Computer Sciences Commons^™

Assured Android Execution Environments, Brandon P. Froberg

Theses and Dissertations

Current cybersecurity best practices, techniques, tactics and procedures are insufficient to ensure the protection of Android systems. Software tools leveraging formal methods use mathematical means to assure both a design and implementation for a system and these methods can be used to provide security assurances. The goal of this research is to determine methods of assuring isolation when executing Android software in a contained environment. Specifically, this research demonstrates security properties relevant to Android software containers can be formally captured and validated, and that an implementation can be formally verified to satisfy a corresponding specification. A three-stage methodology called "The …

Mitigating The Effects Of Boom Occlusion On Automated Aerial Refueling Through Shadow Volumes, Zachary C. Paulson

Theses and Dissertations

In flight refueling of Unmanned Aerial Vehicles (UAVs) is critical to the United States Air Force (USAF). However, the large communication latency between a ground-based operator and his/her remote UAV makes docking with a refueling tanker unsafe. This latency may be mitigated by leveraging a tanker-centric stereo vision system. The vision system observes and computes an approaching receiver's relative position and orientation offering a low-latency, high frequency docking solution. Unfortunately, the boom -- an articulated refueling arm responsible for physically pumping fuel into the receiver -- occludes large portions of the receiver especially as the receiver approaches and docks with …

Stereo Vision: A Comparison Of Synthetic Imagery Vs. Real World Imagery For The Automated Aerial Refueling Problem, Nicholas J. Seydel

Theses and Dissertations

Missions using unmanned aerial vehicles have increased in the past decade. Currently, there is no way to refuel these aircraft. Accomplishing automated aerial refueling can be made possible using the stereo vision system on a tanker. Real world experiments for the automated aerial refueling problem are expensive and time consuming. Currently, simulations performed in a virtual world have shown promising results using computer vision. It is possible to use the virtual world as a substitute environment for the real world. This research compares the performance of stereo vision algorithms on synthetic and real world imagery.

The Application Of Text Mining And Data Visualization Techniques To Textual Corpus Exploration, Jeffrey R. Smith Jr.

Theses and Dissertations

Unstructured data in the digital universe is growing rapidly and shows no evidence of slowing anytime soon. With the acceleration of growth in digital data being generated and stored on the World Wide Web, the prospect of information overload is much more prevalent now than it has been in the past. As a preemptive analytic measure, organizations across many industries have begun implementing text mining techniques to analyze such large sources of unstructured data. Utilizing various text mining techniques such as n -gram analysis, document and term frequency analysis, correlation analysis, and topic modeling methodologies, this research seeks to develop …

Variable Speed Simulation For Accelerated Industrial Control System Cyber Training, Luke M. Bradford

Theses and Dissertations

It is important for industrial control system operators to receive quality training to defend against cyber attacks. Hands-on training exercises with real-world control systems allow operators to learn various defensive techniques and see the real-world impact of changes made to a control system. Cyber attacks and operator actions can have unforeseen effects that take a significant amount of time to manifest and potentially cause physical harm to the system, making high-fidelity training exercises time-consuming and costly. This thesis presents a method for accelerating training exercises by simulating and predicting the effects of a cyber event on a partially-simulated control system. …

Securing Critical Infrastructure: A Ransomware Study, Blaine M. Jeffries

Theses and Dissertations

This thesis reviews traditional ransomware attack trends in order to present a taxonomy for ransomware targeting industrial control systems. After reviewing a critical infrastructure ransomware attack methodology, a corresponding response and recovery plan is described. The plan emphasizes security through redundancy, specifically the incorporation of standby programmable logic controllers. This thesis goes on to describe a set of experiments conducted to test the viability of defending against a specialized ransomware attack with a redundant controller network. Results support that specific redundancy schemes are effective in recovering from a successful attack. Further experimentation is conducted to test the feasibility of industrial …

Assessment Of Structure From Motion For Reconnaissance Augmentation And Bandwidth Usage Reduction, Jonathan B. Roeber

Theses and Dissertations

Modern militaries rely upon remote image sensors for real-time intelligence. A typical remote system consists of an unmanned aerial vehicle, or UAV, with an attached camera. A video stream is sent from the UAV, through a bandwidth-constrained satellite connection, to an intelligence processing unit. In this research, an upgrade to this method of collection is proposed. A set of synthetic images of a scene captured by a UAV in a virtual environment is sent to a pipeline of computer vision algorithms, collectively known as Structure from Motion. The output of Structure from Motion, a three-dimensional model, is then assessed in …

Assessing And Expanding Extracurricular Cybersecurity Youth Activities' Impact On Career Interest, Michael H. Dunn

Theses and Dissertations

This thesis assesses and expands the potential of extracurricular activities to address the shortage of cybersecurity workers by increasing secondary school students’ interest in these careers. Competitions and badges, two forms of gamification often applied in extracurricular educational activities, have potential to improve motivation and increase interest in related careers, but are significantly understudied in the context of cybersecurity activities. CyberPatriot is the largest cybersecurity competition in the United States for secondary school students. Impact on participants’ career interests is assessed by analyzing responses to recent surveys conducted by the competition organizers. Analysis demonstrates significantly increased interest in cybersecurity in …

An Analysis Of Multi-Domain Command And Control And The Development Of Software Solutions Through Devops Toolsets And Practices, Mason R. Bruza

Theses and Dissertations

Multi-Domain Command and Control (MDC2) is the exercise of command and control over forces in multiple operational domains (namely air, land, sea, space, and cyberspace) in order to produce synergistic effects in the battlespace, and enhancing this capability has become a major focus area for the United States Air Force (USAF). In order to meet demands for MDC2 software, solutions need to be acquired and/or developed in a timely manner, information technology infrastructure needs to be adaptable to new software requirements, and user feedback needs to drive iterative updates to fielded software. In commercial organizations, agile software development methodologies and …

Quality Of Service Impacts Of A Moving Target Defense With Software-Defined Networking, Samuel A. Mayer

Theses and Dissertations

An analysis of the impact a defensive network technique implemented with software-defined networking has upon quality of service experienced by legitimate users. The research validates previous work conducted at AFIT to verify claims of defensive efficacy and then tests network protocols in common use (FTP, HTTP, IMAP, POP, RTP, SMTP, and SSH) on a network that uses this technique. Metrics that indicate the performance of the protocols under test are reported with respect to data gathered in a control network. The conclusions of these experiments enable network engineers to determine if this defensive technique is appropriate for the quality of …

Expected Coverage (Excov): A Proposal To Compare Fuzz Test Coverage Within An Infinite Input Space, Evan V. Swihart

Theses and Dissertations

A Fuzz test is an approach used to discover vulnerabilities by intentionally sending invalid inputs to a system for the purpose of triggering some type of fault or unintended effect that renders the system vulnerable to an exploit. Fuzz testing is an important cyber-testing technique used to find and fix vulnerabilities before they are exploited. The fuzzing of military data links presents a particular challenge because existing fuzzing tools cannot be easily applied to these systems. As a result, the tools and techniques used to fuzz these links vary widely in sophistication and effectiveness. Because of the infinite, or nearly …

Securing Data In Transit Using Two Channel Communication, Clark L. Wolfe

Theses and Dissertations

Securing data in transit is critically important to the Department of Defense in todays contested environments. While encryption is often the preferred method to provide security, there exist applications for which encryption is too resource intensive, not cost-effective or simply not available. In this thesis, a two-channel communication system is proposed in which the message being sent can be intelligently and dynamically split over two or more channels to provide a measure of data security either when encryption is not available, or perhaps in addition to encryption. This data spiting technique employs multiple wireless channels operating at the physical layer, …

A Large-Scale Analysis Of How Openssl Is Used In Open-Source Software, Scott Jared Heidbrink

Theses and Dissertations

As vulnerabilities become more common the security of applications are coming under increased scrutiny. In regards to Internet security, recent work discovers that many vulnerabilities are caused by TLS library misuse. This misuse is attributed to large and confusing APIs and developer misunderstanding of security generally. Due to these problems there is a desire for simplified TLS libraries and security handling. However, as of yet there is no analysis of how the existing APIs are used, beyond how incorrect usage motivates the need to replace them. We provide an analysis of contemporary usage of OpenSSL across 410 popular secure applications. …

Target Detection Using Convolutional Neural Networks, Robert P. Loibl

Theses and Dissertations

This research explores the use of Convolutional Neural Networks (CNNs) to classify targets of interest within satellite imagery. Methods were specifically devised for the classification of airports within Landsat-8 scenes. A novel automated dataset generation technique was developed to create labeled datasets from satellite imagery using only coordinate metadata. Using this approach a very large dataset of over 132,000 labeled images was created without human input. This dataset was used to evaluate the effects of color and resolution on airport classification accuracy. Two experiments were run with the first experiment classifying large airports with 96.8% accuracy, and the second classifying …

Developing A Cyberterrorism Policy: Incorporating Individual Values, Osama Bassam J. Rabie

Theses and Dissertations

Preventing cyberterrorism is becoming a necessity for individuals, organizations, and governments. However, current policies focus on technical and managerial aspects without asking for experts and non-experts values and preferences for preventing cyberterrorism. This study employs value focused thinking and public value forum to bare strategic measures and alternatives for complex policy decisions for preventing cyberterrorism. The strategic measures and alternatives are per socio-technical process.

Optimization For Structural Equation Modeling: Applications To Substance Use Disorders, Mahsa Zahery

Theses and Dissertations

Substance abuse is a serious issue in both modern and traditional societies. Besides health complications such as depression, cancer and HIV, social complications such as loss of concentration, loss of job, and legal problems are among the numerous hazards substance use disorder imposes on societies. Understanding the causes of substance abuse and preventing its negative effects continues to be the focus of much research.

Substance use behaviors, symptoms and signs are usually measured in form of ordinal data, which are often modeled under threshold models in Structural Equation Modeling (SEM). In this dissertation, we have developed a general nonlinear optimizer …

.Net Core Kundrejt Express Js Si Framework Për Zhvillim Modern Të Web - It, Rrezon Hasani

Theses and Dissertations

Ky punim ka për qëllim të identifikoj avantazhet dhe disavantazhet e Asp.Net Core kundrejt Express js, si dhe ndryshimet dhe qasjet që kanë këta dy frameworks për zhvillim modern të web –it. Pikat ku do të krahasohen Asp.Net Core dhe Express js janë: Instalimi, Ekosistemi dhe Performanca, Komuniteti i Zhvilluesve dhe Forumet për këta frameworks. Mënyrat e krahasimit janë bërë nepërmjet zhvillimit, testimit, demonstrimit të kodit si dhe statistikave të marra nga Interneti. Rezultatet e këtijë punimi do të ndihmojnë zhvilluesit në përzgjedhjen e frameworkut ndërmjet Asp.Net Core dhe Express js në projektet e tyre në bazë të krahasimeve që …

Implementation Costs Of Spiking Versus Rate-Based Anns, Lacie Renee Stiffler

Theses and Dissertations

Artificial neural networks are an effective machine learning technique for a variety of data sets and domains, but exploiting the inherent parallelism in neural networks requires specialized hardware. Typically, computing the output of each neuron requires many multiplications, evaluation of a transcendental activation function, and transfer of its output to a large number of other neurons. These restrictions become more expensive when internal values are represented with increasingly higher data precision. A spiking neural network eliminates the limitations of typical rate-based neural networks by reducing neuron output and synapse weights to one-bit values, eliminating hardware multipliers, and simplifying the activation …

Improving Speech-Related Facial Action Unit Recognition By Audiovisual Information Fusion, Zibo Meng

Theses and Dissertations

In spite of great progress achieved on posed facial display and controlled image acquisition, performance of facial action unit (AU) recognition degrades significantly for spontaneous facial displays. Furthermore, recognizing AUs accompanied with speech is even more challenging since they are generally activated at a low intensity with subtle facial appearance/geometrical changes during speech, and more importantly, often introduce ambiguity in detecting other co-occurring AUs, e.g., producing non-additive appearance changes. All the current AU recognition systems utilized information extracted only from visual channel. However, sound is highly correlated with visual channel in human communications. Thus, we propose to exploit both audio …

Smartphone User Privacy Preserving Through Crowdsourcing, Bahman Rashidi

Theses and Dissertations

In current Android architecture, users have to decide whether an app is safe to use or not. Expert users can make savvy decisions to avoid unnecessary private data breach. However, the majority of regular users are not technically capable or do not care to consider privacy implications to make safe decisions. To assist the technically incapable crowd, we propose a permission control framework based on crowdsourcing. At its core, our framework runs new apps under probation mode without granting their permission requests up-front. It provides recommendations on whether to accept or not the permission requests based on decisions from peer …

Uncertainty Estimation Of Deep Neural Networks, Chao Chen

Theses and Dissertations

Normal neural networks trained with gradient descent and back-propagation have received great success in various applications. On one hand, point estimation of the network weights is prone to over-fitting problems and lacks important uncertainty information associated with the estimation. On the other hand, exact Bayesian neural network methods are intractable and non-applicable for real-world applications. To date, approximate methods have been actively under development for Bayesian neural networks, including but not limited to: stochastic variational methods, Monte Carlo dropouts, and expectation propagation. Though these methods are applicable for current large networks, there are limits to these approaches with either underestimation …

Authenticating Users With 3d Passwords Captured By Motion Sensors, Jing Tian

Theses and Dissertations

Authentication plays a key role in securing various resources including corporate facilities or electronic assets. As the most used authentication scheme, knowledgebased authentication is easy to use but its security is bounded by how much a user can remember. Biometrics-based authentication requires no memorization but ‘resetting’ a biometric password may not always be possible. Thus, we propose study several behavioral biometrics (i.e., mid-air gestures) for authentication which does not have the same privacy or availability concerns as of physiological biometrics.

In this dissertation, we first propose a user-friendly authentication system Kin- Write that allows users to choose arbitrary, short and …

Suggesting Missing Information In Text Documents, Grant Michael Hodgson

Theses and Dissertations

A key part of contract drafting involves thinking of issues that have not been addressedand adding language that will address the missing issues. To assist attorneys with this task, we present a pipeline approach for identifying missing information within a contract section. The pipeline takes a contract section as input and includes 1) identifying sections that are similar to the input section from a corpus of contract sections; and 2) identifying and suggesting information from the similar sections that are missing from the input section. By taking advantage of sentence embedding and principal component analysis, this approach suggests sentences that …

Machine Learning Based Disease Gene Identification And Mhc Immune Protein-Peptide Binding Prediction, Zhonghao Liu

Theses and Dissertations

Machine learning and deep learning methods have been increasingly applied to solve challenging and important bioinformatics problems such as protein structure prediction, disease gene identification, and drug discovery. However, the performances of existing machine learning based predictive models are still not satisfactory. The question of how to exploit the specific properties of bioinformatics data and couple them with the unique capabilities of the learning algorithms remains elusive. In this dissertation, we propose advanced machine learning and deep learning algorithms to address two important problems: mislocation-related cancer gene identification and major histocompatibility complex-peptide binding affinity prediction. Our first contribution proposes a …

Phylogeny, Ancestral Genome, And Disease Diagnoses Models Constructions Using Biological Data, Bing Feng

Theses and Dissertations

Studies of bioinformatics develop methods and software tools to analyze the biological data and provide insight of the mechanisms of biological process. Machine learning techniques have been widely used by researchers for disease prediction, disease diagnosis, and bio-marker identification. Using machine-learning algorithms to diagnose diseases has a couple of advantages. Besides solely relying on the doctors’ experiences and stereotyped formulas, researchers could use learning algorithms to analyze sophisticated, high-dimensional and multimodal biomedical data, and construct prediction/classification models to make decisions even when some information was incomplete, unknown, or contradictory. In this study, first of all, we built an automated computational …

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, …

Estimating The Respiratory Lung Motion Model Using Tensor Decomposition On Displacement Vector Field, Kingston Kang

Theses and Dissertations

Modern big data often emerge as tensors. Standard statistical methods are inadequate to deal with datasets of large volume, high dimensionality, and complex structure. Therefore, it is important to develop algorithms such as low-rank tensor decomposition for data compression, dimensionality reduction, and approximation.

With the advancement in technology, high-dimensional images are becoming ubiquitous in the medical field. In lung radiation therapy, the respiratory motion of the lung introduces variabilities during treatment as the tumor inside the lung is moving, which brings challenges to the precise delivery of radiation to the tumor. Several approaches to quantifying this uncertainty propose using a …

A Behavior-Driven Recommendation System For Stack Overflow Posts, Chase D. Greco

Theses and Dissertations

Developers are often tasked with maintaining complex systems. Regardless of prior experience, there will inevitably be times in which they must interact with parts of the system with which they are unfamiliar. In such cases, recommendation systems may serve as a valuable tool to assist the developer in implementing a solution. Many recommendation systems in software engineering utilize the Stack Overflow knowledge-base as the basis of forming their recommendations. Traditionally, these systems have relied on the developer to explicitly invoke them, typically in the form of specifying a query. However, there may be cases in which the developer is in …

Consuming Digital Debris In The Plasticene, Stephen R. Parks

Theses and Dissertations

Claims of customization and control by socio-technical industries are altering the role of consumer and producer. These narratives are often misleading attempts to engage consumers with new forms of technology. By addressing capitalist intent, material, and the reproduction limits of 3-D printed objects’, I observe the aspirational promise of becoming a producer of my own belongings through new networks of production. I am interested in gaining a better understanding of the data consumed that perpetuates hyper-consumptive tendencies for new technological apparatuses. My role as a designer focuses on the resolution of not only the surface of the object through 3-D …

Big Networks: Analysis And Optimal Control, Hung The Nguyen

Theses and Dissertations

The study of networks has seen a tremendous breed of researches due to the explosive spectrum of practical problems that involve networks as the access point. Those problems widely range from detecting functionally correlated proteins in biology to finding people to give discounts and gain maximum popularity of a product in economics. Thus, understanding and further being able to manipulate/control the development and evolution of the networks become critical tasks for network scientists. Despite the vast research effort putting towards these studies, the present state-of-the-arts largely either lack of high quality solutions or require excessive amount of time in real-world …