DoD is a significant contributor to the carbon emissions of the USA and will be required to reduce the emissions. Therefore, in order to make appropriate programmatic decisions the DoD needs to develop an appropriate method for estimating carbon and making programmatic decisions; trading-off carbon emissions with the traditional cost-schedule-performance metrics. This thesis examines the possibility of developing a model that can be used to estimate the carbon footprint of producing a system before detailed engineering designed have been complete.

Simulating Autonomous Cruise Missile Swarm Behaviors In An Anti-Access Area Denial (A2ad) Environment, Kyle W. Goggins

Theses and Dissertations

The increasingly sophisticated anti-access area denial (A2AD) threat imposed by the modern integrated air defense system (IADS), coupled with the decreasingly potent advantage provided by high-end stealth platforms, has prompted Air Force senior leaders to invest in radically changing the nature of air power for the year 2030 and beyond. A prominent element of this new vision is weapon swarming, which aims to address this challenge by overwhelming the IADS with huge numbers of low-cost, attritable aerial assets emboldened by autonomous capabilities. This research proposes a framework for classifying the different levels of autonomous capability along three independent dimensions—namely ability …

Telemetry Data Mining For Unmanned Aircraft Systems, Li Yu

Theses and Dissertations

With ever more data becoming available to the US Air Force, it is vital to develop effective methods to leverage this strategic asset. Machine learning (ML) techniques present a means of meeting this challenge, as these tools have demonstrated successful use in commercial applications. For this research, three ML methods were applied to a unmanned aircraft system (UAS) telemetry dataset with the aim of extracting useful insight related to phases of flight. It was shown that ML provides an advantage in exploratory data analysis and as well as classification of phases. Neural network models demonstrated the best performance with over …