Other Computer Sciences Commons^™

Smart Homes And You: Iot Device Data Risks In An Ever-Changing World, Autumn Person

Theses and Dissertations

Social media applications are increasingly seen as a national security threat and a cause for concern because they can be used to create user profiles on government personnel and on US citizens. These profiles could be used for big data and artificial intelligence purposes of interest to foreign governments. With the rise of big data and AI being used, foreign governments could use this data for a variety of purposes that can affect normal everyday citizens, not just high value personnel. IoT (Internet of Things) devices that the population uses everyday can also pose the same threat. These devices can …

Docker Technology For Small Scenario-Based Excercises In Cybersecurity, Zeinab Ahmed

Theses and Dissertations

This study aims to better prepare students for cybersecurity roles by providing practical tools that bridge the gap between theory and real-world applications. We investigate the role of small scenario-based exercises for students’ understanding of cybersecurity concepts. In particular, we assess the use of Docker technology to deliver training that includes a simple small scenario on html code injection. The effectiveness of scenario-based learning has long been defined and by using SBL, we are going to create hands-on activity that involves the fundamental topics in cybersecurity using Docker technology, allowing students to see the exploitation of the vulnerabilities and defense …

A Multimodal Immune System Inspired Defense Architecture For Detecting And Deterring Digital Pathogens In Container Hosted Web Services, Islam Khalil

Theses and Dissertations

With the increased use of web technologies, microservices, and Application Programming Interface (API) for integration between systems, and with the development of containerization of services on operating system level as a method of isolating system execution and for easing the deployment and scaling of systems, there is a growing need as well as opportunities for providing platforms that improve the security of such services. In our work, we propose an architecture for a containerization platform that utilizes various concepts derived from the human immune system. The goal of the proposed containerization platform is to introduce the concept of slowing down …

Material Extrusion-Based Additive Manufacturing: G-Code And Firmware Attacks And Defense Frameworks, Haris Rais

Theses and Dissertations

Additive Manufacturing (AM) refers to a group of manufacturing processes that create physical objects by sequentially depositing thin layers. AM enables highly customized production with minimal material wastage, rapid and inexpensive prototyping, and the production of complex assemblies as single parts in smaller production facilities. These features make AM an essential component of Industry 4.0 or Smart Manufacturing. It is now used to print functional components for aircraft, rocket engines, automobiles, medical implants, and more. However, the increased popularity of AM also raises concerns about cybersecurity. Researchers have demonstrated strength degradation attacks on printed objects by injecting cavities in the …

X-Ray Vision At Action Space Distances: Depth Perception In Context, Nate Phillips

Theses and Dissertations

Accurate and usable x-ray vision has long been a goal in augmented reality (AR) research and development. X-ray vision, or the ability to comprehend location and object information when such is viewed through an opaque barrier, would be imminently useful in a variety of contexts, including industrial, disaster reconnaissance, and tactical applications. In order for x-ray vision to be a useful tool for many of these applications, it would need to extend operators’ perceptual awareness of the task or environment. The effectiveness with which x-ray vision can do this is of significant research interest and is a determinant of …

Abm Simulation Model Of A Pandemic For Optimizing Vaccination Strategy, Gibeom Park

Theses and Dissertations

This study presents a process-oriented hybrid model for individuals' immune responses and interactions involving vaccination to describe the trend of contagious disease and estimate the future societal cost. The model considers "recovery" as a non-absorbing state and incorporates various infection stage states including two symptomatic states. To model contagiousness to be consistent with the current pandemic and include that the spread of a disease depends on the mobility of people, we developed an Agent-Based Simulator that fitted to the particular model used in this study and can test various what-if scenarios. We improved the simulator considerably by appying data structures …

Developing A Model Of Driver Performance, Situation Awareness, And Cognitive Load Considering Different Levels Of Partial Vehicle Autonomy, Jessie E. Cossitt

Theses and Dissertations

To fully utilize the abilities of current autonomous vehicles, it is necessary to understand the interactions between vehicles and their operators. Since the current state of the art of autonomous vehicles is partial autonomy that requires operators to perform parts of the driving task and be alert and ready to take over full control of the vehicle, it is necessary to know how operators' abilities are impacted by the amount of autonomy present in the system. Autonomous systems have known effects on performance, cognitive load, and situation awareness, but little is known about how these effects change in relation to …

A Longitudinal Analysis Of Pathways To Computing Careers: Defining Broadening Participation In Computing (Bpc) Success With A Rearview Lens, Mercy Jaiyeola

Theses and Dissertations

Efforts to increase the participation of groups historically underrepresented in computing studies, and in the computing workforce, are well documented. It is a national effort with funding from a variety of sources being allocated to research in broadening participation in computing (BPC). Many of the BPC efforts are funded by the National Science Foundation (NSF) but as existing literature shows, the growth in representation of traditionally underrepresented minorities and women is not commensurate to the efforts and resources that have been directed toward this aim.

Instead of attempting to tackle the barriers to increasing representation, this dissertation research tackles the …

Error Detection In Quantum Algorithms, Simeon R. Hanks

Theses and Dissertations

Quantum computers need to be able to control highly entangled quantum states in the presence of environmental perturbations that lead to errors in calculations. Progress in superconducting qubits has enabled the development of computers capable of running small quantum circuits. The current era of Noise Intermediate Scale Quantum computing has a high error rate. To alleviate this error rate we apply an encoding scheme that allows us to remove results with known errors improving the quality of our results. The encoding uses multiple qubits as a single logical qubit and balances the natural tendency of state-of-the-art quantum computers to decohere …

Pseudo-Data Generation For Improving Clinical Named Entity Recognition, Jeffrey T. Smith

Theses and Dissertations

One of the primary challenges for clinical Named Entity Recognition (NER) is the availability of annotated training data. Technical and legal hurdles prevent the creation and release of corpora related to electronic health records (EHRs). In this work, we look at the imapct of pseudo-data generation on clinical NER using gazetteering and thresholding utilizing a neural network model. We report that gazetteers can result in the inclusion of proper terms with the exclusion of determiners and pronouns in preceding and middle positions. Gazetteers that had higher numbers of terms inclusive to the original dataset had a higher impact. We also …

Sparsity And Weak Supervision In Quantum Machine Learning, Seyran Saeedi

Theses and Dissertations

Quantum computing is an interdisciplinary field at the intersection of computer science, mathematics, and physics that studies information processing tasks on a quantum computer. A quantum computer is a device whose operations are governed by the laws of quantum mechanics. As building quantum computers is nearing the era of commercialization and quantum supremacy, it is essential to think of potential applications that we might benefit from. Among many applications of quantum computation, one of the emerging fields is quantum machine learning. We focus on predictive models for binary classification and variants of Support Vector Machines that we expect to be …

Non-Contact Height Estimation For Material Extrusion Additive Systems Via Monocular Imagery, Andrew C. Gorospe

Theses and Dissertations

Additive manufacturing is a dynamic technology with a compelling potential to advance the manufacturing industry. Despite its capacity to produce intricate designs in an efficient manner, industry still has not widely adopted additive manufacturing since its commercialization as a result of its many challenges related to quality control. The Air Force Research Laboratory (AFRL), Materials and Manufacturing Directorate, Functional Materials Division, Soft Matter Materials Branch (RXAS) requires a practical and reliable method for maintaining quality control for the production of printed flexible electronics. Height estimation is a crucial component for maintaining quality control in Material Extrusion Additive Manufacturing (MEAM), as …

Indirect Relatedness, Evaluation, And Visualization For Literature Based Discovery, Sam Henry

Theses and Dissertations

The exponential growth of scientific literature is creating an increased need for systems to process and assimilate knowledge contained within text. Literature Based Discovery (LBD) is a well established field that seeks to synthesize new knowledge from existing literature, but it has remained primarily in the theoretical realm rather than in real-world application. This lack of real-world adoption is due in part to the difficulty of LBD, but also due to several solvable problems present in LBD today. Of these problems, the ones in most critical need of improvement are: (1) the over-generation of knowledge by LBD systems, (2) a …

Novel Support Vector Machines For Diverse Learning Paradigms, Gabriella A. Melki

Theses and Dissertations

This dissertation introduces novel support vector machines (SVM) for the following traditional and non-traditional learning paradigms: Online classification, Multi-Target Regression, Multiple-Instance classification, and Data Stream classification.

Three multi-target support vector regression (SVR) models are first presented. The first involves building independent, single-target SVR models for each target. The second builds an ensemble of randomly chained models using the first single-target method as a base model. The third calculates the targets' correlations and forms a maximum correlation chain, which is used to build a single chained SVR model, improving the model's prediction performance, while reducing computational complexity.

Under the multi-instance paradigm, …

Multi-Plc Exercise Environments For Training Ics First Responders, Joseph K. Daoud

Theses and Dissertations

When systems are targeted by cyber attacks, cyber first responders must be able to react effectively, especially when dealing with critical infrastructure. Training for cyber first responders is lacking and most existing exercise platforms are expensive, inaccessible or ineffective. This paper presents a mobile training platform which incorporates a variety of programmable logic controllers into a single system which facilitates the development of the unique skills required of cyber first responders operating in the realm of industrial control systems. The platform is modeled after a jail in the northeastern United States and was developed to maximize realism. Example training scenarios …

Big Data Visualization Platform For Mixed Reality, Aliakbar Panahi

Theses and Dissertations

The visualization of data helps to provide faster and deeper insight into the data. In this work, a system for visualizing and analyzing big data in an interactive mixed reality environment is proposed. Such a system can be used for representing different types of data such as temporal, geospatial, network graph, and high dimensional. Also, an implementation of this system for four different data types are created. The data types include network data, volumetric data, high dimensional, and spectral data for different mixed reality devices such as Microsoft HoloLens, Oculus Rift, Samsung Gear VR, and Android ARCore were created. It …

Network Analytics For The Mirna Regulome And Mirna-Disease Interactions, Joseph Jayakar Nalluri

Theses and Dissertations

miRNAs are non-coding RNAs of approx. 22 nucleotides in length that inhibit gene expression at the post-transcriptional level. By virtue of this gene regulation mechanism, miRNAs play a critical role in several biological processes and patho-physiological conditions, including cancers. miRNA behavior is a result of a multi-level complex interaction network involving miRNA-mRNA, TF-miRNA-gene, and miRNA-chemical interactions; hence the precise patterns through which a miRNA regulates a certain disease(s) are still elusive. Herein, I have developed an integrative genomics methods/pipeline to (i) build a miRNA regulomics and data analytics repository, (ii) create/model these interactions into networks and use optimization techniques, motif …

Position And Volume Estimation Of Atmospheric Nuclear Detonations From Video Reconstruction, Daniel T. Schmitt

Theses and Dissertations

Recent work in digitizing films of foundational atmospheric nuclear detonations from the 1950s provides an opportunity to perform deeper analysis on these historical tests. This work leverages multi-view geometry and computer vision techniques to provide an automated means to perform three-dimensional analysis of the blasts for several points in time. The accomplishment of this requires careful alignment of the films in time, detection of features in the images, matching of features, and multi-view reconstruction. Sub-explosion features can be detected with a 67% hit rate and 22% false alarm rate. Hotspot features can be detected with a 71.95% hit rate, 86.03% …

Mobile Indoor Positioning For Augmented Reality Systems, Robert B. Glass

Theses and Dissertations

This thesis explores the creation and setup of a prototype that allows users of the device to interact within an indoor real world environment and a virtual environment simultaneously using high-tech common technology. The prototype is comprised of a small mobile device such as a cellular mobile phone, Raspberry Pi computer, a battery powered handheld Pico projector, and software developed for the Android OS. The software can easily be ported to other mobile and non-mobile operating systems. The mobile device must contain accelerometer, magnetometer, and gyroscope embedded sensors as well as 802.11 wireless network chip. The prototype software implements an …

Android Protection System: A Signed Code Security Mechanism For Smartphone Applications, Jonathan D. Stueckle

Theses and Dissertations

This research develops the Android Protection System (APS), a hardware-implemented application security mechanism on Android smartphones. APS uses a hash-based white-list approach to protect mobile devices from unapproved application execution. Functional testing confirms this implementation allows approved content to execute on the mobile device while blocking unapproved content. Performance benchmarking shows system overhead during application installation increases linearly as the application package size increases. APS presents no noticeable performance degradation during application execution. The security mechanism degrades system performance only during application installation, when users expect delay. APS is implemented within the default Android application installation process. Applications are hashed …

Performance Of Scattering Matrix Decomposition And Color Spaces For Synthetic Aperture Radar Imagery, Manuel E. Arriagada

Theses and Dissertations

Polarimetrc Synthetic Aperture Radar (SAR) has been shown to be a powerful tool in remote sensing because uses up to four simultaneous measurements giving additional degrees of freedom for processing. Typically, polarization decomposition techniques are applied to the polarization-dependent data to form colorful imagery that is easy for operators systems to interpret. Yet, the presumption is that the SAR system operates with maximum bandwidth which requires extensive processing for near- or real-time application. In this research, color space selection is investigated when processing sparse polarimetric SAR data as in the case of the publicly available \Gotcha Volumetric SAR Data Set, …

Range Estimation Algorithm Comparison In 3-D Flash Ladar Data, Steven P. Jordan

Theses and Dissertations

Range estimation algorithms have been applied to Laser Detection and Ranging (LADAR) data to test for accuracy and precision. Data was acquired from Matlab® simulations and an experiment using the Advanced Scientific Concepts 3-D flash LADAR camera. Simulated LADAR data was based on a Gaussian pulse shape model with Poisson noise added. Simulations were performed to test range estimation algorithm performance with respect to waveform position within the range gate. The effectiveness of each algorithm is presented in terms of its average root mean square error and standard deviation in 1000 trials. The measured data experiment examined the effectiveness of …

A Hybrid Templated-Based Composite Classification System, Michael A. Turnbaugh

Theses and Dissertations

An automatic target classification system contains a classifier which reads a feature as an input and outputs a class label. Typically, the feature is a vector of real numbers. Other features can be non-numeric, such as a string of symbols or alphabets. One method of improving the performance of an automatic classification system is through combining two or more independent classifiers that are complementary in nature. Complementary classifiers are observed by finding an optimal method for partitioning the problem space. For example, the individual classifiers may operate to identify specific objects. Another method may be to use classifiers that operate …

Solving The Protein Structure Prediction Problem With Fast Messy Genetic Algorithms (Scaling The Fast Messy Genetic Algorithm To Medium-Sized Peptides By Detecting Secondary Structures), Steven R. Michaud

Theses and Dissertations

The ability to accurately predict a polypeptide's molecular structure given its amino acid sequence is important to numerous scientific, medical, and engineering applications. Studies have been conducted in the application of Genetic Algorithms (GAs) to this problem with promising initial results. In this thesis report, we use the fast messy Genetic Algorithm (fmGA) to attempt to find the minimization of an empirical CHARMM energy model and generation of the associated conformation. Previous work has shown that the fmGA provided favorable results, at least when applied to the pentapeptide Met-Enkephalin. We extend these results to a larger Polyalinine peptide by utilizing …

Extensible Markup Language As A Weather Tool, Michael J. Calidonna

Theses and Dissertations

This thesis is a proof of concept work that will extend the Core Mapping Application Program Interface (CMAPI) components to include weather data. The CMAPI project is headed by Air Force Research Lab (AFRL)/Information Directorate Information Handling Branch (IFEB) at Rome labs in Rome, New York. This work extends the CMAPI project in two distinct areas. The first goal is to figure out how to overlay and display weather data on a dynamically linked Internet platform. This was accomplished by incorporating existing data from the Air Force Weather Agency (AFWA) into the CMAPI program in a static environment. The other …