Physical Sciences and Mathematics Commons^™

Fine-Grained Topic Models Using Anchor Words, Jeffrey A. Lund

Theses and Dissertations

Topic modeling is an effective tool for analyzing the thematic content of large collections of text. However, traditional probabilistic topic modeling is limited to a small number of topics (typically no more than hundreds). We introduce fine-grained topic models, which have large numbers of nuanced and specific topics. We demonstrate that fine-grained topic models enable use cases not currently possible with current topic modeling techniques, including an automatic cross-referencing task in which short passages of text are linked to other topically related passages. We do so by leveraging anchor methods, a recent class of topic model based on non-negative matrix …

Evaluating An Educational Cybersecurity Playable Case Study, Tanner West Johnson

Theses and Dissertations

The realities of cyberattacks have become more and more prevalent in the world today. Due to the growing number of these attacks, the need for highly trained individuals has also increased. Because of a shortage of qualified candidates for these positions, there is an increasing need for cybersecurity education within high schools and universities. In this thesis, I discuss the development and evaluation of Cybermatics, an educational simulation, or playable case study, designed to help students learn and develop skills within the cybersecurity discipline.

This playable case study was designed to allow students to gain an understanding of the field …

Designing Cybersecurity Competitions In The Cloud: A Framework And Feasibility Study, Chandler Ryan Newby

Theses and Dissertations

Cybersecurity is an ever-expanding field. In order to stay current, training, development, and constant learning are necessary. One of these training methods has historically been competitions. Cybersecurity competitions provide a method for competitors to experience firsthand cybersecurity concepts and situations. These experiences can help build interest in, and improve skills in, cybersecurity.

While there are diverse types of cybersecurity competitions, most are run with on-premise hardware, often centralized at a specific location, and are usually limited in scope by available hardware. This research focuses on the possibility of running cybersecurity competitions, specifically CCDC style competitions, in a public cloud environment. …

User Attitudes About Duo Two-Factor Authentication At Byu, Jonathan Dutson

Undergraduate Honors Theses

Simple password-based authentication provides insufficient protection against increasingly common incidents of online identity theft and data loss. Although two-factor authentication (2FA) provides users with increased protection against attackers, users have mixed feelings about the usability of 2FA. We surveyed the students, faculty, and staff of Brigham Young University (BYU) to measure user sentiment about DUO Security, the 2FA system adopted by BYU in 2017. We find that most users consider DUO to be annoying, and about half of those surveyed expressed a preference for authentication without using a second-factor. About half of all participants reported at least one instance of …

Improving The Quality Of Neural Machine Translation Using Terminology Injection, Duane K. Dougal

Theses and Dissertations

Most organizations use an increasing number of domain- or organization-specific words and phrases. A translation process, whether human or automated, must also be able to accurately and efficiently use these specific multilingual terminology collections. However, comparatively little has been done to explore the use of vetted terminology as an input to machine translation (MT) for improved results. In fact, no single established process currently exists to integrate terminology into MT as a general practice, and especially no established process for neural machine translation (NMT) exists to ensure that the translation of individual terms is consistent with an approved terminology collection. …

Flow Adaptive Video Object Segmentation, Fanqing Lin

Theses and Dissertations

We tackle the task of semi-supervised video object segmentation, i.e, pixel-level object classification of the images in video sequences using very limited ground truth training data of its corresponding video. Recently introduced online adaptation of convolutional neural networks for video object segmentation (OnAVOS) has achieved good results by pretraining the network, fine-tuning on the first frame and training the network at test time using its approximate prediction as newly obtained ground truth. We propose Flow Adaptive Video Object Segmentation (FAVOS) that refines the generated adaptive ground truth for online updates and utilizes temporal consistency between video frames with the help …

Security Analysis And Recommendations For Coniks As A Pki Solution For Mobile Apps, George Bradley Spendlove

Theses and Dissertations

Secure mobile apps, including end-to-end encrypted messaging apps such as Whats-App and Signal, are increasingly popular today. These apps require trust in a centralized key directory to automatically exchange the public keys used to secure user communication. This trust may be abused by malicious, subpoenaed, or compromised directories. A public key infrastructure (PKI) solution that requires less trust would increase the security of these commonly used apps.CONIKS is a recent PKI proposal that features transparent key directories which publish auditable digests of the public keys they present to queriers. By monitoring its key every time a new digest is published, …

Toward Real-Time Flip Fluid Simulation Through Machine Learning Approximations, Javid Kennon Pack

Theses and Dissertations

Fluids in computer generated imagery can add an impressive amount of realism to a scene, but are particularly time-consuming to simulate. In an attempt to run fluid simulations in real-time, recent efforts have attempted to simulate fluids by using machine learning techniques to approximate the movement of fluids. We explore utilizing machine learning to simulate fluids while also integrating the Fluid-Implicit-Particle (FLIP) simulation method into machine learning fluid simulation approaches.

Usable Security And Privacy For Secure Messaging Applications, Elham Vaziripour

Theses and Dissertations

The threat of government and corporate surveillance around the world, as well as the publicity surrounding major cybersecurity attacks, have increased interest in secure and private end-to-end communications. In response to this demand, numerous secure messaging applications have been developed in recent years. These applications have been welcomed and publically used not just by political activists and journalists but by everyday users as well. Most of these popular secure messaging applications are usable because they hide many of the details of how encryption is provided. The strength of the security properties of these applications relies on the authentication ceremony, wherein …

Netlight: Cloud Baked Indirect Illumination, Nathan Andrew Zabriskie

Theses and Dissertations

Indirect lighting drastically increases the realism of rendered scenes but it has traditionally been very expensive to calculate. This has long precluded its use in real-time rendering applications such as video games which have mere milliseconds to respond to user input and produce a final image. As hardware power continues to increase, however, some recently developed algorithms have started to bring real-time indirect lighting closer to reality. Of specific interest to this paper, cloud-based rendering systems add indirect lighting to real-time scenes by splitting the rendering pipeline between a server and one or more connected clients. However, thus far they …

Certificate Revocation Table: Leveraging Locality Of Reference In Web Requests To Improve Tls Certificate Revocation, Luke Austin Dickinson

Theses and Dissertations

X.509 certificate revocation defends against man-in-the-middle attacks involving a compromised certificate. Certificate revocation strategies face scalability, effectiveness, and deployment challenges as HTTPS adoption rates have soared. We propose Certificate Revocation Table (CRT), a new revocation strategy that is competitive with or exceeds alternative state-of-the-art solutions in effectiveness, efficiency, certificate growth scalability, mass revocation event scalability, revocation timeliness, privacy, and deployment requirements. The CRT periodically checks the revocation status of X.509 certificates recently used by an organization, such as clients on a university's private network. By prechecking the revocation status of each certificate the client is likely to use, the client …

Fully Convolutional Neural Networks For Pixel Classification In Historical Document Images, Seth Andrew Stewart

Theses and Dissertations

We use a Fully Convolutional Neural Network (FCNN) to classify pixels in historical document images, enabling the extraction of high-quality, pixel-precise and semantically consistent layers of masked content. We also analyze a dataset of hand-labeled historical form images of unprecedented detail and complexity. The semantic categories we consider in this new dataset include handwriting, machine-printed text, dotted and solid lines, and stamps. Segmentation of document images into distinct layers allows handwriting, machine print, and other content to be processed and recognized discriminatively, and therefore more intelligently than might be possible with content-unaware methods. We show that an efficient FCNN with …

A Quantitative Study Of The Deployment Of The Sender Policy Framework, Eunice Zsu Tan

Theses and Dissertations

Email has become a standard form of communication between businesses. With the prevalent use of email as a form of communication between businesses and customers, phishing emails have emerged as a popular social engineering approach. With phishing, attackers trick users into divulging their personal information through email spoofing. Thus, it is imperative to verify the sender of an email. Anti-spoofing mechanisms such as the Sender Policy Framework (SPF) have been developed as the first line of defense against spoofing by validating the source of an email as well as the presenting options of how to handle emails that fail to …

An Algorithm For Symbolic Computing Of Singular Limits Of Dynamical Systems, Dane Jordan Bjork

Theses and Dissertations

The manifold boundary approximation method, MBAM is a new technique used in approximating systems of equations using parameter reduction. This method and other approximation methods are introduced and described. Several current issues in performing MBAM are discussed in further detail. These issues significantly slow down the process of MBAM and create a barrier of entry for those wishing to use the method without a strong background in mathematics. A solution is proposed to automatically reparameterize models and evaluate specific types of variables approaching limits -- significantly speeding up the process of MBAM. An implementation of the solution is discussed.

Machine Learning For Inspired, Structured, Lyrical Music Composition, Paul Mark Bodily

Theses and Dissertations

Computational creativity has been called the "final frontier" of artificial intelligence due to the difficulty inherent in defining and implementing creativity in computational systems. Despite this difficulty computer creativity is becoming a more significant part of our everyday lives, in particular music. This is observed in the prevalence of music recommendation systems, co-creational music software packages, smart playlists, and procedurally-generated video games. Significant progress can be seen in the advances in industrial applications such as Spotify, Pandora, Apple Music, etc., but several problems persist. Of more general interest, however, is the question of whether or not computers can exhibit autonomous …

Evaluating The Usability Of Two-Factor Authentication, Kendall Ray Reese

Theses and Dissertations

Passwords are the dominant form of authentication on the web today. However,many users choose weak passwords and reuse the same password on multiple sites, thus increasing their vulnerability to having their credentials leaked or stolen. Two-factor authentication strengthens existing password authentication schemes against impersonation attacks and makes it more difficult for attackers to reuse stolen credentials on other websites. Despite the added security benefits of two-factor authentication, there are still many open questions about its usability. Many two-factor authentication systems in widespread usage today have not yet been subjected to adequate usability testing. Previous comparative studies have demonstrated significant differences …

Probabilistic Programming For Theory Of Mind For Autonomous Decision Making, Iris Rubi Seaman

Theses and Dissertations

As autonomous agents (such as unmanned aerial vehicles, or UAVs) become more ubiquitous, they are being used for increasingly complex tasks. Eventually, they will have to reason about the mental state of other agents, including those agents' beliefs, desires and goals – so-called Theory of Mind – and make decisions based on that reasoning. We describe increasingly complex theory of mind models of a UAV pursuing an intruder, and show that (1) there is a natural Bayesian formulation to reasoning about the uncertainty inherent in our estimate of another agent's mental state, and that (2) probabilistic programming is a natural …

Signal Structure For A Class Of Nonlinear Dynamic Systems, Meilan Jin

Theses and Dissertations

The signal structure is a partial structure representation for dynamic systems. It characterizes the causal relationship between manifest variables and is depicted in a weighted graph, where the weights are dynamic operators. Earlier work has defined signal structure for linear time-invariant systems through dynamical structure function. This thesis focuses on the search for the signal structure of nonlinear systems and proves that the signal structure reduces to the linear definition when the systems are linear. Specifically, this work: (1) Defines the complete computational structure for nonlinear systems. (2) Provides a process to find the complete computational structure given a state …

Adaptive Fluid Simulation Using A Linear Octree Structure, Sean A. Flynn

Theses and Dissertations

An Eulerian approach to fluid flow provides an efficient, stable paradigm for realistic fluid simulation. However, its traditional reliance on a fixed-resolution grid is not ideal for simulations that simultaneously exhibit both large and small-scale fluid phenomena. Octree-based fluid simulation approaches have provided the needed adaptivity, but the inherent weakness of a pointer-based tree structure has limited their effectiveness. We present a linear octree structure that provides a significant runtime speedup using these octree-based simulation algorithms. As memory prices continue to decline, we leverage additional memory when compared to traditional octree structures to provide this improvement. In addition to reducing …

Subword Spotting And Its Applications, Brian Lafayette Davis

Theses and Dissertations

We propose subword spotting, a generalization of word spotting where the search is for groups of characters within words. We present a method for performing subword spotting based on state-of-the-art word spotting techniques and evaluate its performance at three granularitires (unigrams, bigrams and trigrams) on two datasets. We demonstrate three applications of subword spotting, though others may exist. The first is assisting human transcribers identify unrecognized characters by locating them in other words. The second is searching for suffixes directly in word images (suffix spotting). And the third is computer assisted transcription (semi-automated transcription). We investigate several variations of computer …

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. …

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 …