Computer Engineering Commons^™

Systemic Risk Analysis Of Human Factors In Phishing, Mark Guilford

Engineering Management & Systems Engineering Theses & Dissertations

The scope of this study is the systemic risk of the role of humans in the risk of phishing. The relevance to engineering managers and systems engineers of the risks of phishing attacks is the theft of data which has significantly increased in the past couple of years. Phishing has become a systemic persistent threat to all internet users. Understanding the role of humans in phishing from a systemic perspective is a critical objective towards creating a strong defense against complex and manipulative phishing attacks. The systemic view of phishing concentrates on how phishing affects the entire organizational system, not …

Explainable Physics-Informed Deep Learning For Rainfall-Runoff Modeling And Uncertainty Assessment Across The Continental United States, Sadegh Sadeghi Tabas

All Dissertations

Hydrologic models provide a comprehensive tool to calibrate streamflow response to environmental variables. Various hydrologic modeling approaches, ranging from physically based to conceptual to entirely data-driven models, have been widely used for hydrologic simulation. During the recent years, however, Deep Learning (DL), a new generation of Machine Learning (ML), has transformed hydrologic simulation research to a new direction. DL methods have recently proposed for rainfall-runoff modeling that complement both distributed and conceptual hydrologic models, particularly in a catchment where data to support a process-based model is scared and limited.

This dissertation investigated the applicability of two advanced probabilistic physics-informed DL …

Niche: A Curated Dataset Of Engineered Machine Learning Projects In Python, Ratnadira Widyasari, Zhou Yang, Ferdian Thung, Sheng Qin Sim, Fiona Wee, Camellia Lok, Jack Phan, Haodi Qi, Constance Tan, David Lo, David Lo

Research Collection School Of Computing and Information Systems

Machine learning (ML) has gained much attention and has been incorporated into our daily lives. While there are numerous publicly available ML projects on open source platforms such as GitHub, there have been limited attempts in filtering those projects to curate ML projects of high quality. The limited availability of such a high-quality dataset poses an obstacle to understanding ML projects. To help clear this obstacle, we present NICHE, a manually labelled dataset consisting of 572 ML projects. Based on the evidence of good software engineering practices, we label 441 of these projects as engineered and 131 as non-engineered. This …

Power Amplifier Based On Composite Injection-Voltaic Transistors, Nodira Batirdjanovna Alimova

Chemical Technology, Control and Management

The problem of high-current radio engineering devices is related to the fact that the use of high-power transistors and other semiconductor devices is limited by such a phenomenon as a secondary breakdown, in which there is a sharp decrease in the voltage on the device with simultaneous internal current lacing, and the device fails. To solve the problem of secondary breakdown, schemes have been proposed that operate stably at reverse voltage values 4-5 times higher than usual and at power dissipation 2-3 times higher than the maximum allowable power for an individual device. The problem is proposed to be solved …

Methods And Algorithms For Monitoring And Prediction Of Various Fire Hazardous Situations, Mizaakbar Xakkulmirzayevich Hudayberdiyev, Oybek Zokirovich Koraboshev

Chemical Technology, Control and Management

This article analyzes emergency situations arising from natural disasters (fires, explosions, earthquakes, floods, landslides, etc.) and man-made accidents. The event in which the values of fire risks in the area decrease uniformly and at the same time the amount of fire risks is minimal is considered optimal. Models, methods, and logistic regression algorithm have been used to predict fire hazard situations and identify potential fire safety measures.

User Classification Based On Mouse Dynamic Authentication Using K-Nearest Neighbor, Didih Rizki Chandranegara, Anzilludin Ashari, Zamah Sari, Hardianto Wibowo, Wildan Suharso

Makara Journal of Technology

Mouse dynamics authentication is a method for identifying a person by analyzing the unique pattern or rhythm of their mouse movement. Owing to its distinctive properties, such mouse movements can be used as the basis for security. The development of technology is followed by the urge to keep private data safe from hackers. Therefore, increasing the accuracy of user classification and reducing the false acceptance rate (FAR) are necessary to improve data security. In this study, we propose to combine the K-nearest neighbor method and simple random sampling and obtain a sample from a dataset to improve the classification of …

Motion Control Simulation Of A Hexapod Robot, Weishu Zhan

Dartmouth College Master’s Theses

This thesis addresses hexapod robot motion control. Insect morphology and locomotion patterns inform the design of a robotic model, and motion control is achieved via trajectory planning and bio-inspired principles. Additionally, deep learning and multi-agent reinforcement learning are employed to train the robot motion control strategy with leg coordination achieves using a multi-agent deep reinforcement learning framework. The thesis makes the following contributions:

First, research on legged robots is synthesized, with a focus on hexapod robot motion control. Insect anatomy analysis informs the hexagonal robot body and three-joint single robotic leg design, which is assembled using SolidWorks. Different gaits are …

Infrastructure-As-Code: Automating The Deployment On Aws Using Terraform, Srikar Pratap

Masters Projects

In my master’s project, I used Terraform to create a scalable infrastructure on Amazon Web Services (AWS) for my personal website. Terraform is an open-source infrastructure-as-code (IAC) tool that allows you to create, manage and provision infrastructure resources, such as virtual machines, storage accounts, networks, and more, across multiple cloud providers and on-premises data centers using a declarative configuration language. A scalable infrastructure is important because it enables a system or application to handle increasing amounts of traffic or workload without experiencing performance issues or downtime. It ensures that the system remains responsive, available, and reliable as an organization grows …

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 …

College Of Business Prospective Students Application, Caden Bewley, Joseph Morton, Brayden Reddin, Marvin Martinez, Ashlyn Ward

ATU Scholars Symposium

The College of Business wanted a webpage that makes applying to one of their majors more user-friendly. Currently, incoming freshmen tend to choose the wrong major as the application process can be confusing. They needed to reduce the redundancy of inputting information, so they asked for the application on their webpage to auto-fill on Arkansas Tech University's application webpage.

Graduate Faculty Directory, Christopher Andrews, Cody Mckenney, Drake Traylor, Joseph Freeman

ATU Scholars Symposium

The Graduate College would like to update the current faculty search page to filter search results by Department and Research in addition to Name. With the current system, a person who wanted to find an unknown professor based upon a department or an interest in research topic would be unable to search because the only option is to type the professor's name. We have created a website linked to a database containing graduate faculty that is able to search by name, filter by department, and search through the professors' listed research topics. This website will be much more useful and …

Encrypted Malicious Network Traffic Detection Using Machine Learning, Niklas Knipschild

Symposium of Student Scholars

The research project aims to find ways to detect malicious packets inside encrypted network traffic. In addition to this goal maintaining user privacy is a priority. As encryption has become less expensive to implement more and more network traffic is encrypted. Currently, 90% of all network traffic is encrypted, and this trend is expected to increase. The creators of malware areemploying various methods to ensure delivery of their malware, including encryption. One proposed method to combat this suggests implementing machine learning with various algorithms to analyze packet attributes to determine if they contain malware, without actually knowing what's inside …

Ransomware: Evaluation Of Mitigation And Prevention Techniques, Juanjose Rodriguez-Cardenas

Symposium of Student Scholars

Ransomware is classified as one of the main types of malware and involves the design of exploitations of new vulnerabilities through a host. That allows for the intrusion of systems and encrypting of any information assets and data in order to demand a sum of payment normally through untraceable cryptocurrencies such as Monero for the decryption key. This rapid security threat has put governments and private enterprises on high alert and despite evolving technologies and more sophisticated encryption algorithms critical assets are being held for ransom and the results are detrimental, including the recent Colonial Pipeline ransomware attack in 2021 …

A Study Of Iot-Optimized Low Power Asset Tracking With Cloud-Enabled Lorawan, Fatima Salman

Symposium of Student Scholars

The world of technology is expanding very quickly today, including technologies like cloud-based asset monitoring, but this makes it difficult to keep up with this technology's development and many other things. It is possible to monitor and manage your assets remotely with a cloud-based system thanks to its many features. The lifecycle of any commodity, including inventory, machinery, vehicles, and real estate, can be tracked using this kind of cloud-based system. Wide-area networks can be used to send data with the aid of low-power wide-area network (LPWAN) technologies like LoRa, SigFox, and NB-IoT. This project will examine traditional, cloud-based, LPWAN-based …

Models Of Team Structure In Information Security Incident Investigation, Fayzullajon Botirov

Chemical Technology, Control and Management

This article discusses the models of the group structure in the investigation of information security incidents, contradictions in the investigation of information security incidents, methods for assessing information security incidents at the enterprise, processes for assessing information security incidents based on its factors.

Detection Optimization Of Rare Attacks In Software-Defined Network Using Ensemble Learning, Ahmed M. El-Shamy, Nawal A. El-Fishawy, Gamal M. Attiya, Mokhtar Ahmed

Mansoura Engineering Journal

Software-defined networking (SDN) is a highly flexible architecture that automates and facilitates network configuration and management. Intrusion detection systems (IDS) are becoming essential components in the network to detect malicious attacks and suspicious activities by continuously monitoring network traffic. Integration between SDN and machine learning (ML) techniques is extensively used to build an effective IDS against all potential cyber-attacks that aim at breaking the network security policy and stealing valuable data. Implementing an IDS based on SDN and ML has the advantage of managing traffic dynamically and fully autonomously to provide high protection against security threats. The main objective of …

Ransomware: What Is Ransomware, And How To Prevent It, Brandon Chambers

Cybersecurity Undergraduate Research Showcase

This research paper answers the question, “What is Ransomware, and How to prevent it?”. This paper will discuss what ransomware is, its history about ransomware, how ransomware attacks Windows systems, how to prevent ransomware, how to handle ransomware once it is already on the network, ideas for training professionals to avoid ransomware, and how anti-virus helps defend against ransomware. Many different articles, case studies, and professional blogs will be used to complete the research on this topic.

Enhancing Neural Text Detector Robustness With Μattacking And Rr-Training, Gongbo Liang, Jesus Guerrero, Fengbo Zheng, Izzat Alsmadi

Computer Science Faculty Publications (Archived)

With advanced neural network techniques, language models can generate content that looks genuinely created by humans. Such advanced progress benefits society in numerous ways. However, it may also bring us threats that we have not seen before. A neural text detector is a classification model that separates machine-generated text from human-written ones. Unfortunately, a pretrained neural text detector may be vulnerable to adversarial attack, aiming to fool the detector into making wrong classification decisions. Through this work, we propose µAttacking, a mutation-based general framework that can be used to evaluate the robustness of neural text detectors systematically. Our experiments demonstrate …

Region-Specified Inverse Design Of Absorption And Scattering In Nanoparticles By Using Machine Learning, Alex Vallone, Nooshin M. Estakhri, Nasim Mohammadi Estrakhri

Engineering Faculty Articles and Research

Machine learning provides a promising platform for both forward modeling and the inverse design of photonic structures. Relying on a data-driven approach, machine learning is especially appealing for situations when it is not feasible to derive an analytical solution for a complex problem. There has been a great amount of recent interest in constructing machine learning models suitable for different electromagnetic problems. In this work, we adapt a region-specified design approach for the inverse design of multilayered nanoparticles. Given the high computational cost of dataset generation for electromagnetic problems, we specifically investigate the case of a small training dataset, enhanced …

Game Based Learning: Engaging Students And Measuring Their Progress, Jonathan Stover, Siegwart Mayr

Campus Research Month

Digital natives are constantly surrounded by technology. Therefore, traditional methods of teaching are becoming obsolete and increasingly creative solutions are required to keep students engaged. Among these solutions is a concept called game based learning. Game based learning is a unique educational experience that incorporates the engagement factors of video games with education. Even though it is still in an early stage of adoption, game based learning has been proven to be a surprisingly effective tool for providing students with a valuable educational experience. Even with this evidence in mind, current game based learning programs still hold the potential to …