Computer Sciences Commons^™

Gr-70 Defending Data Reconstruction Through Adaptive Image Augmentation, Seunghyeon Shin

C-Day Computing Showcase

In this paper, we introduce a data augmentation-based defense strategy for preventing the reconstruction of training data through the exploitation of stolen model gradient. The collection of training data to a centralized server has been required for the training of neural networks in traditional machine learning. However, as privacy becomes a significant concern, the concept of Federated learning is introduced. In federated learning, a centralized server shares the well-trained neural network and participating end-users send the gradient back to the server after training without sharing the sensitive data itself. As the concept of federated learning does not share the original …

Uc-12 Comprehensive Security Solution For Small E-Commerce Business, Patrick Mccollums, Hristo Bakalov, Philinda Morse, Tyler Phillips, Watson Day

C-Day Computing Showcase

Project Description: Create an e-commerce server and a comprehensive security program to protect a web server for a simulated small business. This server will include security tools such as intrusion detection, firewall, and network monitoring. The installation and maintenance of this solution will be documented as part of the final documentation package. The server will be reviewed for exploitation from other teams while we attempt the exploitation of their server(s). Research/Motivation: How to research, install, configure, and integrate various open-source software packages for information security, e-commerce, web hosting, and database. Our motivation for this project was to create and secure …

Uc-15 Malware Analysis Using Reverse Engineering, Shamour Jones, Cynthia S Marcellus, Andy Pham, Nathan Rowe, Joshua Rowland

C-Day Computing Showcase

The motivation for this project is driven by evaluation of the different tools on the market that allow for breaking down executables or binary files, and understanding what the malware is doing. By reverse-engineering the malware, we can understand its impact and how to protect against it. Our focus is to understand where different tools are stronger than others, as well as understand the evolving landscape of malware and security overall. For this capstone project, we utilized two different tools and many sample malware files. The methods used to debug the malware are detailed in our milestone two report and …

Uc-20 Analyzing Concentration Levels In Online Education Using Machine Learning, Gray Daugherty, Rachel W Lawson, Kyle C. Ensley, Michael Chann, Tobi Adams

C-Day Computing Showcase

These past few years have introduced the most important time in history to study new faucets of online learning. Due to COVID's impact, online learning became a staple in millions of homes across the country. Guided by the research question, “Can a machine learning model be created and trained to detect student concentration level based on eye and facial data?”, we set out to contribute to society’s understanding of online learning under the guidance of Dr. Ying Xie and Dr. Linh Le. Our process involved recording ourselves participating in online classes to garnish eye and facial data. Each student recorded …

Uc-25 Woodline Interiors Project Planning Application, Beniamin Costea, Iram Nawaz, Natan Beraki, Daniel Lopez, Carter Richter, Yeonkuk Woo

C-Day Computing Showcase

Meeting with the client regularly, we’ve established one of the many solutions to their requirements. The client, WoodLine Interiors, needs a well-designed system that can solve product management, client communication, and project management. The main issue that the company is facing is in the area of managing multiple projects and tracking project progress. Their issue is commonly addressed by a large number of companies that create software solutions, but it’s not personalized for their appropriate needs in the field of cabinetry. As a result our solution created the perfect stages and states of the project so there is no more …

Uc-30 Malware Analysis Using Reverse Engineering, William K Pharr, Kelton Reid, Icyss M Strong, Michael R Lewis

C-Day Computing Showcase

Cybercrimes are a billion-dollar industry that is rapidly growing by the day. One of the biggest threats faced by companies is the infection of malware. New forms of malware are created daily and ever evolving to evade detection methods. Understanding how malware infects your system and how it eludes detection is crucial to keeping a company's network and devices safe. During this project we will be using reverse engineering methods to better understand the functionality of malware, as well as how it eludes detection. We will be using IDAPro and WiDbg to perform the reverse engineering. Using this knowledge, we …

Gr-38 Energy Cost And Efficiency On Edge Computing: Challenges And Vision, Kousalya Banka

C-Day Computing Showcase

The Internet of Things (IoT) has been the key for many advancements in next-generation technologies for the past few years. With a conceptual grouping of ecosystem elements such as sensors, actuators, and smart objects connected to perform complex operations to perform environmental monitoring, intelligent transport system, smart building, smart cities, and endless other possibilities. Edge computing helps the IoT’s reach even further and be more robust by connecting multiple censored devices through the internet and forming powerful computational capabilities. Unfortunately, this computation level comes at a cost as the devices are constantly being used to communicate and perform specific actions. …

Uc-57 Cultiva- The Plant Companion, Travis R Hescox, Kat Branham, Ahsan Jamal, Joseph Henggeler, Erick Reyes, Andy Alcaraz, Momodou Mbye

C-Day Computing Showcase

The goal of this project is to improve the lives of gardeners or everyday people with a green thumb by providing them with a planter that will not only hold their plant of choice, but also give them information about the health and growth of their plant without them having to interact with it directly. This project will provide the user with a planter containing sensors that communicate with an application from which the user can monitor the environment of the plant. This project can serve a wide range of people from first-time gardeners to seasoned veterans. Users will no …

Uc-59 Analyzing Concentration Levels In Online Learning With Facial Values, Elliott J Witherell, Jakeira Askew, Jonathan R Dicks, Steven C Mcguire, Jacob A Walton

C-Day Computing Showcase

Can deep learning models accurately predict whether an individual is focused or distracted on a task in order to improve learning efficiency? In the context of online learning with the use of a webcam, this project is aimed at detecting concentration levels of students to potentially assist with improving learning efficiency. Machine learning technologies have been utilized to evaluate students’ facial expression and eye movements to identify whether a student is focused or distracted. The machine learning branch that is employed is a supervised learning model. This supervised learning model makes predictions based on given input features. A total of …

Uc-6 Covid-19 Data Analysis - Regression, Noah Druss

C-Day Computing Showcase

Covid-19 has been arguably the most impactful event in the past century. SARS-Cov-2 is a viral respiratory illness discovered in late 2019 that has spread to almost every country in the world. It has directly or indirectly affected just about everybody in the world greatly, causing over 117 million cases and 2.59 million deaths as of March 2021. This project has focused on the use of different types of linear regression to both analyze and predict Covid-19 infection data based on different features. First, simple linear regression was used to predict total deaths based on infections both globally and by …

Uc-62 Machine Learning: Twitter Bots In Disguise, Matthew Joseph Scheer, Nicolas Vasquez, James C Andersen, Joshua Tiangco, Justin Van, Cody R Walicek, Daniel Rimmel

C-Day Computing Showcase

This project was designed to help fight against misinformation spread by bots(computers), the goal assigned to us was to find and inform Twitter users of bots that follow and are being followed by the user.Advisors(s): Dr. Reza PariziTopic(s): Artificial IntelligenceSWE 4724

Uc-69 Team 10b Bchain, Jonathan D Lashgari, Carlos A Diaz, Jeffery Erhunse, Caleb T Goff, Giang T Nguyen

C-Day Computing Showcase

BChain is a new P2P file sharing system that is fully private, anonymous, globally self-verifying, and utilizes an automatic peer-maintained network of trust in data, accomplished through new methods of routing content over the whole network, encrypted, rather than per torrent download. Verification is done by adding file metadata to a blockchain giving the network consistent knowledge of each file it can transfer, and how to verify file received against the network. This enables a policy of zero trust against peers. This system is implemented by an app that interfaces with the network using the protocol, using it for upload, …

Ur-41 The Accessibility Of The Mobile Gaming Platform For The Visually Impaired, Christian Thomas Jansen

C-Day Computing Showcase

The motivation for this project is to research mobile gaming interfaces with the goal of conceptualizing practices in game design that would create more accessible interfaces for the visual impairment community. Thus far, the project has focused on practices that mobile game designers can use to make their games more accessible to the visually impaired. These includes the use of plain text rather than graphics to be scannable by screen readers, the inclusion of audio-oriented support and instruction, the use of contrasting colors to make options more recognizable to those with partial visual impairments, and the implementation of game mechanics …

Ur-46 Breastnet;, Cora L Meador, Ryan Deem

C-Day Computing Showcase

In the United states, 13% of women are diagnosed with breast cancer in their lifetime, and it is the second leading cause of death by cancer in women. Early detection and screening can result in an increase of life expectancy by 10 years on average. Unfortunately, breast cancer can be challenging to detect, since it can appear anywhere in the breast. Cancer that is detected in its early stages can give patients more options and save thousands of dollars in medical costs. Some of the most recent developments in computer science and machine learning are in the biomedical field, especially …

Kennesaw State University Research Computing Facilities And Resources, Tom Boyle, Ramazan Aygun

Training Materials, User Guides, and Documentation

The Kennesaw State University High Performance Computing (HPC) resources represent the University’s commitment to research computing. This resource contains verbiage for users of Kennesaw State University's HPC resources to include in their grants and publications. Please use the recommended citation rather than including the listed authors in the your citations.

The current version was published Fall 2023. Previous versions can be found below.

A Predictive Model For Diabetes Using Machine Learning Techniques (A Case Studyof Some Selected Hospitals In Kaduna Metropolis), A E. Evwiekpaefe, Nafisat Abdulkadir

Master of Science in Computer Science Theses

Diabetes Mellitus (DM) which refers to a metabolic disorder that occurs when the level of blood sugar in the body is considered high, which could be a resulting effect of inadequate availability of insulin in the body. It is a chronic disease which may lead to myriads of complications in the body system. Statistics by the World Health Organization (WHO) in 2013, indicated that DM was the cause of death of over 1.5 million people around the world and in 2016, 8.5% of adults within age seventeen (17) and above were reported to be diabetic and diabetic patients have continued …

Gophish: Implementing A Real-World Phishing Exercise To Teach Social Engineering, Andy Luse, Jim Burkman

Journal of Cybersecurity Education, Research and Practice

Social engineering is a large problem in our modern technological world, but while conceptually understood, it is harder to teach compared to traditional pen testing techniques. This research details a class project where students implemented a phishing exercise against real-world targets. Through cooperation with an external corporate partner, students learned the legal, technical, behavioral, analysis, and reporting aspects of social engineering. The outcome provided both usable data for a real-world corporation as well as valuable educational experience for the students.

Applying High Impact Practices In An Interdisciplinary Cybersecurity Program, Brian K. Payne, Lisa Mayes, Tisha Paredes, Elizabeth Smith, Hongyi Wu, Chunsheng Xin

Journal of Cybersecurity Education, Research and Practice

The Center for Cybersecurity Education and Research at Old Dominion University has expanded its use of high impact practices in the university’s undergraduate cybersecurity degree program. Strategies developed to promote student learning included learning communities, undergraduate research, a robust internship program, service learning, and electronic portfolios. This paper reviews the literature on these practices, highlights the way that they were implemented in our cybersecurity program, and discusses some of the challenges encountered with each practice. Although the prior literature on high impact practices rarely touches on cybersecurity coursework, the robust evidence of the success of those practices provides a sound …

An Assessment Of Internet Use And Cyber-Risk Prevalence Among Students In Selected Nigerian Secondary Schools, Adeola O. Opesade Dr, Abiodun O. Adetona Mr

Journal of Cybersecurity Education, Research and Practice

The use of the Internet has become highly pervasive among adolescents. While these people derive numerous benefits from their use of this technology, they are also faced with a challenge of being exposed to many cyber risks. Nigeria is a developing country with a teeming population of adolescents who are regular users of the Internet, but with inadequate research on adolescent Internet safety. There is therefore, a need to conduct studies on child online risks in Nigeria, to help evaluate the enormity of child online abuses. The present study investigated Internet use and cyber-risk prevalence among four hundred secondary school …

From The Editors, Michael E. Whitman, Herbert J. Mattord, Hossain Shahriar

Journal of Cybersecurity Education, Research and Practice

A commentary from the editors, with an overview of the articles contained in this issue of the Journal.

A Serious Game For Social Engineering Awareness Creation, Fabian Muhly, Philipp Leo, Stefano Caneppele

Journal of Cybersecurity Education, Research and Practice

Social engineering is a method used by offenders to deceive their targets utilizing rationales of human psychology. Offenders aim to exploit information and use them for intelligence purposes or financial gains. Generating resilience against these malicious methods is still challenging. Literature shows that serious gaming learning approaches are used more frequently to instill lasting retention effects. Serious games are interactive, experiential learning approaches that impart knowledge about rationales and concepts in a way that fosters retention. In three samples and totally 97 participants the study at hand evaluated a social engineering serious game for participants’ involvement and instruction compliance during …

A Federated Deep Autoencoder For Detecting Iot Cyber Attacks, Christopher M. Regan

Master of Science in Computer Science Theses

Internet of Things (IoT) devices are mass-produced and rapidly released to the public in a rough state. IoT devices are produced by various companies satisfying various goals, such as monitoring the environment, senor trigger cameras, on-demand electrical switches. These IoT devices are produced by companies to meet a market demand quickly, producing a rough software solution that customers or other enterprises willingly buy with the expectation they will have software updates after production. These IoT devices are often heterogeneous in nature, only to receive updates at infrequently intervals, and can remain out of sight on a home or office network …

A Preliminary Analysis Of How A Software Organization’S Maturity And Size Affect Its Intellectual Property Portfolio, Daniel Gifford

Master of Science in Software Engineering Theses

Intellectual property, commonly known as IP, is complex. The four main types of software IP, which is what this thesis will focus on, are patents, trade secrets, trademarks, and copyright. Patents, trade secrets, and copyrights were all studied by this thesis. Software IP is unique in that it can by copyrighted. Different IP owners, which can be businesses of different types, individuals, and universities, often have different strategies as to how to use their IP portfolio. This thesis studies differences in IP usage between these entities specifically in the field of software. Large and small software companies were analyzed specifically. …

An Analysis Of The Effectiveness Of Cuban Cyberactivism, Neta Kanny

Journal of Global Initiatives: Policy, Pedagogy, Perspective

This article applies power-law degree distribution and network theory as a conceptual framework for assessing the effectiveness of Cuban cyberactivism based on an analysis of previous scholarly work on the topic. While Cuban cyberactivism indicates the potential for a more accessible, just, and transparent media environment, the movement continues to face serious obstacles due to extensive controls put in place by the Communist Party of Cuba.

Contingency Planning Amidst A Pandemic, Natalie C. Belford

KSU Proceedings on Cybersecurity Education, Research and Practice

Proper prior planning prevents pitifully poor performance: The purpose of this research is to address mitigation approaches - disaster recovery, contingency planning, and continuity planning - and their benefits as they relate to university operations during a worldwide pandemic predicated by the Novel Coronavirus (COVID-19). The most relevant approach pertaining to the University’s needs and its response to the Coronavirus pandemic will be determined and evaluated in detail.

Developing An Ai-Powered Chatbot To Support The Administration Of Middle And High School Cybersecurity Camps, Jonathan He, Chunsheng Xin

KSU Proceedings on Cybersecurity Education, Research and Practice

Throughout the Internet, many chatbots have been deployed by various organizations to answer questions asked by customers. In recent years, we have been running cybersecurity summer camps for youth. Due to COVID-19, our in-person camp has been changed to virtual camps. As a result, we decided to develop a chatbot to reduce the number of emails, phone calls, as well as the human burden for answering the same or similar questions again and again based on questions we received from previous camps. This paper introduces our practical experience to implement an AI-powered chatbot for middle and high school cybersecurity camps …

A Survey Of Serious Games For Cybersecurity Education And Training, Winston Anthony Hill Jr., Mesafint Fanuel, Xiaohong Yuan, Jinghua Zhang, Sajad Sajad

KSU Proceedings on Cybersecurity Education, Research and Practice

Serious games can challenge users in competitive and entertaining ways. Educators have used serious games to increase student engagement in cybersecurity education. Serious games have been developed to teach students various cybersecurity topics such as safe online behavior, threats and attacks, malware, and more. They have been used in cybersecurity training and education at different levels. Serious games have targeted different audiences such as K-12 students, undergraduate and graduate students in academic institutions, and professionals in the cybersecurity workforce. In this paper, we provide a survey of serious games used in cybersecurity education and training. We categorize these games into …

Factors That Influence Hipaa Secure Compliance In Small And Medium-Size Health Care Facilities, Wlad Pierre-Francois, Indira Guzman

KSU Proceedings on Cybersecurity Education, Research and Practice

This study extends the body of literature concerning security compliance by investigating the antecedents of HIPPA security compliance. A conceptual model, specifying a set of hypothesized relationships between management support, security awareness, security culture; security behavior, and risk of sanctions to address their effect on HIPAA security compliance is presented. This model was developed based on the review of the literature, Protection Motivation Theory, and General Deterrence Theory. Specifically, the aim of the study is to examine the mediating role of risk of sanctions on HIPAA security compliance.

Towards An Assessment Of Pause Periods On User Habituation In Mitigation Of Phishing Attacks, Amy Antonucci, Yair Levy, Martha Snyder, Laurie Dringus

KSU Proceedings on Cybersecurity Education, Research and Practice

Social engineering is the technique in which the attacker sends messages to build a relationship with the victim and convinces the victim to take some actions that lead to significant damages and losses. Industry and law enforcement reports indicate that social engineering incidents costs organizations billions of dollars. Phishing is the most pervasive social engineering attack. While email filtering and warning messages have been implemented for over three decades, organizations are constantly falling for phishing attacks. Prior research indicated that attackers use phishing emails to create an urgency and fear response in their victims causing them to use quick heuristics, …

Towards An Assessment Of Judgment Errors In Social Engineering Attacks Due To Environment And Device Type, Tommy Pollock, Yair Levy, Wei Li, Ajoy Kumar

KSU Proceedings on Cybersecurity Education, Research and Practice

Phishing continues to be a significant invasive threat to computer and mobile device users. Cybercriminals continuously develop new phishing schemes using email, and malicious search engine links to gather personal information of unsuspecting users. This information is used for financial gains through identity theft schemes or draining financial accounts of victims. Users are often distracted and fail to fully process the phishing attacks then unknowingly fall victim to the scam until much later. Users operating mobile phones and computers are likely to make judgment errors when making decisions in distracting environments due to cognitive overload. Distracted users can fail to …