Preserving User Data Privacy Through The Development Of An Android Solid Library,
2023
University of Arkansas, Fayetteville
Preserving User Data Privacy Through The Development Of An Android Solid Library, Alexandria Lim
Computer Science and Computer Engineering Undergraduate Honors Theses
In today’s world where any and all activity on the internet produces data, user data privacy and autonomy are not prioritized. Companies called data brokers are able to gather data elements of personal information numbering in the billions. This data can be anything from purchase history, credit card history, downloaded applications, and service subscriptions. This information can be analyzed and inferences can be drawn from analysis, categorizing people into groups that range in sensitivity — from hobbies to race and income classes. Not only do these data brokers constantly overlook data privacy, this mass amount of data makes them extremely …
Reverse Engineering Post-Quantum Cryptography Schemes To Find Rowhammer Exploits,
2023
University of Arkansas, Fayetteville
Reverse Engineering Post-Quantum Cryptography Schemes To Find Rowhammer Exploits, Sam Lefforge
Computer Science and Computer Engineering Undergraduate Honors Theses
Post-quantum cryptography is a necessary countermeasure to protect against attacks from quantum computer. However, the post-quantum cryptography schemes are potentially vulnerable to side channel attacks. One such method of attacking involves creating bit-flips in victim memory through a process called Rowhammer. These attacks can vary in nature, but can involve rowhammering bits to raise the encryption scheme's decryption failure rate, or modifying the scheme's random seed. With a high enough decryption failure rate, it becomes feasible to generate sufficient information about the secret key to perform a key recovery attack. This thesis proposed two attacks on proposed post-quantum cryptography algorithms, …
Critical Infrastructure Workforce Development Pods For Teaching Cybersecurity Using Netlab+,
2023
University of Arkansas, Fayetteville
Critical Infrastructure Workforce Development Pods For Teaching Cybersecurity Using Netlab+, Gideon Sutterfield
Computer Science and Computer Engineering Undergraduate Honors Theses
As digital automation for Industrial Control Systems has grown, so has its vulnerability to cyberattacks. The world of industry has responded effectively to this, but the world of academia is still lagging as its emphasis is still almost entirely on information technology. Considering this, we created a workforce development pod that serves as a hands-on learning module for teaching students key cybersecurity ideas surrounding operational technology using the NETLAB+ platform. A pod serves as the virtual environment where the learning exercise takes place. This project’s implementation involved the creation of a segmented network within the pod where a student starts …
Fuel Prediction: Determining The Desirable Stops For The Cheapest Road Trips,
2023
University of Arkansas, Fayetteville
Fuel Prediction: Determining The Desirable Stops For The Cheapest Road Trips, Maxx Smith
Computer Science and Computer Engineering Undergraduate Honors Theses
Current technology has given rise to many advanced route-planning applications that are available for use by the general public. Gone are the days of preparing for road trips by looking at a paper map for hours on end trying to determine the correct exits or calculate the distance to be traveled. However, with the use of modern technology, there is a certain aspect of forward-thinking that is now lost with planning a road trip. One of the biggest constraints that often gets left on the backburner is deciding when and where to stop to refuel the car. This report is …
Culture In Computing: The Importance Of Developing Gender-Inclusive Software,
2023
University of Arkansas, Fayetteville
Culture In Computing: The Importance Of Developing Gender-Inclusive Software, Creighton France
Computer Science and Computer Engineering Undergraduate Honors Theses
The field of computing as we know it today exists because of the contributions of numerous female mathematicians, computer scientists, and programmers. While working with hardware was viewed as “a man’s job” during the mid-20th century, computing and programming was viewed as a noble and high-paying field for women to occupy. However, as time has progressed, the U.S. has seen a decrease in the number of women pursuing computer science. The idea that computing is a masculine discipline is common in the U.S. today for reasons such as male-centered marketing of electronics and gadgets, an inaccurate representation of what it …
Source Code Plagiarism Detection Using Jplag & Stack Overflow Data,
2023
Western Kentucky University
Source Code Plagiarism Detection Using Jplag & Stack Overflow Data, Sudheer Yetthapu
Masters Theses & Specialist Projects
Advancements in computer technology and internet services have led to the availability of vast amounts of information like videos, articles, research papers, and code samples. Free online information will increase the possibility of plagiarism and collusion among students. People can commit plagiarism in both text and code [1], as tools used to detect plagiarism between texts and between codes are distinct. Traditionally plagiarism in code is detected using manual inspection, which is a tedious process and misses to compare code from previous submissions and external sources. To overcome this issue, systems that can automatically detect plagiarism in code were developed …
Green Hpc: Optimizing Software Stack Energy Efficiency Of Large Data Systems,
2023
Clemson University
Green Hpc: Optimizing Software Stack Energy Efficiency Of Large Data Systems, Grant Wilkins
Honors College Theses
High-performance computing (HPC) is indispensable in modern scientific research and industry applications, but its energy consumption is a growing concern. This thesis presents two novel approaches to optimize energy consumption in large data systems. The first chapter of the thesis will discuss the use of Dynamic Voltage and Frequency Scaling (DVFS) to optimize the energy efficiency of two popular lossy compression algorithms: SZ and ZFP. By adjusting the voltage and frequency levels of computing resources, DVFS can reduce energy consumption while maintaining the desired level of performance and accuracy. The second chapter of the thesis will focus on a detailed …
Modeling And Control Strategies For A Two-Wheel Balancing Mobile Robot,
2023
University of Arkansas, Fayetteville
Modeling And Control Strategies For A Two-Wheel Balancing Mobile Robot, John Alan Moritz
Graduate Theses and Dissertations
The problem of balancing and autonomously navigating a two-wheel mobile robot is an increasingly active area of research, due to its potential applications in last-mile delivery, pedestrian transportation, warehouse automation, parts supply, agriculture, surveillance, and monitoring. This thesis investigates the design and control of a two-wheel balancing mobile robot using three different control strategies: Proportional Integral Derivative (PID) controllers, Sliding Mode Control, and Deep Q-Learning methodology. The mobile robot is modeled using a dynamic and kinematic model, and its motion is simulated in a custom MATLAB/Simulink environment. The first part of the thesis focuses on developing a dynamic and kinematic …
Uibee: An Improved Deep Instance Segmentation And Classification Of Ui Elements In Wireframes,
2023
TÜBİTAK
Uibee: An Improved Deep Instance Segmentation And Classification Of Ui Elements In Wireframes, Cahi̇t Berkay Kazangi̇rler, Caner Özcan, Buse Yaren Teki̇n
Turkish Journal of Electrical Engineering and Computer Sciences
User Interface (UI) is a basic concept in which individuals interact with any computer program or technological device to create a graphical design. In the initial stages of app development, UI prototype is a must. An automatic analysis system for the basic execution of UI designs will considerably speed up the development of designs according to old-fashioned methods. In this approach, it is aimed at saving cost and time by automating the process. For the aforesaid objective, we present a new approach rather than the traditional methods. For this reason, a high amount of elements in wireframes are detected and …
Adversarial Deep Learning And Security With A Hardware Perspective,
2023
Clemson University
Adversarial Deep Learning And Security With A Hardware Perspective, Joseph Clements
All Dissertations
Adversarial deep learning is the field of study which analyzes deep learning in the presence of adversarial entities. This entails understanding the capabilities, objectives, and attack scenarios available to the adversary to develop defensive mechanisms and avenues of robustness available to the benign parties. Understanding this facet of deep learning helps us improve the safety of the deep learning systems against external threats from adversaries. However, of equal importance, this perspective also helps the industry understand and respond to critical failures in the technology. The expectation of future success has driven significant interest in developing this technology broadly. Adversarial deep …
Digital Simulations Of Memristors Towards Integration With Reconfigurable Computing,
2023
University of Arkansas, Fayetteville
Digital Simulations Of Memristors Towards Integration With Reconfigurable Computing, Ivris Raymond
Computer Science and Computer Engineering Undergraduate Honors Theses
The end of Moore’s Law has been predicted for decades. Demand for increased parallel computational performance has been increased by improvements in machine learning. This past decade has demonstrated the ever-increasing creativity and effort necessary to extract scaling improvements in CMOS fabrication processes. However, CMOS scaling is nearing its fundamental physical limits. A viable path for increasing performance is to break the von Neumann bottleneck. In-memory computing using emerging memory technologies (e.g. ReRam, STT, MRAM) offers a potential path beyond the end of Moore’s Law. However, there is currently very little support from industry tools for designers wishing to incorporate …
Beyond Just Money Transactions: Redesigning Digital Peer-To-Peer Payments For Social Connections,
2023
Clemson University
Beyond Just Money Transactions: Redesigning Digital Peer-To-Peer Payments For Social Connections, Lingyuan Li
All Dissertations
Financial activities, such as the exchange of money between individuals, have long been considered a crucial aspect of how people build and maintain their interpersonal relationships (i.e., a strong, deep, or close association/acquaintance between two or more people) with individuals they know because money is a sensitive social construct. In particular, over the past decade, how to conduct, manage, and experience money exchanges and processes between individuals has been dramatically transformed due to the increasing popularity of digital peer-to-peer (P2P) payment services (i.e., performing one to one online money transactions via a digital device). In this sense, digital P2P payments …
Deep Reinforcement Learning And Game Theoretic Monte Carlo Decision Process For Safe And Efficient Lane Change Maneuver And Speed Management,
2023
Clemson University
Deep Reinforcement Learning And Game Theoretic Monte Carlo Decision Process For Safe And Efficient Lane Change Maneuver And Speed Management, Shahab Karimi
All Dissertations
Predicting the states of the surrounding traffic is one of the major problems in automated driving. Maneuvers such as lane change, merge, and exit management could pose challenges in the absence of intervehicular communication and can benefit from driver behavior prediction. Predicting the motion of surrounding vehicles and trajectory planning need to be computationally efficient for real-time implementation. This dissertation presents a decision process model for real-time automated lane change and speed management in highway and urban traffic. In lane change and merge maneuvers, it is important to know how neighboring vehicles will act in the imminent future. Human driver …
Vanet Applications Under Loss Scenarios & Evolving Wireless Technology,
2023
Clemson University
Vanet Applications Under Loss Scenarios & Evolving Wireless Technology, Adil Alsuhaim
All Dissertations
In this work we study the impact of wireless network impairment on the performance of VANET applications such as Cooperative Adaptive Cruise Control (CACC), and other VANET applications that periodically broadcast messages. We also study the future of VANET application in light of the evolution of radio access technologies (RAT) that are used to exchange messages. Previous work in the literature proposed fallback strategies that utilizes on-board sensors to recover in case of wireless network impairment, those methods assume a fixed time headway value, and do not achieve string stability. In this work, we study the string stability of a …
Enhanced Mobile Networking Using Multi-Connectivity And Packet Duplication In Next-Generation Cellular Networks,
2023
Clemson University
Enhanced Mobile Networking Using Multi-Connectivity And Packet Duplication In Next-Generation Cellular Networks, Prabodh Mishra
All Dissertations
Modern cellular communication systems need to handle an enormous number of users and large amounts of data, including both users as well as system-oriented data. 5G is the fifth-generation mobile network and a new global wireless standard that follows 4G/LTE networks. The uptake of 5G is expected to be faster than any previous cellular generation, with high expectations of its future impact on the global economy. The next-generation 5G networks are designed to be flexible enough to adapt to modern use cases and be highly modular such that operators would have the flexibility to provide selective features based on user …
Task Offloading And Resource Allocation Based On Dl-Ga In Mobile Edge Computing,
2023
TÜBİTAK
Task Offloading And Resource Allocation Based On Dl-Ga In Mobile Edge Computing, Hang Gu, Minjuan Zhang, Wenzao Li, Yuwen Pan
Turkish Journal of Electrical Engineering and Computer Sciences
With the rapid development of 5G and the Internet of Things (IoT), the traditional cloud computing architecture struggle to support the booming computation-intensive and latency-sensitive applications. Mobile edge computing (MEC) has emerged as a solution which enables abundant IoT tasks to be offloaded to edge services. However, task offloading and resource allocation remain challenges in MEC framework. In this paper, we add the total number of offloaded tasks to the optimization objective and apply algorithm called Deep Learning Trained by Genetic Algorithm (DL-GA) to maximize the value function, which is defined as a weighted sum of energy consumption, latency, and …
Breath Analysis For Detection Of Lung Cancer With Hybrid Sensor-Based Electronic Nose,
2023
TÜBİTAK
Breath Analysis For Detection Of Lung Cancer With Hybrid Sensor-Based Electronic Nose, Ümi̇t Özsandikcioğlu, Ayten Atasoy
Turkish Journal of Electrical Engineering and Computer Sciences
Lung cancer has the highest death rates among all types of cancer worldwide. Detection of lung cancer in its early stages significantly increases the survival rate. In this study, the aim is to improve the lung cancer detection performance of electronic noses (e-noses) with breath analysis by using two different types of gas sensor-based e-nose. The developed e-nose system consists of 14 quartz crystal microbalance (QCM) sensors and 8 metal oxide semiconductor (MOS) sensors. Breath samples were collected from a total of 100 volunteers, including 60 patients with lung cancer, 20 healthy nonsmokers, and 20 healthy smokers, and were classified …
Integration Of Neural Network And Distance Relay To Improve The Fault Localization On Transmission Lines,
2023
TÜBİTAK
Integration Of Neural Network And Distance Relay To Improve The Fault Localization On Transmission Lines, Linh Tran
Turkish Journal of Electrical Engineering and Computer Sciences
Power transmission lines are integral and very important components of power systems. Because of the length of these lines and the complexity of the power grids, the lines may encounter various incidents such as lightning strike, shortage, and breakage. When an incident or a fault occurs, a fast process of identification, localization, and isolation of the fault is desired. An accurate fault localization would have a great impact in reducing the restoration time of the system. One of the most popular solutions for fault detection and localization is the distance relays using the impedance-based algorithms. However, these relays are still …
Quadratic Programming Based Partitioning For Block Cimmino With Correct Value Representation,
2023
TÜBİTAK
Quadratic Programming Based Partitioning For Block Cimmino With Correct Value Representation, Zuhal Taş, Fahreddi̇n Şükrü Torun
Turkish Journal of Electrical Engineering and Computer Sciences
The block Cimmino method is successfully used for the parallel solution of large linear systems of equations due to its amenability to parallel processing. Since the convergence rate of block Cimmino depends on the orthogonality between the row blocks, advanced partitioning methods are used for faster convergence. In this work, we propose a new partitioning method that is superior to the state-of-the-art partitioning method, GRIP, in several ways. Firstly, our proposed method exploits the Mongoose partitioning library which can outperform the state-of-the-art methods by combining the advantages of classical combinatoric methods and continuous quadratic programming formulations. Secondly, the proposed method …
Unbiased Federated Learning In Energy Harvesting Error-Prone Channels,
2023
TÜBİTAK
Unbiased Federated Learning In Energy Harvesting Error-Prone Channels, Zeynep Çakir, Eli̇f Tuğçe Ceran Arslan
Turkish Journal of Electrical Engineering and Computer Sciences
Federated learning (FL) is a communication-efficient and privacy-preserving learning technique for collaborative training of machine learning models on vast amounts of data produced and stored locally on the distributed users. This paper investigates unbiased FL methods that achieve a similar convergence as state-of-the-art methods in scenarios with various constraints like an error-prone channel or intermittent energy availability. For this purpose, we propose FL algorithms that jointly design unbiased user scheduling and gradient weighting according to each user's distinct energy and channel profile. In addition, we exploit a prevalent metric called the age of information (AoI), which quantifies the staleness of …
