Physical Sciences and Mathematics Commons^™

An Analysis Of Significant Cyber Incidents And The Impact On The Past, Present, And Future, Seth E. Smith

Cybersecurity Undergraduate Research Showcase

This report discusses data collected on significant cybersecurity incidents from the early 2000s to present. The first part of the report addresses previously discussed information, data, and literature (e.g. case studies), pertinent to cybersecurity incidents. The findings from this study are framed by scholarly sources and information from the Federal Bureau of Investigation, a number of notable universities, and literature online, of which all support information discussed within this report. The second part of the report discusses data compiled upon analyzing significant cyber incidents and events from the Center for Strategic and International Affairs (CSIS). Finally, the last portion of …

Joint Linear And Nonlinear Computation With Data Encryption For Efficient Privacy-Preserving Deep Learning, Qiao Zhang

Electrical & Computer Engineering Theses & Dissertations

Deep Learning (DL) has shown unrivalled performance in many applications such as image classification, speech recognition, anomalous detection, and business analytics. While end users and enterprises own enormous data, DL talents and computing power are mostly gathered in technology giants having cloud servers. Thus, data owners, i.e., the clients, are motivated to outsource their data, along with computationally-intensive tasks, to the server in order to leverage the server’s abundant computation resources and DL talents for developing cost-effective DL solutions. However, trust is required between the server and the client to finish the computation tasks (e.g., conducting inference for the newly-input …

Data-Driven Operational And Safety Analysis Of Emerging Shared Electric Scooter Systems, Qingyu Ma

Computational Modeling & Simulation Engineering Theses & Dissertations

The rapid rise of shared electric scooter (E-Scooter) systems offers many urban areas a new micro-mobility solution. The portable and flexible characteristics have made E-Scooters a competitive mode for short-distance trips. Compared to other modes such as bikes, E-Scooters allow riders to freely ride on different facilities such as streets, sidewalks, and bike lanes. However, sharing lanes with vehicles and other users tends to cause safety issues for riding E-Scooters. Conventional methods are often not applicable for analyzing such safety issues because well-archived historical crash records are not commonly available for emerging E-Scooters.

Perceiving the growth of such a micro-mobility …

Analytical Approach To Biometric Security And How It Affects Privacy, Torré A. Williams

Cybersecurity Undergraduate Research Showcase

In this time where the world is using technology every day, there is going to be a need for some type of security to take place to protect its citizens from unwanted harm or danger. The use of any authentication methods is becoming very essential for a lot of companies and even for your own personal belongings. The use of biometric technology has offered companies the chance to upgrade their security system. This has also provided easier ways that people authenticate themselves as who they say they are. Due to their growth of usage, there is a privacy and security …

The Maritime Domain Awareness Center– A Human-Centered Design Approach, Gary Gomez

Political Science & Geography Faculty Publications

This paper contends that Maritime Domain Awareness Center (MDAC) design should be a holistic approach integrating established knowledge about human factors, decision making, cognitive tasks, complexity science, and human information interaction. The design effort should not be primarily a technology effort that focuses on computer screens, information feeds, display technologies, or user interfaces. The existence of a room with access to vast amounts of information and wall-to-wall video screens of ships, aircraft, weather data, and other regional information does not necessarily correlate to possessing situation awareness. Fundamental principles of human-centered information design should guide MDAC design and technology selection, and …

Developing An International Framework For Addressing Non-State Actors In Cyberspace, Joanna C. Di Scipio

Cybersecurity Undergraduate Research Showcase

On May 7, 2021, Colonial Pipeline shut down its operations following a ransomware attack by the criminal group DarkSide (Bordoff, 2021). It took five days to resume normal operations, but this short period led to panic buying, rising prices, and significant gas shortages. The attack underscores an emerging threat in the landscape of cybersecurity: critical infrastructure attacks carried out by non-state actors.

Internet Of Things: Cybersecurity In Small Businesses, Zobair Wali

Cybersecurity Undergraduate Research Showcase

Small businesses are the most vital part of a nation’s economy. In today’s world, as we are moving towards digitizing almost everything around us, cybersecurity is essential and vital for our digitalized world to function. Small businesses are no exception. All businesses collect, use, and store information. They store employees’ information, tax information, customers’ information, business transaction information, and all other operational information that is needed for a business to function. Without an appropriate cybersecurity program, these businesses are vulnerable and can be easily impacted by cyber incidents and malicious attacks. Businesses are putting resources to protect their systems against …

Gdpr, Pipl & Lgpd: Privacy Regulations & Policies Across The Globe, Raymond H. Geistel

Cybersecurity Undergraduate Research Showcase

Several privacy laws around the world are adopting similar regulations to the GPDR; this has effects on privacy policies of companies providing services in across multiple countries & continents. While these regulations share many attributes, their differing requirements can make things difficult for companies regarding said policies. Automation could be a potential solution to both analyze and compare regulations from different nations & international organizations, analyze and monitor privacy policy adherence to said regulations.

How Secure Are Android And Apple’S Operating Systems And Based Applications Against Cyber Attacks And Cyber Crime, Marlowe Cosby Jr.

Cybersecurity Undergraduate Research Showcase

Smartphone has become an important part of our everyday life. Android and apple are the two most used operating system (OS) for smart phones. We usually store important information in our smart phone, e.g.: credit card, bank account, driving ID, SSN. As a result, Android and Apple operating systems and applications have both been subject to a wide number of vulnerabilities and attacks. This directly effects many people being that they are the global leaders of users within their platforms reaching billions of people daily. It is important that smartphones receive better defense and security. In this paper, we aim …

Self-Supervised Perceptual Ad-Blocker, Killian Robinson

Cybersecurity Undergraduate Research Showcase

This project proposes a new self-supervised ad-blocker to minimize the amount of human effort required to effectively combat pushed advertisements. Current ad-blocker models are expensive to develop and not always effective in identifying advertisements. We investigated the possibility of solving these problems with the introduction of a deep learning, self-supervised ad-blocker model. More specifically, the proposed ad-blocker will be trained in a self-supervised fashion to tackle the issue of lacking labelled training data. The proposed solution was prototyped using Pytorch and achieved a detection accuracy of 81% on a diverse selection of popular websites.

Protection Of Patient Privacy On Mobile Device Machine Learning, Matthew Nguyen

Cybersecurity Undergraduate Research Showcase

An existing StudentLife Study mobile dataset was evaluated and organized to be applied to different machine learning methods. Different variables like user activity, exercise, sleep, study space, social, and stress levels are optimized to train a model that could predict user stress level. The different machine learning methods would test if both patient data privacy and training efficiency can be ensured.

Cybersecurity Maturity Model Certification (Cmmc) Compliance For Dod Contractors, Sierra Burnett

Cybersecurity Undergraduate Research Showcase

The DoD is currently taking a supply-chain risk management strategy to foster cybersecurity. This unique strategy is often referred to as CMMC which stands for “Cybersecurity Maturity Model Certification”. The approach requires that all the 300,000 DoD contractors acquire third-party authentication that may attain the requirements for the CMMC maturity level suitable to the work they desire to do for the DoD. CMMC typically examines the organization's capability to safeguard Federal Contract Information as well as CUI. It integrates various cybersecurity standards already in place and plots the best practices alongside processes to five maturity levels that range from the …

Effects Of Cloud Computing In The Workforce, Kevin Rossi Acosta

Cybersecurity Undergraduate Research Showcase

In recent years, the incorporation of cloud computing and cloud services has increased in many different types of organizations and companies. This paper will focus on the philosophical, economical, and political factors that cloud computing and cloud services have in the workforce and different organizations. Based on various scholarly articles and resources it was observed that organizations used cloud computing and cloud services to increase their overall productivity as well as decrease the overall cost of their operations, as well as the different policies that were created by lawmakers to control the realm of cloud computing. The results of this …

A Look Into Increasing The Number Of Veterans And Former Government Employees Converting To Career And Technical Cybersecurity Teachers, Vukica M. Jovanovic, Michael Anthony Crespo, Drew E. Brown, Deborah Marshall, Otilia Popescu, Murat Kuzlu, Petros J. Katsioloudis, Linda Vahala

Engineering Technology Faculty Publications

The current state of technology with recent explosions in the digital processing of paperwork, computer networking use, and online and virtual approaches to areas, which until very recently had traditional and non-computerized ways of operating, led to a steady increase in the demand for jobs in the area of computer science and cybersecurity. The education system, the pipeline for the incoming workforce, needs to keep up with this tremendous pace in technology and the job market. The current K-12 school system has been extensively challenged to fill out necessary positions in order to address the increasing need for programs that …

State Antifragility: An Agent-Based Modeling Approach To Understanding State Behavior, Rebecca Lee Law

Graduate Program in International Studies Theses & Dissertations

This dissertation takes an interdisciplinary approach to understanding what makes states antifragile and why this matters by constructing a parsimonious, first of its kind agent-based model. The model focuses on the key elements of state antifragility that reside along a spectrum of fragility and transverse bidirectionally from fragile to resilient to antifragile given a certain set of environmental conditions.

First coined by Nicholas Nassim Taleb and applied to economics, antifragility is a nascent concept. In 2015, Nassim Taleb and Gregory Treverton’s article in Foreign Affairs outlined five characteristics of state antifragility. This project aims to advance the study of anti-fragility …

A Digital One Degree Of Freedom Model Of An Electromagnetic Position Sensor, Michelle Elizabeth Weinmann

Mechanical & Aerospace Engineering Theses & Dissertations

The purpose of this project was to improve an existing system currently in use by NASA Langley Research Center (LaRC). The 6-inch Magnetic Suspension and Balance System (MSBS) built at MIT is operational with control in three degrees of freedom, with two additional degrees of freedom exhibiting passive stability. The means for measuring model displacement within the magnetic environment is an Electromagnetic Position Sensor (EPS), consisting of excitation coils at 20 kHz and multiple sets of pickup coils. The pickup coil voltages are proportional to model displacement in each degree of freedom. However, the EPS electronic signal processing system is …

Move: Mobile Observers Variants And Extensions, Ryan Florin

Computer Science Theses & Dissertations

Traffic state estimation is a fundamental task of Intelligent Transportation Systems. Recent advances in sensor technology and emerging computer and vehicular communications paradigms have brought the task of estimating traffic state parameters in real-time within reach.

This has led to the main research question of this thesis: Can a vehicle accurately estimate traffic parameters using onboard resources shared through CV technology in a lightweight manner without utilizing centralized or roadside infrastructure?

In 1954 Wardrop and Charlesworth proposed the Moving Observer method to measure traffic parameters based on an observed number of vehicle passes. We start by proposing methods for detecting …

Deep Learning Approaches For Seagrass Detection In Multispectral Imagery, Kazi Aminul Islam

Electrical & Computer Engineering Theses & Dissertations

Seagrass forms the basis for critically important marine ecosystems. Seagrass is an important factor to balance marine ecological systems, and it is of great interest to monitor its distribution in different parts of the world. Remote sensing imagery is considered as an effective data modality based on which seagrass monitoring and quantification can be performed remotely. Traditionally, researchers utilized multispectral satellite images to map seagrass manually. Automatic machine learning techniques, especially deep learning algorithms, recently achieved state-of-the-art performances in many computer vision applications. This dissertation presents a set of deep learning models for seagrass detection in multispectral satellite images. It …

Improving Collection Understanding For Web Archives With Storytelling: Shining Light Into Dark And Stormy Archives, Shawn M. Jones

Computer Science Theses & Dissertations

Collections are the tools that people use to make sense of an ever-increasing number of archived web pages. As collections themselves grow, we need tools to make sense of them. Tools that work on the general web, like search engines, are not a good fit for these collections because search engines do not currently represent multiple document versions well. Web archive collections are vast, some containing hundreds of thousands of documents. Thousands of collections exist, many of which cover the same topic. Few collections include standardized metadata. Too many documents from too many collections with insufficient metadata makes collection understanding …

Methods For Detecting Floodwater On Roadways From Ground Level Images, Cem Sazara

Computational Modeling & Simulation Engineering Theses & Dissertations

Recent research and statistics show that the frequency of flooding in the world has been increasing and impacting flood-prone communities severely. This natural disaster causes significant damages to human life and properties, inundates roads, overwhelms drainage systems, and disrupts essential services and economic activities. The focus of this dissertation is to use machine learning methods to automatically detect floodwater in images from ground level in support of the frequently impacted communities. The ground level images can be retrieved from multiple sources, including the ones that are taken by mobile phone cameras as communities record the state of their flooded streets. …

Quantifying Cyber Risk By Integrating Attack Graph And Impact Graph, Omer F. Keskin

Engineering Management & Systems Engineering Theses & Dissertations

Being a relatively new risk source, models to quantify cyber risks are not well developed; therefore, cyber risk management in most businesses depends on qualitative assessments. With the increase in the economic consequences of cyber incidents, the importance of quantifying cyber risks has increased. Cyber risk quantification is also needed to establish communication among decision-makers of different levels of an enterprise, from technical personnel to top management.

The goal of this research is to build a probabilistic cybersecurity risk analysis model that relates attack propagation with impact propagation through internal dependencies and allows temporal analysis.

The contributions of the developed …

A Unified Framework For Parallel Anisotropic Mesh Adaptation, Christos Tsolakis

Computer Science Theses & Dissertations

Finite-element methods are a critical component of the design and analysis procedures of many (bio-)engineering applications. Mesh adaptation is one of the most crucial components since it discretizes the physics of the application at a relatively low cost to the solver. Highly scalable parallel mesh adaptation methods for High-Performance Computing (HPC) are essential to meet the ever-growing demand for higher fidelity simulations. Moreover, the continuous growth of the complexity of the HPC systems requires a systematic approach to exploit their full potential. Anisotropic mesh adaptation captures features of the solution at multiple scales while, minimizing the required number of elements. …

Sql Injection & Web Application Security: A Python-Based Network Traffic Detection Model, Nyki Anderson

Cybersecurity Undergraduate Research Showcase

The Internet of Things (IoT) presents a great many challenges in cybersecurity as the world grows more and more digitally dependent. Personally identifiable information (PII) (i,e., names, addresses, emails, credit card numbers) is stored in databases across websites the world over. The greatest threat to privacy, according to the Open Worldwide Application Security Project (OWASP) is SQL injection attacks (SQLIA) [1]. In these sorts of attacks, hackers use malicious statements entered into forms, search bars, and other browser input mediums to trick the web application server into divulging database assets. A proposed technique against such exploitation is convolution neural network …

Vaim For Solving Inverse Problems, Manal Almaeen, Yasir Alanazi, Michelle Kuchera, Nobuo Sato, Wally Melnitchouk, Yaohang Li

College of Sciences Posters

In this work, we propose the Variational Autoencoder Inverse Mapper (VAIM) to solve inverse problems, where there is a demand to accurately restore hidden parameters from indirect observations. VAIM is an autoencoder-based neural network architecture. The encoder and decoder networks approximate the forward and backward mapping, respectively, and a variational latent layer is incorporated into VAIM to learn the posterior parameter distributions with respect to the given observables. VAIM shows promising results on several artificial inverse problems. VAIM further demonstrates preliminary effectiveness in constructing the inverse function mapping quantum correlation functions to observables in a quantum chromodynamics analysis of nucleon …

Cybersecurity Legislation And Ransomware Attacks In The United States, 2015-2019, Joseph Skertic

Graduate Program in International Studies Theses & Dissertations

Ransomware has rapidly emerged as a cyber threat which costs the global economy billions of dollars a year. Since 2015, ransomware criminals have increasingly targeted state and local government institutions. These institutions provide critical infrastructure – e.g., emergency services, water, and tax collection – yet they often operate using outdated technology due to limited budgets. This vulnerability makes state and local institutions prime targets for ransomware attacks. Many states have begun to realize the growing threat from ransomware and other cyber threats and have responded through legislative action. When and how is this legislation effective in preventing ransomware attacks? This …

Data-Limited Domain Adaptation And Transfer Learning For Learning Latent Expression Labels Of Child Facial Expression Images, Megan Witherow, Winston Shields, Manar Samad, Khan Iftekharuddin

College of Engineering & Technology (Batten) Posters

While state-of-the-art deep learning models have demonstrated success in adult facial expression classification by leveraging large, labeled datasets, labeled data for child facial expression classification is limited. Due to differences in facial morphology and development in child and adult faces, deep learning models trained on adult data do not generalize well to child data. Recent deep domain adaptation approaches have improved the generalizability of models trained on a source domain to a target domain with few labeled samples. We propose that incorporating steps of deep transfer learning, e.g. weights initialization from the pre-trained source model and freezing model layers, may …

Analysis Of Reading Patterns Of Scientific Literature Using Eye-Tracking Measures, Gavindya Jayawardena, Sampath Jayarathna, Jian Wu

College of Sciences Posters

Scientific literature is crucial for researchers to inspire novel research ideas and find solutions to various problems. This study presents a reading task for novice researchers using eye-tracking measures. The study focused on the scan paths, fixation, and pupil dilation frequency of the participants. In this study, 3 participants were asked to read a pre-selected research paper while wearing an eye-tracking device (PupilLabs Core 200Hz). We specified sections of the research paper as areas of interest (title, abstract, motivation, methodology, conclusion)to analyze the eye-movements. Then we extracted eye-movements data from the recordings and processed them using an eye-movement processing pipeline. …

Multi-Dimensional Numerical Integration On Parallel Architectures, Ioannis Sakiotis, Marc Paterno, Balsa Terzic, Mohammad Zubair, Desh Ranjan

College of Sciences Posters

Multi-dimensional numerical integration is a challenging computational problem that is encountered in many scientific computing applications. Despite extensive research and the development of efficient techniques such as adaptive and Monte Carlo methods, many complex high-dimensional integrands can be too computationally intense even for state-of-the-art numerical libraries such as CUBA, QUADPACK, NAG, and MSL. However, adaptive integration has few dependencies and is very well suited for parallel architectures where processors can operate on different partitions of the integration-space. While existing parallel methods exist, most are simple extensions of their sequential versions. This results in moderate speedup and in many cases failure …

Nanopore Guided Regional Assembly, Eleni Adam, Desh Ranjan, Harold Riethman

College of Sciences Posters

The telomeres are the “caps” of the chromosomes and their vital role is to protect them. Possible telomere dysfunction caused by telomere rearrangements can be fatal for the cell and result in age-related diseases, including cancer. The telomeres and subtelomeres are regions that are hard to investigate. The current technology cannot provide their complete sequence, instead the DNA is given in multiple pieces. Current methods of assembling the pieces of these regions are not accurate enough due to the region’s high variability and complex repeated patterns. We propose a hybrid assembly method, the NPGREAT, which utilizes two of the latest …

Combine Cryo-Em Density Map And Residue Contact For Protein Structure Prediction: A Case Study, Maytha Alshammari, Jing He

College of Sciences Posters

Although atomic structures have been determined directly from cryo-EM density maps with high resolutions, current structure determination methods for medium resolution (5 to 10 Å) cryo-EM maps are limited by the availability of structure templates. Secondary structure traces are lines detected from a cryo-EM density map for α-helices and β-strands of a protein. A topology of secondary structures defines the mapping between a set of sequence segments in 1D and a set of traces of secondary structures in 3D. In order to enhance the accuracy in ranking secondary structure topologies, we propose a method that combines three sources of information …