Digital Communications and Networking Commons^™

Adaptable Quantum Education Platform Using Learning Objects, Krishna Puja Anumula

Master's Theses

In recent years, the need to make classroom learning more interactive and engaging has become increasingly important. The lack of workforce in interdisciplinary fields such as quantum networking and quantum internet requires a new approach that addresses every learner’s individual needs. To address this challenge, this thesis introduces an adaptive learning platform rooted in the theory of learning objects and Kolb’s experiential learning model. The platform aids educators and learners in designing and utilizing various learning objects for quantum networking and quantum internet.

The platform enables educators and learners to build their own lessons and lesson plans using learning objects …

Welcome To Cheney App, Timothy Nelson, Nolan Posey, Tanner Stephenson, Daniel Palmer, Matthew Matriciano

2024 Symposium

Welcome to Cheney is a non-profit organization committed to fostering communication, connection, and action within the city of Cheney. Their primary purpose is to provide timely and accurate information to the residents of Cheney. Welcome to Cheney has tried utilizing other forms of social media such as Facebook and Instagram to share information, but their presence is being overshadowed amidst the noise on those platforms. Therefore, the intention of this project is to develop a mobile app with the sole purpose of being a reliable means of sharing important information with the residents of Cheney.

The information being shared on …

“The Role Of Modern Technologies In Effective Management Of Crowds”, Ayman El-Din

Journal of Police and Legal Sciences

Scientists started to think about the importance of developing crowd management methods, because of human gatherings - in different countries - have been accompanied by lots of disasters that have killed many and resulted in many injuries. Gathering crowd data is vital in the process of managing crowds, as crowd information contributes significantly to planning and decision-making processes and increasing communication between parties interacting with them, and data collected includes "the number of crowd members, crowd density, and problems that may occur”. Technology and technical awareness play an important role in “collecting, organizing, analyzing” real-time collected data of crowd. This …

Authenticated Diagnosing Of Covid-19 Using Deep Learning-Based Ct Image Encryption Approach, Mohamed Attia Abdelgwad, Amira Hassan Abed, Mahmoud Bahloul

Future Computing and Informatics Journal

Researchers are motivated to use artificial intelligence in biometrics, medical imaging encryption, as well as cybersecurity due to its rapid progress. An encryption method for CT scans—which are used to diagnose COVID-19 disease—is proposed in this study. The suggested encryption method creates a connection among an individual's face picture and CT image to increase confidentiality. The simple CT picture is first enhanced with a host image. An encryption key is multiplied by the final result. This key is produced by applying a Convolutional Neural Network (CNN) to recognize characteristics from people's face photographs. Additionally, a straightforward CNN with three convolutional …

The Logical Implications Of Open Public Data: Examining The Current Situation, Reviewing The Problems And Advancing The Rule Of Law, Yanlei Cheng, Lin Zhang, Xu Zhang

Journal of Scientific Information Research

[Purpose/significance]Digital rule of law government is a new paradigm of government governance that is compatible with digital China and digital society. Data elements have become an important driving force for high-quality economic development in the era of digital, and public data openness is an important issue in the construction of digital rule of law government. [Method/process]In this paper, the regulations, policies and technical standards of the central government and 10 provinces, including Zhejiang, Shandong, Guizhou, Guangdong, Sichuan, Fujian, Guangxi, Hainan, Jiangxi and Jiangsu as research samples to examine the current system of regulations and policies on the opening up of …

Comprehensive Network Redundancy Implementation And Cybersecurity Hardening Project: Ensuring Resilience And Defending Against Dhcp Starvation, Stp Man-In-The-Middle, And Brute Force Attacks, Seth Shaheen

Williams Honors College, Honors Research Projects

I have created a network topology that contains three Cisco routers, three Cisco switches, and three endpoints. The network has been built using the software GNS-3. The endpoints on the topology include one VPC, one Kali Linux VM, and one Ubuntu Server VM. The main purpose of this network topology is to show the skills I have learned during my tenure at The University of Akron. This will be done by hardening this network to ensure that the network is impervious to cyber-attacks. The Kali Linux VM will act as the attacker on the network and conduct three attacks: STP …

Optimal False Data Injection (Fdi) In Simulated Cooperative Adaptive Cruise Control (Cacc) Systems, Lovro Dukic

Master's Theses

In the rapidly advancing field of autonomous vehicles, ensuring the security and reliability of self-driving systems is crucial. Autonomous vehicle systems, such as cooperative adaptive cruise control (CACC), must undergo significant research and testing before their integration into commercial intelligent transportation systems. CACC considers multiple vehicles in close proximity as a single entity, or platoon, with each vehicle equipped with a controller that uses sensor-based measurements and vehicle-to-vehicle (V2V) communication to control inter-vehicle spacing. While this system offers numerous potential benefits for traffic safety and efficiency, it is also susceptible to False Data Injection (FDI) attacks, which can cause the …

A Study On Privacy Over Security And Privacy Enhancing Networks, Everett Lee Conway

Master's Theses

With rapid developments in communication technologies and awareness of security and privacy risks online, Security and Privacy Enhancing Networks (SPENs) have become increasingly popular. Especially during the COVID-19 pandemic, workplaces encouraged employees to take additional security measures, such as VPNs. In this work, we conduct a comprehensive study on website fingerprinting attacks. A comprehensive system model and threat model based on two types of SPENs (Virtual Private Networks and Tor Networks) are presented. Moreover, we demonstrate a website fingerprinting attack by ethically collecting website fetch data and analyzing the collected data using five different machine learning classification models including k …

Anomaly Detection In Heterogeneous Iot Systems: Leveraging Symbolic Encoding Of Performance Metrics For Anomaly Classification, Maanav Patel

Master's Theses

Anomaly detection in Internet of Things (IoT) systems has become an increasingly popular field of research as the number of IoT devices proliferate year over year. Recent research often relies on machine learning algorithms to classify sensor readings directly. However, this approach leads to solutions being non-portable and unable to be applied to varying IoT platform infrastructure, as they are trained with sensor data specific to one configuration. Moreover, sensors generate varying amounts of non-standard data which complicates model training and limits generalization. This research focuses on addressing these problems in three ways a) the creation of an IoT Testbed …

Communication Challenges In Underwater Wireless Networks: Mac Protocols And Software Solutions, Dmitrii Dugaev

Dissertations, Theses, and Capstone Projects

Underwater wireless networks (UWNs) represent a diverse and intriguing research domain, encompassing a wide array of scientific and industrial applications. This dissertation delves into the communication challenges at the Medium Access Control (MAC) layer within UWNs, stemming from the distinctive signal propagation conditions and the harshness of the deployment environment. The manuscript provides comprehensive coverage of key aspects of UWNs, including potential applications, communication protocols, methodologies employed in such networks, and existing software solutions that facilitate simulation, emulation, and real testbed scenarios for underwater research endeavors. Furthermore, this research introduces innovative software and communication solutions designed to facilitate the seamless …

Expanding The Horizon: Blockchain Technology Beyond The Bounds Of Cryptocurrency, Hassan Azhar

SMU Data Science Review

Blockchain technology has extended beyond its initial role as the infrastructure for cryptocurrencies to transform various industries with its decentralized and transparent ledger system. This paper examines the broad spectrum of blockchain applications beyond cryptocurrency. It explores its potential to innovate and drive change across finance, supply chain management, healthcare, real estate, and voting systems. We review recent literature, detail specific use cases, and discuss blockchain's challenges and opportunities, aiming to provide a comprehensive overview of its transformative impact. Integrating emerging technologies, scalability, regulatory considerations, and energy consumption are critical challenges to its adoption. Our findings underscore the need for …

A Deep Learning Framework For Blockage Mitigation In Mmwave Wireless, Ahmed Hazaa Almutairi

Dissertations and Theses

Millimeter-Wave (mmWave) communication is a key technology to enable next generation wireless systems. However, mmWave systems are highly susceptible to blockages, which can lead to a substantial decrease in signal strength at the receiver. Identifying blockages and mitigating them is thus a key challenge to achieve next generation wireless technology goals, such as enhanced mobile broadband (eMBB) and Ultra-Reliable and Low-Latency Communication (URLLC). This thesis proposes several deep learning (DL) frameworks for mmWave wireless blockage detection, mitigation, and duration prediction. First, we propose a DL framework to address the problem of identifying whether the mmWave wireless channel between two devices …

Analysis Of Inequality In Household Internet Utilization And Policy Implications, Shanisara Chamwong, Thoedsak Chomtohsuwan, Narissara Charoenphandhu

Journal of Demography

This research investigates the pervasive inequality in household internet access and use that contributes to the digital divide. As the internet becomes an integral part of daily life, variations in access and use carry significant implications for social and economic opportunities. A quantitative approach is applied, analyzing data from The National Statistical Office of Thailand to capture a comprehensive understanding of inequality in household internet access and use, as measured by the Gini coefficient. Five aspects of internet access and use are considered as the determinants of inequality, including internet connectivity, internet affordability, internet quality, device availability, and flexibility and …

Learning Proximal Operators With Gaussian Process And Adaptive Quantization In Distributed Optimization, Aldo Duarte Vera Tudela

LSU Doctoral Dissertations

In networks consisting of agents communicating with a central coordinator and working together to solve a global optimization problem in a distributed manner, the agents are often required to solve private proximal minimization subproblems. Such a setting often requires a further decomposition method to solve the global distributed problem, resulting in extensive communication overhead. In networks where communication is expensive, it is crucial to reduce the communication overhead of the distributed optimization scheme. Integrating Gaussian processes (GP) as a learning component to the Alternating Direction Method of Multipliers (ADMM) has proven effective in learning each agent's local proximal operator to …

Effects Of A Wi-Fi Link On The Performance Of A Path Following Autonomous Ground Vehicle, Anthony Iwejuo, Austin Cagle, Billy Kihei, Ph.D.

Symposium of Student Scholars

As vehicles become more automated and connected, the future of safe and efficient travel will be dependent on efficient wireless networks. Artificial intelligence (AI) demands high power resources and computing resources that can be resource-intensive for mobile robotic systems. A new paradigm involving the remote computing of A.I. can enable robotics that are built lighter and more power efficient. In this study, we compare a locally run artificial intelligence algorithm for autonomous ground vehicle navigation against remote computation through various wireless links to highlight the need for low-latency access to remote computing resources over Wi-Fi network calls. Our findings show …

Computer Security Lab Experiment, Orit D. Gruber, Herbert Schanker

Open Educational Resources

This is a basic experiment for all students of all majors to explore Computer Security. Each instruction included in this experiment is conducted online via a Web Browser; Firefox or Chrome is recommended. Software does not need to be downloaded nor installed. The step by step instructions in this experiment include interactive questions and observations which are then included in the (student's) final report.

Evaluating The Effect Of Noise On Secure Quantum Networks, Karthick Anbalagan

Master's Theses

This thesis focuses on examining the resilience of secure quantum networks to environmental noise. Specifically, we evaluate the effectiveness of two well-known quantum key distribution (QKD) protocols: the Coherent One-Way (COW) protocol and Kak’s Three-Stage protocol (Kak06). The thesis systematically evaluates these protocols in terms of their efficiency, operational feasibility, and resistance to noise, thereby contributing to the progress of secure quantum communications. Using simulations, this study evaluates the protocols in realistic scenarios that include factors such as noise and decoherence. The results illustrate each protocol’s relative benefits and limitations, highlighting the three-stage protocol’s superior security characteristics, resistance to interference, …

Machine Learning For Intrusion Detection Into Unmanned Aerial System 6g Networks, Faisal Alrefaei

Doctoral Dissertations and Master's Theses

Progress in the development of wireless network technology has played a crucial role in the evolution of societies and provided remarkable services over the past decades. It remotely offers the ability to execute critical missions and effective services that meet the user's needs. This advanced technology integrates cyber and physical layers to form cyber-physical systems (CPS), such as the Unmanned Aerial System (UAS), which consists of an Unmanned Aerial Vehicle (UAV), ground network infrastructure, communication link, etc. Furthermore, it plays a crucial role in connecting objects to create and develop the Internet of Things (IoT) technology. Therefore, the emergence of …

Improving Ethics Surrounding Collegiate-Level Hacking Education: Recommended Implementation Plan & Affiliation With Peer-Led Initiatives, Shannon Morgan, Dr. Sanjay Goel

Military Cyber Affairs

Cybersecurity has become a pertinent concern, as novel technological innovations create opportunities for threat actors to exfiltrate sensitive data. To meet the demand for professionals in the workforce, universities have ramped up their academic offerings to provide a broad range of cyber-related programs (e.g., cybersecurity, informatics, information technology, digital forensics, computer science, & engineering). As the tactics, techniques, and procedures (TTPs) of hackers evolve, the knowledge and skillset required to be an effective cybersecurity professional have escalated accordingly. Therefore, it is critical to train cyber students both technically and theoretically to actively combat cyber criminals and protect the confidentiality, integrity, …

Using Digital Twins To Protect Biomanufacturing From Cyberattacks, Brenden Fraser-Hevlin, Alec W. Schuler, B. Arda Gozen, Bernard J. Van Wie

Military Cyber Affairs

Understanding of the intersection of cyber vulnerabilities and bioprocess regulation is critical with the rise of artificial intelligence and machine learning in manufacturing. We detail a case study in which we model cyberattacks on network-mediated signals from a novel bioreactor, where it is important to control medium feed rates to maintain cell proliferation. We use a digital twin counterpart reactor to compare glucose and oxygen sensor signals from the bioreactor to predictions from a kinetic growth model, allowing discernment of faulty sensors from hacked signals. Our results demonstrate a successful biomanufacturing cyberattack detection system based on fundamental process control principles.