Computer Engineering Commons^™

Diegetic Sonification For Low Vision Gamers, Jhané Dawes

Master's Theses

There are not many games designed for all players that provide accommodations for low vision users. This means that low vision users may not get to engage with the gaming community in the same way as their sighted peers. In this thesis, I explore how diegetic sonification can be used as a tool to support these low vision gamers in the typical gaming environment. I asked low vision players to engage with a prototype game level with two diegetic sonification techniques applied, without the use of their corrective lenses. I found that participants had more enjoyment and experienced less difficulty …

Assessing Blockchain’S Potential To Ensure Data Integrity And Security For Ai And Machine Learning Applications, Aiasha Siddika

Master of Science in Information Technology Theses

The increasing use of data-centric approaches in the fields of Machine Learning and Artificial Intelligence (ML/AI) has raised substantial issues over the security, integrity, and trustworthiness of data. In response to this challenge, Blockchain technology offered a promising and practical solution, as its inherent characteristics as a decentralized distributed ledger, coupled with cryptographic processes, offer an unprecedented level of data confidentiality and immutability. This study examines the mutually beneficial connection between Blockchain technology and ML/AI, using Blockchain's inherent capacity to protect against unauthorized alterations of data during the training phase of ML models. The method involves building valid blocks of …

Screensafefuture: A Parent-Empathetic And Practical Mhealth Application For Toddlers' Brain Development Addressing Screen-Addiction Challenges, Nafisa Anjum

Master of Science in Information Technology Theses

The surging incidents of infants and toddlers screen addiction in the United States are becoming a pressing concern due to its detrimental and compound impact on cognitive development, mental health, and physical growth. To address this era's critical child health and human development problem, we propose an innovative mHealth application-- ScreenSafeFuture-- in this paper. ScreenSafeFuture provides practical and parent-friendly solutions that seamlessly fit into parents' busy lifestyles, also acknowledging the effectiveness and convenience of smartphones as a healthcare tool. Our offering includes essential features designed to enhance the experience between parents and their children under 3 years old. With an …

Designing Intelligent Energy Efficient Scheduling Algorithm To Support Massive Iot Communication In Lora Networks, Jui Mhatre

Master of Science in Computer Science Theses

We are about to enter a new world with sixth sense ability – “Network as a sensor -6G”. The driving force behind digital sensing abilities is IoT. Due to their capacity to work in high frequency, 6G devices have voracious energy demand. Hence there is a growing need to work on green solutions to support the underlying 6G network by making it more energy efficient. Low cost, low energy, and long-range communication capability make LoRa the most adopted and promising network for IoT devices. Since LoRaWAN uses ALOHA for multi-access of channels, collision management is an important task. Moreover, in …

Detection Of Crypto-Ransomware Attack Using Deep Learning, Muna Jemal

Master of Science in Computer Science Theses

The number one threat to the digital world is the exponential increase in ransomware attacks. Ransomware is malware that prevents victims from accessing their resources by locking or encrypting the data until a ransom is paid. With individuals and businesses growing dependencies on technology and the Internet, researchers in the cyber security field are looking for different measures to prevent malicious attackers from having a successful campaign. A new ransomware variant is being introduced daily, thus behavior-based analysis of detecting ransomware attacks is more effective than the traditional static analysis. This paper proposes a multi-variant classification to detect ransomware I/O …

Analysis Of The Adherence Of Mhealth Applications To Hipaa Technical Safeguards, Bilash Saha

Master of Science in Information Technology Theses

The proliferation of mobile health technology, or mHealth apps, has made it essential to protect individual health details. People now have easy access to digital platforms that allow them to save, share, and access their medical data and treatment information as well as easily monitor and manage health-related issues. It is crucial to make sure that protected health information (PHI) is effectively and securely transmitted, received, created, and maintained in accordance with the rules outlined by the Health Insurance Portability and Accountability Act (HIPAA), as the use of mHealth apps increases. Unfortunately, many mobile app developers, particularly those of mHealth …

A Comparative Study On Blockchain-Based Electronic Health Record Systems: Performance, Privacy, And Security Between Hyperledger Fabric And Ethereum Frameworks, Md Jobair Hossain Faruk, Hossain Shahriar, Maria Valero, Xia Li

Master of Science in Software Engineering Theses

Traditional data collection, storage, and processing of Electronic Health Records (EHR) utilize centralized techniques that pose several risks of single point of failure and lean the systems to a number of internal and external data breaches that compromise their reliability and availability. Addressing the challenges of conventional database techniques and improving the overall aspects of EHR application, blockchain technology is being evaluated to find a possible solution. Blockchain refers to an emerging distributed technology and incorruptible database of records or digital events which execute, validate, and maintain by a ledger technology to provide an immutable architecture and prevent records manipulation …

Graph Based Management Of Temporal Data, Alex Fotso

Master of Science in Computer Science Theses

In recent decades, there has been a significant increase in the use of smart devices and sensors that led to high-volume temporal data generation. Temporal modeling and querying of this huge data have been essential for effective querying and retrieval. However, custom temporal models have the problem of generalizability, whereas the extended temporal models require users to adapt to new querying languages. In this thesis, we propose a method to improve the modeling and retrieval of temporal data using an existing graph database system (i.e., Neo4j) without extending with additional operators. Our work focuses on temporal data represented as intervals …

Efficient Yet Robust Privacy For Video Streaming, Luke Cranfill, Junggab Son

Master of Science in Computer Science Theses

MPEG-DASH is a video streaming standard that outlines protocols for sending audio and video content from a server to a client over HTTP. The standard has been widely utilized by the video streaming industry. However, it creates an opportunity for an adversary to invade users’ privacy. While a user is watching a video, information is leaked in the form of meta-data, the size and time that the server sent data to the user. This information is not protected by encryption and can be used to create a fingerprint for a video. Once the fingerprint is created, the adversary can use …

Decentralized Aggregation Design And Study Of Federated Learning, Venkata Naga Surya Sameeraja Malladi

Master of Science in Software Engineering Theses

The advent of machine learning techniques has given rise to modern devices with built-in models for decision making and providing rich content to users. This typically involves processing huge volumes of data in central servers and sending updated models to end-user devices. There are two main concerns on this server architecture, one is the privacy of data that is being transferred to a central server and the other is volumes of data sent over the network for the model update. Federated Learning helps solve these problems by training models on local data within the device and aggregating the model with …

Project Blipper, Peter Jacobs, Preston Delaware, Ryan Foster

Senior Design Project For Engineers

This project was sponsored by Clorox to design and create an automatic bottle-unscrambling system for possible implementation at their bottling plant in Chile. The objective was to use a robotic arm to unscramble bottles from an incoming conveyor belt and place them upright on an outbound conveyor belt. Throughout the research, design, and testing of solutions for this project, several design alternatives were found for each discipline, and will be presented to Clorox so that they can make an informed decision for how and if they want to move forward with implementation of this project.

The project was split into …

Optimal Order Assignment With Minimum Wage Consideration (Ooamwc), Hakem Alazmi

Master of Science in Computer Science Theses

While the application of crowdsourcing has increased over the years, the technology experiences various issues during implementation. Examples of some of the issues that affect crowdsourcing include task assignment, profit maximizations, as well as time window issues. In some instances addressing some of the issues results in the other issues being overlooked. An example is when assigning tasks to workers, the profits of the workers might not be considered and this ends up affecting the profit maximization aspect. Various algorithms have been proposed to address the task assignment, profit maximizations, and time window issues. However, these algorithms address the issues …

Rethinking The Weakness Of Stream Ciphers And Its Application To Encrypted Malware Detection, William T. Stone, Junggab Son

Master of Science in Computer Science Theses

Encryption key use is a critical component to the security of a stream cipher: because many implementations simply consist of a key scheduling algorithm and logical exclusive or (XOR), an attacker can completely break the cipher by XORing two ciphertexts encrypted under the same key, revealing the original plaintexts and the key itself. The research presented in this paper reinterprets this phenomenon, using repeated-key cryptanalysis for stream cipher identification. It has been found that a stream cipher executed under a fixed key generates patterns in each character of the ciphertexts it produces and that these patterns can be used to …

Leveraging Smart Contracts For Asynchronous Group Key Agreement In Internet Of Things, Victor Youdom Kemmoe, Junggab Son

Master of Science in Computer Science Theses

Group Key Agreement (GKA) mechanism plays a crucial role in the realization of various secure applications in various networks such as, but not limited to, sensor networks, Internet of Things (IoT), vehicular networks, social networks, and so on. To be suitable for IoT, GKA must satisfy several critical requirements. First, a GKA mechanism must be robust against a compromised device attack and satisfy essential secrecy definitions without the existence of a Trusted Third Party (TTP). TTP is often used by IoT devices in the establishment of ad hoc networks and usually, these devices are resource-constrained. Second, the GKA mechanism must …

Performance Of Malware Classification On Machine Learning Using Feature Selection, Nusrat Asrafi

Master of Science in Computer Science Theses

The exponential growth of malware has created a significant threat in our daily lives, which heavily rely on computers running all kinds of software. Malware writers create malicious software by creating new variants, new innovations, new infections and more obfuscated malware by using techniques such as packing and encrypting techniques. Malicious software classification and detection play an important role and a big challenge for cyber security research. Due to the increasing rate of false alarm, the accurate classification and detection of malware is a big necessity issue to be solved. In this research, eight malware family have been classifying according …

A Framework To Detect Presentation Attacks, Laeticia Etienne

Master of Science in Information Technology Theses

Biometric-based authentication systems are becoming the preferred choice to replace password-based authentication systems. Among several variations of biometrics (e.g., face, eye, fingerprint), iris-based authentication is commonly used in every day applications. In iris-based authentication systems, iris images from legitimate users are captured and certain features are extracted to be used for matching during the authentication process. Literature works suggest that iris-based authentication systems can be subject to presentation attacks where an attacker obtains printed copy of the victim’s eye image and displays it in front of an authentication system to gain unauthorized access. Such attacks can be performed by displaying …

Document Layout Analysis And Recognition Systems, Sai Kosaraju

Master of Science in Computer Science Theses

Automatic extraction of relevant knowledge to domain-specific questions from Optical Character Recognition (OCR) documents is critical for developing intelligent systems, such as document search engines, sentiment analysis, and information retrieval, since hands-on knowledge extraction by a domain expert with a large volume of documents is intensive, unscalable, and time-consuming. There have been a number of studies that have automatically extracted relevant knowledge from OCR documents, such as ABBY and Sandford Natural Language Processing (NLP). Despite the progress, there are still limitations yet-to-be solved. For instance, NLP often fails to analyze a large document. In this thesis, we propose a knowledge …

Knn Optimization For Multi-Dimensional Data, Arialdis Japa

Master of Science in Computer Science Theses

The K-Nearest Neighbors (KNN) algorithm is a simple but powerful technique used in the field of data analytics. It uses a distance metric to identify existing samples in a dataset which are similar to a new sample. The new sample can then be classified via a class majority voting of its most similar samples, i.e. nearest neighbors. The KNN algorithm can be applied in many fields, such as recommender systems where it can be used to group related products or predict user preferences. In most cases, the performance of the KNN algorithm tends to suffer as the size of the …

Compliance Of Open Source Ehr Applications With Hipaa And Onc Security And Privacy Requirements, Maryam Farhadi, Hisham Haddad, Hossain Shahriar

Master of Science in Computer Science Theses

Electronic Health Records (EHRs) are digital versions of paper-based patient's health information. EHR applications are increasingly being adopted in many countries. They have resulted in improved quality in healthcare, convenient access to histories of patient medication and clinic visits, easier follow up of patient treatment plans, and precise medical decision-making process. EHR applications are guided by measures of the Health Insurance Portability and Accountability Act (HIPAA) to ensure confidentiality, integrity, and availability. However, there have been reported breaches of Protected Health Identifier (PHI) data stored by EHR applications. In many reported breaches, improper use of EHRs has resulted in disclosure …

Public Blockchain Scalability: Advancements, Challenges And The Future, Amritraj .

Master of Science in Software Engineering Theses

In the last decade, blockchain has emerged as one of the most influential innovations in software architecture and technology. Ideally, blockchains are designed to be architecturally and politically decentralized, similar to the Internet. But recently, public and permissionless blockchains such as Bitcoin and Ethereum have faced stumbling blocks in the form of scalability. Both Bitcoin and Ethereum process fewer than 20 transactions per second, which is significantly lower than their centralized counterpart such as VISA that can process approximately 1,700 transactions per second. In realizing this hindrance in the wide range adoption of blockchains for building advanced and large scalable …

American Sign Language Recognition Using Machine Learning And Computer Vision, Kshitij Bantupalli, Ying Xie

Master of Science in Computer Science Theses

Speech impairment is a disability which affects an individual’s ability to communicate using speech and hearing. People who are affected by this use other media of communication such as sign language. Although sign language is ubiquitous in recent times, there remains a challenge for non-sign language speakers to communicate with sign language speakers or signers. With recent advances in deep learning and computer vision there has been promising progress in the fields of motion and gesture recognition using deep learning and computer vision-based techniques. The focus of this work is to create a vision-based application which offers sign language translation …

Automatic Identification Of Animals In The Wild: A Comparative Study Between C-Capsule Networks And Deep Convolutional Neural Networks., Joel Kamdem Teto, Ying Xie

Master of Science in Computer Science Theses

The evolution of machine learning and computer vision in technology has driven a lot of

improvements and innovation into several domains. We see it being applied for credit decisions, insurance quotes, malware detection, fraud detection, email composition, and any other area having enough information to allow the machine to learn patterns. Over the years the number of sensors, cameras, and cognitive pieces of equipment placed in the wilderness has been growing exponentially. However, the resources (human) to leverage these data into something meaningful are not improving at the same rate. For instance, a team of scientist volunteers took 8.4 years, …

Implementation Of Secure Dnp3 Architecture Of Scada System For Smart Grids, Uday Bhaskar Boyanapalli

Master of Science in Computer Science Theses

With the recent advances in the power grid system connecting to the internet, data sharing, and networking enables space for hackers to maliciously attack them based on their vulnerabilities. Vital stations in the smart grid are the generation, transmission, distribution, and customer substations are connected and controlled remotely by the network. Every substation is controlled by a Supervisory Control and Data Acquisition (SCADA) system which communicates on DNP3 protocol on Internet/IP which has many security vulnerabilities. This research will focus on Distributed Network Protocol (DNP3) communication which is used in the smart grid to communicate between the controller devices. We …

An Iot System For Converting Handwritten Text To Editable Format Via Gesture Recognition, Nidhi Patel

Master of Science in Computer Science Theses

Evaluation of traditional classroom has led to electronic classroom i.e. e-learning. Growth of traditional classroom doesn’t stop at e-learning or distance learning. Next step to electronic classroom is a smart classroom. Most popular features of electronic classroom is capturing video/photos of lecture content and extracting handwriting for note-taking. Numerous techniques have been implemented in order to extract handwriting from video/photo of the lecture but still the deficiency of few techniques can be resolved, and which can turn electronic classroom into smart classroom.

In this thesis, we present a real-time IoT system to convert handwritten text into editable format by implementing …

Classification Of Images Based On Pixels That Represent A Small Part Of The Scene. A Case Applied To Microaneurysms In Fundus Retina Images, Pablo F. Ordonez, Pablo F. Ordonez

Master of Science in Computer Science Theses

Convolutional Neural Networks (CNNs), the state of the art in image classification, have proven to be as effective as an ophthalmologist, when detecting Referable Diabetic Retinopathy (RDR). Having a size of less than 1\% of the total image, microaneurysms are early lesions in DR that are difficult to classify. The purpose of this thesis is to improve the accuracy of detection of microaneurysms using a model that includes two CNNs with different input image sizes, 60x60 and 420x420 pixels. These models were trained using the Kaggle and Messidor datasets and tested independently against the Kaggle dataset, showing a sensitivity of …

Feature Selection And Improving Classification Performance For Malware Detection, Carlos A. Cepeda Mora

Master of Science in Computer Science Theses

The ubiquitous advance of technology has been conducive to the proliferation of cyber threats, resulting in attacks that have grown exponentially. Consequently, researchers have developed models based on machine learning algorithms for detecting malware. However, these methods require significant amount of extracted features for correct malware classification, making that feature extraction, training, and testing take significant time; even more, it has been unexplored which are the most important features for accomplish the correct classification.

In this Thesis, it is created and analyzed a dataset of malware and clean files (goodware) from the static and dynamic features provided by the online …

Comparative Study Of Dimension Reduction Approaches With Respect To Visualization In 3-Dimensional Space, Pooja Chenna

Master of Science in Computer Science Theses

In the present big data era, there is a need to process large amounts of unlabeled data and find some patterns in the data to use it further. If data has many dimensions, it is very hard to get any insight of it. It is possible to convert high-dimensional data to low-dimensional data using different techniques, this dimension reduction is important and makes tasks such as classification, visualization, communication and storage much easier. The loss of information should be less while mapping data from high-dimensional space to low-dimensional space. Dimension reduction has been a significant problem in many fields as …

Ultrasonic Data Transmission And Steganography, Hunter Young

KSU Journey Honors College Capstones and Theses

This project discusses the feasibility of using ultrasound to transmit data between computer systems, particularly computer systems that have been intentionally cut off from traditional networks for increased security. The goal of this project is to provide a synthesis of the current research that has been done into the use of ultrasonic data transmission, and to conduct a series of tests determining the validity of certain claims made in regards to ultrasonic data transmission within the information security community. All research, experiments, results, and inferences have been discussed in the context of how they relate to the realm of information …