Computer Sciences Commons^™

On-Focus : A Web-Based Platform For Planning, Organizing, And Managing Focus Groups, Nnamdi Chuka-Maduji

Theses, Dissertations and Culminating Projects

Focus groups are a research methodology that researchers use to get qualitative data about a subject matter or a product. Owing to the Covid outbreak in 2019 and the prevalence of group think in focus groups, a web-based platform called On-Focus was developed as a means for researchers to organize and manage focus groups online.

On-Focus was developed by following the recommended design approach for conducting focus groups found in literatures. With On-Focus, researchers can filter out participants that are not a fit for the focus group by asking questions that are filled by participants before they send a request …

Facial Recognition And Face Mask Detection Using Machine Learning Techniques, Mira M. Boulos

Theses, Dissertations and Culminating Projects

Facial recognition, as a biometric system, is a crucial tool for the identification procedures. When using facial recognition, an individual's identity is identified using their unique facial features. Biometric authentication system helps in identifying individuals using their physiological and behavioral features. Physiological biometrics utilize human features such as faces, irises, and fingerprints. In contrast, behavioral biometric rely on features that humans do, such as voice and handwritings. Facial recognition has been widely used for security and other law enforcement purposes. However, since COVID-19 pandemic, many people around the world had to wear face masks. This thesis introduces a neural network …

Time Of Flight And Fingerprinting Based Methods For Wireless Rogue Device Detection, Daniel Chege

Theses, Dissertations and Culminating Projects

Existing network detection techniques rely on SSIDs, network patterns or MAC addresses of genuine wireless devices to identify malicious attacks on the network. However, these device characteristics can be manipulated posing a security threat to information integrity, lowering detection accuracy, and weakening device protection. This research study focuses on empirical analysis to elaborate the relationship between received signal strength (RSSI) and distance; investigates methods to detect rogue devices and access points on Wi-Fi networks using network traffic analysis and fingerprint identification methods. In this paper, we conducted three experiments to evaluate the performance of RSSI and clock skews as features …

Detecting Bots Using A Hybrid Approach, Edmund Kofi Genfi

Theses, Dissertations and Culminating Projects

Artificial intelligence (AI) remains a crucial aspect for improving our modern lives but it also casts several social and ethical issues. One issue is of major concern, investigated in this research, is the amount of content users consume that is being generated by a form of AI known as bots (automated software programs). With the rise of social bots and the spread of fake news more research is required to understand how much content generated by bots is being consumed. This research investigates the amount of bot generated content relating to COVID-19. While research continues to uncover the extent to …

Fast And Secure Friend Recommendation In Online Social Networks, Raiyan Hossain

Theses, Dissertations and Culminating Projects

Online Social Networks have completely transformed communication in the world of social networks. Participation in online social networks have been growing significantly and is expected to continue to grow in the upcoming years. As user participation in online social media is on the rise, so is the concern pertaining to user privacy and information security; users want to interact on social media without jeopardizing their privacy and personal information. Extensive research has been conducted in the area of developing privacy-preserving protocols to allow users to interact in a secure and privacy-preserving environment. One of the elements that social media have …

Towards Secure And Verifiable Computation Of Knn Queries In Outsourced Environments, Gowri Pandian Sundarapandi

Theses, Dissertations and Culminating Projects

The popularity of cloud computing has increased significantly in the last few years due to scalability, cost efficiency, resiliency, and quality of service. Organizations are more interested in outsourcing the database and DBMS functionalities to the cloud owing to the tremendous growth of big data and on-demand access requirements. As the data is outsourced to untrusted parties, security has become a key consideration to achieve the confidentiality and integrity of data. Therefore, data owners must transform and encrypt the data before outsourcing. In this paper, we focus on a Secure and Verifiable Computation for k-Nearest Neighbor (SVC-kNN) problem. The existing …

Mining Subgroups From Temporal Data : From The Parts To The Whole, Alexander Gorovits

Legacy Theses & Dissertations (2009 - 2024)

A variety of dynamic systems can be broken down into potentially overlapping subcomponents with varying temporal behavior, ranging from communities in networks, to clusters of trajectories in spatiotemporal data, to co-evolving subsets within multivariate time series. Using explicit regularization on various temporal behaviors within a tensor factorizationframework, I demonstrate means to mine these subgroups along with their temporal activities, as well as how that yields information about the overall systems. Additionally, I adapt this notion of temporal communities to the spatiotemporal setting to develop a reinforcement learning approach for optimizing co-ordinated communication between independent agents.

How The Growth Of Technology Has Forced Accounting Firms To Put An Emphasis On Cybersecurity, Holden Halbach

Accounting Undergraduate Honors Theses

The advancement of technology has brought many changes to accounting firms. Computer applications such as Microsoft Excel have made calculators and physical spreadsheets obsolete. Then with the introduction of cloud computing employees can store, access, and exchange large amounts of data instantaneously from any location. These technological innovations have increased the accuracy and efficiency of firms substantially. However, this growth in technology has shown the importance of putting an emphasis on cybersecurity throughout the accounting industry. The emphasis placed on cybersecurity throughout accounting firms is more prevalent than any other industry. This is primarily because accounting firms not only deal …

Security Fatigue And Its Effects On Perceived Password Strength Among University Students, Chase Carroll

Honors Theses

This study was performed with the goal of observing the effect, if any, that security fatigue has on students’ perceived strength of passwords. In doing so, it was hoped to find some correlation between the two that would help in establishing a measurable effect of the phenomenon in students. This could potentially aid organizational decision-makers, such as security policy writers and system admins, to make more informed decisions about implementing security measures. To achieve the goal of observing this fatigue and attempting to measure it, a survey was distributed to numerous students on the University of Tennessee at Chattanooga campus. …

Simplifying The Creation Of Virtual Topologies Using Mpi Sessions, Tom Herschberg

Honors Theses

As supercomputers have approached exascale performance, several scalability issues have emerged within MPI. These issues arise because MPI includes all processes in the World model, which consumes unacceptable amounts of time and resources at large scale. The Sessions model was developed to combat these issues by removing the requirement of MPI_COMM_WORLD, which provides a more scalable method of creating communication groups in large jobs. Additionally, the Sessions model enables the creation of virtual topologies directly from sets of processes allocated to the execution of a parallel application rather than building virtual topologies from an existing communication group such as MPI_COMM_WORLD. …

Ground Truth: Towards Labeling On-Demand Iot Traffic, Daniel Jordan Campos

Theses and Dissertations

A lack of transparency has accompanied the rapid proliferation of Internet of Things (IoT) devices. To this end, a growing body of work exists to classify IoT device traffic to identify unexpected or surreptitious device activity. However, this work requires fine-grained labeled datasets of device activity. This paper proposes a holistic approach for IoT device traffic collection and automated event labeling. Our work paves the way for future research by thoroughly examining different techniques for synthesizing and labeling on-demand traffic from IoT sensors and actuators. To demonstrate this approach, we instrumented a smart home environment consisting of 57 IoT devices …

Brave New World Reboot: Technology’S Role In Consumer Manipulation And Implications For Privacy And Transparency, Allie Mertensotto

Marketing Undergraduate Honors Theses

Most consumers are aware that our data is being obtained and collected through the use of our devices we keep in our homes or even on our person throughout the day. But, it is understated how much data is being collected. Conversations you have with your peers – in a close proximity of a device – are being used to tailor advertising. The advertisements you receive on your devices are uniquely catered to your individual person, due to the fact it consistently uses our data to produce efficient and personal ads. On the flip side, our government is also tapping …

Cross Domain Iw Threats To Sof Maritime Missions: Implications For U.S. Sof, Gary C. Kessler, Diane M. Zorri

Publications

As cyber vulnerabilities proliferate with the expansion of connected devices, wherein security is often forsaken for ease of use, Special Operations Forces (SOF) cannot escape the obvious, massive risk that they are assuming by incorporating emerging technologies into their toolkits. This is especially true in the maritime sector where SOF operates nearshore in littoral zones. As SOF—in support to the U.S. Navy— increasingly operate in these contested maritime environments, they will gradually encounter more hostile actors looking to exploit digital vulnerabilities. As such, this monograph comes at a perfect time as the world becomes more interconnected but also more vulnerable.

The Effect Of User Interface, User Experience And Design On Mobile E-Commerce Applications In The Fashion Industry, Debra Perlman

Honors College Theses

This study aims to explore elements of the user experience, and how those with the user interface and design of mobile apps in the e-commerce and fashion industries affect the user experience and customer behavior with online shopping. In this area, other work has been done in evaluating the user experience, and its effects on components of the user interface and design, however, this study offers a more specific look into these features in a niche industry, namely in the frame of e-commerce and the fashion industry. This fits into the context of the field of the user experience as …

A Framework To Detect The Susceptibility Of Employees To Social Engineering Attacks, Hashim H. Alneami

Doctoral Dissertations and Master's Theses

Social engineering attacks (SE-attacks) in enterprises are hastily growing and are becoming increasingly sophisticated. Generally, SE-attacks involve the psychological manipulation of employees into revealing confidential and valuable company data to cybercriminals. The ramifications could bring devastating financial and irreparable reputation loss to the companies. Because SE-attacks involve a human element, preventing these attacks can be tricky and challenging and has become a topic of interest for many researchers and security experts. While methods exist for detecting SE-attacks, our literature review of existing methods identified many crucial factors such as the national cultural, organizational, and personality traits of employees that enable …

Dynamic Task Allocation In Partially Defined Environments Using A* With Bounded Costs, James Hendrickson

Doctoral Dissertations and Master's Theses

The sector of maritime robotics has seen a boom in operations in areas such as surveying and mapping, clean-up, inspections, search and rescue, law enforcement, and national defense. As this sector has continued to grow, there has been an increased need for single unmanned systems to be able to undertake more complex and greater numbers of tasks. As the maritime domain can be particularly difficult for autonomous vehicles to operate in due to the partially defined nature of the environment, it is crucial that a method exists which is capable of dynamically accomplishing tasks within this operational domain. By considering …

Evolving Efficient Floor Plans For Hospital Emergency Rooms, Alex Ramsey

Theses/Capstones/Creative Projects

Genetic Algorithms find wide use in optimization problems across many fields of research, including crowd simulation. This paper proposes that genetic algorithms could be used to create better floor plans for hospital emergency rooms, potentially saving critical time in high risk situations. The genetic algorithm implemented makes use of a hospital-specific crowd simulation to accurately evaluate the effectiveness of produced layouts. The results of combining genetic algorithms with a crowd simulation are promising. Future work may improve upon these results to produce better, more optimal hospital floor plans.

Visual Analysis Of Historical Lessons Learned During Exercises For The United States Air Force Europe (Usafe), Samantha O'Rourke

Theses/Capstones/Creative Projects

Within the United States Air Force, there are repeated patterns of differences observed during exercises. After an exercise is completed, forms are filled out detailing observations, successes, and recommendations seen throughout the exercise. At the most, no two reports are identical and must be analyzed by personnel and then categorized based on common themes observed. Developing a computer application will greatly reduce the time and resources used to analyze each After Action Report. This application can visually represent these observations and optimize the effectiveness of these exercises. The visualization is done through graphs displaying the frequency of observations and recommendations. …

Autonomous Aerial Vehicle Vision And Sensor Guided Landing, Gabriel Bitencourt, Elijah J. Brown, Cedric Bleimling, Gilbert Lai, Arman Molki, Tolga Kaya

School of Computer Science & Engineering Faculty Publications

The use of autonomous landing of aerial vehicles is increasing in demand. Applications of this ability can range from simple drone delivery to unmanned military missions. To be able to land at a spot identified by local information, such as a visual marker, creates an efficient and versatile solution. This allows for a more user/consumer friendly device overall. To achieve this goal the use of computer vision and an array of ranging sensors will be explored. In our approach we utilized an April Tag as our location identifier and point of reference. MATLAB/Simulink interface was used to develop the platform …

Achieving Differential Privacy And Fairness In Machine Learning, Depeng Xu

Graduate Theses and Dissertations

Machine learning algorithms are used to make decisions in various applications, such as recruiting, lending and policing. These algorithms rely on large amounts of sensitive individual information to work properly. Hence, there are sociological concerns about machine learning algorithms on matters like privacy and fairness. Currently, many studies only focus on protecting individual privacy or ensuring fairness of algorithms separately without taking consideration of their connection. However, there are new challenges arising in privacy preserving and fairness-aware machine learning. On one hand, there is fairness within the private model, i.e., how to meet both privacy and fairness requirements simultaneously in …

Network-Based Detection And Prevention System Against Dns-Based Attacks, Yasir Faraj Mohammed

Graduate Theses and Dissertations

Individuals and organizations rely on the Internet as an essential environment for personal or business transactions. However, individuals and organizations have been primary targets for attacks that steal sensitive data. Adversaries can use different approaches to hide their activities inside the compromised network and communicate covertly between the malicious servers and the victims. The domain name system (DNS) protocol is one of these approaches that adversaries use to transfer stolen data outside the organization's network using various forms of DNS tunneling attacks. The main reason for targeting the DNS protocol is because DNS is available in almost every network, ignored, …

Application Of Machine Learning Techniques To Forecast Harmful Algal Blooms In Gulf Of Mexico, Bala Tripura Sundari Yerrapothu

Master's Theses

The Harmful Algal Blooms (HABs) forecast is crucial for the mitigation of health hazards and to inform actions for the protection of ecosystems and fisheries in the Gulf of Mexico (GoM). For the sake of simplicity of our application we assume ocean color satellite imagery from the National Oceanic and Atmospheric Administration as a proxy for HABs.

In this study we use a deep neural network trained on the 2-Dimensional time series proxy data to provide a forecast of the HABs’ manifestations in the GoM.Our approach analyzes between both spatial and temporal features simultaneously. In addition, the network also helps …

A Deep Learning-Based Automatic Object Detection Method For Autonomous Driving Ships, Ojonoka Erika Atawodi

Master's Theses

An important feature of an Autonomous Surface Vehicles (ASV) is its capability of automatic object detection to avoid collisions, obstacles and navigate on their own.

Deep learning has made some significant headway in solving fundamental challenges associated with object detection and computer vision. With tremendous demand and advancement in the technologies associated with ASVs, a growing interest in applying deep learning techniques in handling challenges pertaining to autonomous ship driving has substantially increased over the years.

In this thesis, we study, design, and implement an object recognition framework that detects and recognizes objects found in the sea. We first curated …

Low-Power And Reconfigurable Asynchronous Asic Design Implementing Recurrent Neural Networks, Spencer Nelson

Graduate Theses and Dissertations

Artificial intelligence (AI) has experienced a tremendous surge in recent years, resulting in high demand for a wide array of implementations of algorithms in the field. With the rise of Internet-of-Things devices, the need for artificial intelligence algorithms implemented in hardware with tight design restrictions has become even more prevalent. In terms of low power and area, ASIC implementations have the best case. However, these implementations suffer from high non-recurring engineering costs, long time-to-market, and a complete lack of flexibility, which significantly hurts their appeal in an environment where time-to-market is so critical. The time-to-market gap can be shortened through …

Prediction, Recommendation And Group Analytics Models In The Domain Of Mashup Services And Cyber-Argumentation Platform, Md Mahfuzer Rahman

Graduate Theses and Dissertations

Mashup application development is becoming a widespread software development practice due to its appeal for a shorter application development period. Application developers usually use web APIs from different sources to create a new streamlined service and provide various features to end-users. This kind of practice saves time, ensures reliability, accuracy, and security in the developed applications. Mashup application developers integrate these available APIs into their applications. Still, they have to go through thousands of available web APIs and chose only a few appropriate ones for their application. Recommending relevant web APIs might help application developers in this situation. However, very …

On Utilizing Prunable Blockchains For Secure Message Dissemination In Vanets, Edgar Bowlin Iii`

Undergraduate Honors Theses

Blockchain's use in Vehicular Ad-Hoc Networks (VANETs) research demonstrates that the technology provides useful attributes to allow for the safe and secure operation of VANET applications. The growth of blockchain applications pose a threat to the efficient operation of the MANET-like environment found within VANETs. Floating Genesis Blocks (FGB) can be used to preserve the state of the blockchain up to a certain point, and allows for the safe pruning of the chain without information loss. The early work presented here demonstrates two pruning techniques and compares the effects of each blockchain through simulation measurement of the chain's space requirements. …

A Study On Formal Verification For Javascript Software, Zachary S. Rowland

Honors Theses

Information security is still a major problem for users of websites and hybrid mobile applications. While many apps and websites come with terms of service agreements between the developer and end user, there is no rigorous mechanism in place to ensure that these agreements are being followed. Formal methods can offer greater confidence that these policies are being followed, but there is currently no widely adopted tool that makes formal methods available for average consumers. After studying the current state-of-the-art in JavaScript policy enforcement and verification, this research proposes several new techniques for applying model checking to JavaScript that strikes …

Real-Time Motion Tracking Of Cognitive Baxter Robot Based On Differential Inverse Kinematics, Shaobo Li, Xingxing Zhang, Jing Yang, Qiang Bai, Jianjun Hu, Qisong Song, Zhiang Li

Faculty Publications

The tracking motion of the robot is realized based on a specific robot or relying on an expensive movement acquisition system. It has the problems of complex control procedures, lack of real-time performance, and difficulty in achieving secondary development. We propose a robot real-time tracking control method based on the control principle of differential inverse kinematics, which fuses the position and joint angle information of the robot’s actuators to realize the real-time estimation of the user’s movement during the tracking process. The motion coordinates of each joint of the robot are calculated and the coordinate conversion between man and machine …

Teachability And Interpretability In Reinforcement Learning, Jeevan Rajagopal

School of Computing: Dissertations, Theses, and Student Research

There have been many recent advancements in the field of reinforcement learning, starting from the Deep Q Network playing various Atari 2600 games all the way to Google Deempind's Alphastar playing competitively in the game StarCraft. However, as the field challenges more complex environments, the current methods of training models and understanding their decision making become less effective. Currently, the problem is partially dealt with by simply adding more resources, but the need for a better solution remains.

This thesis proposes a reinforcement learning framework where a teacher or entity with domain knowledge of the task to complete can assist …

“The Revolution Will Not Be Supervised": An Investigation Of The Efficacy And Reasoning Process Of Self-Supervised Representations, Atharva Tendle

School of Computing: Dissertations, Theses, and Student Research

Transfer learning technique enables training Deep Learning (DL) models in a data-efficient way for solving computer vision tasks. It involves pretraining a DL model to learn representations from a large and general-purpose source dataset, then fine-tuning the model using the task-specific target dataset. The dominant supervised learning (SL) approach for pretraining representations suffers from some limitations that include expensive labeling and poor generalizability. Recent advancements in the self-supervised learning (SSL) approach made it possible to learn effective representations from unlabeled data. The performance of the fine-tuned DL models based on pretrained SSL representations is on par with the state-of-the-art pretrained …