Computer Sciences Commons^™

Uc-209 Remote Presence Robot, Andrew Goeden, Hajar Zemzem, Pamir Ahmad, Tam M. Dang, Aaron Newson, Anna Song, Mohammed Rehaan

C-Day Computing Showcase

A motorized robot that has a screen, microphone, webcam, and speaker to perform video chat capabilities and the ability to move about the environment. The robot will have customization functionalities to add a personal flair for the remote user. A remote user can access a web dashboard to control the robot as if they were in person. This will be good for sick or handicapped people. In addition to the standard web dashboard, we can incorporate a customization aspect for the host user to add filters to their image or stream audio (background blur, soundboard playback, etc.) The robot will …

Uc-223 Gtri: Analysis Of Alternatives (Team 3), Damian G. Coffia, Elijah Brooks, Keegan Fleeman, Sean Richards

C-Day Computing Showcase

Our project focuses on analyzing alternative tools for workstation deployment using operating system imaging software. Our project conducts research on ten different tools available on the market, scoring each based on requirements given to us by a company. After evaluation, three tools are selected for implementation and testing. Once testing is concluded, our group will choose one of the tested tools to recommend for workstation deployment for the company by submitting a full hardware analysis detailing the steps taken to select the tool along with implementation steps for tool deployment.

Ur-159 - A Systematic Literature Review On Dark Web, Shahriar Sobhan, Timothy Williams, Edwin Mathew, Juanjose Rodriguez-Cardenas, Jack Wright, Md Jobair Hossain

C-Day Computing Showcase

The dark web is often discussed in taboo by many who are unfamiliar with the subject. However, this paper takes a dive into the skeleton of what constructs the dark web by compiling the research of published essays. The Onion Router (TOR) and other discussed browsers are specialized web browsers that provide anonymity by going through multiple servers and encrypted networks between the host and client, hiding the IP address of both ends. This provides difficulty in terms of controlling or monitoring the dark web, leading to its popularity in criminal underworlds. In this work, we provide an overview of …

Ur-191 - Automated Image Colorization Through Efficientnet, Troy W. Cope

C-Day Computing Showcase

Automatic Image Colorization is the procedure of transforming a gray-scale image into a colored image without any human intervention. This field is highly researched and strongly applicable to the real world due to: historic importance, data generation/augmentation, and human satisfaction. The main objective of this research is to develop an artificial intelligence feature extraction method that implements color into a gray-scale image. To solve this problem, I relied on transfer learning through the EfficientNet model. The problem was treated in multiple parts, those being: the processing of images into features, feature extraction using the model, and then colorization via the …

Uc-236 Energy Crisis 1994, Mason T. Prather

C-Day Computing Showcase

Energy Crisis 1994 is an online multiplayer first-person shooter game. The format of the game is 4 versus 4 (with players or AI) in either King of the Hill or Payload competition. There are four playable characters at launch, each based on a unique role. The four roles are Tank, Assault, Recon, and Support. The game is inspired by Team Fortress 2, Overwatch, and Counter-Strike.

Ur-203 - Subject Identification From Off-Angle Iris Image Using Machine Learning, David E. Chavarro, Mahmut Karakaya

C-Day Computing Showcase

This research paper investigates the use of the Squeezenet Machine Learning Neural Network to identify a subject from off-angle iris images. Squeezenet is a convolutional neural network (CNNs) which contains 50x lesser parameters than Alexnet. It allows the model to be trained on the dataset on devices that have limited resources. The training dataset contains Iris images where the gaze angles are at 0 degrees, while the validation dataset uses off-angle images.

Iot Clusters Platform For Data Collection, Analysis, And Visualization Use Case, Soin Abdoul Kassif Baba M Traore

Symposium of Student Scholars

Climate change is happening, and many countries are already facing devastating consequences. Populations worldwide are adapting to the season's unpredictability they relay to lands for agriculture. Our first research was to develop an IoT Clusters Platform for Data Collection, analysis, and visualization. The platform comprises hardware parts with Raspberry Pi and Arduino's clusters connected to multiple sensors. The clusters transmit data collected in real-time to microservices-based servers where the data can be accessed and processed. Our objectives in developing this platform were to create an efficient data collection system, relatively cheap to implement and easy to deploy in any part …

Machine Learning-Oriented Predictive Maintenance (Pdm) Framework For Autonomous Vehicles (Avs): Adopting Blockchain For Pdm Solution, Md Jobair Hossain Faruk, Hossain Shahriar, Maria Valero

Symposium of Student Scholars

Autonomous Vehicles (AVs) refers to smart, connected and multimedia cars with technological megatrends of the fourth industrial revolution (Industry 4.0) and have gained huge strive in today's world. AVs adopt automated driving systems (ADS) technique that permits the vehicle to manage and control driving points without human drivers by utilizing advanced equipment including a combination of sensors, controllers, onboard computers, actuators, algorithms, and advanced software embedded in the different parts of the vehicle. These advanced sensors provide unique inputs to the ADS to generate a path from point A to point B. Ensuring the safety of sensors by limiting maintenance …

Students Certification Management (Scm): Hyperledger Fabric-Based Digital Repository, Md Jobair Hossain Faruk, Hossain Shahriar, Maria Valero

Symposium of Student Scholars

The higher education sector has been heavily impacted financially by the economic downturn caused by the pandemic that has resulted a decline in student enrollments. Finding cost-effective novel technology for storing and sharing student's credentials among academic institutions and potential employers is a demand. Within the current conventional approach, ensuring authentication of a candidate’s credentials is costly and time-consuming which gives burdens to thousands of prospective students and potential employees. As a result, candidates fail to secure opportunities for either delay or non-submission of credentials all over the world. Blockchain technology has the potential for students' control over their credentials; …

Computer Simulation Of Raman Spectra And Mode Assignment: Application To Methane, Oluwaseun Omodemi, Ciara Tyler, Martina Kaledin

Symposium of Student Scholars

This work uses driven molecular dynamics (DMD) method, in conjunction with an analytic PES calculated using MP2/aug-cc-pVDZ energies to identify and assign Raman vibrational modes of methane. Recently, a new linearized approach was proposed for the Polarizability Tensor Surfaces (PTS) that yields a unique solution to the least-squares fitting problem and provides a competitive level of accuracy compared to the non-linear PTS model. We used the previously reported B3LYP/6-31+G(d) molecular geometries for CH₄ and generated a new PTS at the MP2/aug-cc-pVDZ level of theory. The performance of the linearly parametrized functional form for the CH₄ PTS is examined. …

A Review Of Dark Web: Crawling And Discovery Of Information, Timothy Williams, Edwin Matthew, Juanjose Rodriguez-Cardenas, Jack Wright, Hossain Shahriar

Symposium of Student Scholars

The dark web is often discussed in taboo by many who are unfamiliar with the subject. However, this essay takes a dive into the skeleton of what constructs the dark web by compiling the research of published essays. TOR and other discussed browsers are specialized web browsers that provide anonymity by going through multiple servers and encrypted networks between the host and client, hiding the IP address of both ends. This provides difficulty in terms of controlling or monitoring the dark web, leading to its popularity in criminal underworlds.

In this work, we provide an overview of data mining and …

Directional Pairwise Class Confusion Bias And Its Mitigation, Sudhashree Sayenju, Ramazan Aygun Phd, Jonathan Boardman, Duleep Prasanna Rathgamage Don, Yifan Zhang Phd, Bill Franks, Sereres Johnston Phd, George Lee, Dan Sullivan, Girish Modgil Phd

Published and Grey Literature from PhD Candidates

Recent advances in Natural Language Processing have led to powerful and sophisticated models like BERT (Bidirectional Encoder Representations from Transformers) that have bias. These models are mostly trained on text corpora that deviate in important ways from the text encountered by a chatbot in a problem-specific context. While a lot of research in the past has focused on measuring and mitigating bias with respect to protected attributes (stereotyping like gender, race, ethnicity, etc.), there is lack of research in model bias with respect to classification labels. We investigate whether a classification model hugely favors one class with respect to another. …

Experimental Study To Assess The Impact Of Timers On User Susceptibility To Phishing Attacks, Amy E. Antonucci, Yair Levy, Laurie P. Dringus, Martha Snyder

Journal of Cybersecurity Education, Research and Practice

Social engineering costs organizations billions of dollars. It exploits the weakest link of information systems security, the users. It is well-documented in literature that users continue to click on phishing emails costing them and their employers significant monetary resources and data loss. Training does not appear to mitigate the effects of phishing much; other solutions are warranted. Kahneman introduced the concepts of System-One and System-Two thinking. System-One is a quick, instinctual decision-making process, while System-Two is a process by which humans use a slow, logical, and is easily disrupted. The key aim of our experimental field study was to investigate …

Faculty And Advisor Advice For Cybersecurity Students: Liberal Arts, Interdisciplinarity, Experience, Lifelong Learning, Technical Skills, And Hard Work, Brian K. Payne, Bria Cross, Tancy Vandecar-Burdin

Journal of Cybersecurity Education, Research and Practice

The value of academic advising has been increasingly emphasized in higher education. In this study, attention is given to the most significant types of advice that a sample of cybersecurity faculty and advisors from the Commonwealth of Virginia recommend giving to cybersecurity students. The results show that faculty and advisors recommended that students be aware of six different aspects of cybersecurity education including the value of experience, the need for lifelong learning, the importance of hard work, the need to develop technical skills, the interdisciplinary nature of cybersecurity, and the need to develop liberal arts or professional/soft skills. Implications of …

Subject Matter Experts’ Feedback On Experimental Procedures To Measure User’S Judgment Errors In Social Engineering Attacks, Tommy Pollock, Yair Levy, Wei Li, Ajoy Kumar

Journal of Cybersecurity Education, Research and Practice

Distracted users can fail to correctly distinguish the differences between legitimate and malicious emails or search engine results. Mobile phone users can have a more challenging time identifying malicious content due to the smaller screen size and the limited security features in mobile phone applications. Thus, the main goal of this research study was to design, develop, and validate a set of field experiments to assess user’s judgment when exposed to two types of simulated social engineering attacks: phishing and Potentially Malicious Search Engine Results (PMSER), based on the interaction of the environment (distracting vs. non-distracting) and type of device …

A Taxonomy Of Cyberattacks Against Critical Infrastructure, Miloslava Plachkinova, Ace Vo

Journal of Cybersecurity Education, Research and Practice

The current study proposes a taxonomy to organize existing knowledge on cybercrimes against critical infrastructure such as power plants, water treatment facilities, dams, and nuclear facilities. Routine Activity Theory is used to inform a three-dimensional taxonomy with the following dimensions: hacker motivation (likely offender), cyber, physical, and cyber-physical components of any cyber-physical system (suitable target), and security (capable guardian). The focus of the study is to develop and evaluate the classification tool using Design Science Research (DSR) methodology. Publicly available data was used to evaluate the utility and usability of the proposed artifact by exploring three possible scenarios – Stuxnet, …

The 2020 Twitter Hack – So Many Lessons To Be Learned, Paul D. Witman, Scott Mackelprang

Journal of Cybersecurity Education, Research and Practice

In mid-July 2020, the social media site Twitter had over 100 of its most prominent user accounts start to tweet requests to send Bitcoin to specified Bitcoin wallets. The requests promised that the Bitcoin senders would receive their money back doubled, as a gesture of charity amidst the COVID-19 pandemic. The attack appears to have been carried out by a small group of hackers, leveraging social engineering to get access to internal Twitter support tools. These tools allowed the hackers to gain full control of the high-profile user accounts and post messages on their behalf. The attack provides many paths …

Editorial Vol 2021, No 2, Herbert J. Mattord, Michael E. Whitman, Hossain Shahriar

Journal of Cybersecurity Education, Research and Practice

Welcome to the Winter 2021 edition of the Journal for Cybersecurity Education, Research, and Practice.

Explainabilityaudit: An Automated Evaluation Of Local Explainability In Rooftop Image Classification, Duleep Rathgamage Don, Jonathan Boardman, Sudhashree Sayenju, Ramazan Aygun, Yifan Zhang, Bill Franks, Sereres Johnston, George Lee, Dan Sullivan, Girish Modgil

Published and Grey Literature from PhD Candidates

Explainable Artificial Intelligence (XAI) is a key concept in building trustworthy machine learning models. Local explainability methods seek to provide explanations for individual predictions. Usually, humans must check these explanations manually. When large numbers of predictions are being made, this approach does not scale. We address this deficiency for a rooftop classification problem specifically with ExplainabilityAudit, a method that automatically evaluates explanations generated by a local explainability toolkit and identifies rooftop images that require further auditing by a human expert. The proposed method utilizes explanations generated by the Local Interpretable Model-Agnostic Explanations (LIME) framework as the most important superpixels of …

The Impact Of A Gencyber Camp On In-Service Teachers’ Tpack, Kevin M. Thomas, Jessica Ivy, Kristin Cook, Robert R. Kelley

Journal of Cybersecurity Education, Research and Practice

The purpose of this study was to examine the impact of a GenCyber camp curriculum on teachers’ technology, pedagogy, and content knowledge (TPACK). The camp was designed to engage participants in developing the knowledge and skills to incorporate GenCyber Cybersecurity First Principles and GenCyber Cybersecurity Concepts (GenCyber, 2019) into their curriculums. Participants (37 middle and high school teachers from a variety of disciplines) attended one of two weeklong camps held at a Midwestern liberal arts university. Using the TPACK Self-Reflection and TPACK Self-Assessment Surveys, pre- and post-camp data were collected from participants. Findings indicate that participants demonstrated an increase in …

Toward A Student-Ready Cybersecurity Program: Findings From A Survey Of Stem-Students, Lora Pitman, Brian K. Payne, Tancy Vandecar-Burdin, Lenora Thorbjornsen

Journal of Cybersecurity Education, Research and Practice

As the number of available cybersecurity jobs continues to grow, colleges strive to offer to their cybersecurity students an environment which will make them sufficiently prepared to enter the workforce after graduation. This paper explores the academic and professional needs of STEM-students in various higher education institutions across Virginia and how cybersecurity programs can cater to these needs. It also seeks to propose an evidence-based approach for improving the existing cybersecurity programs so that they can become more inclusive and student-ready. A survey of 251 college students in four higher-education institutions in Virginia showed that while there are common patterns …

Editorial, Michael E. Whitman, Herbert J. Mattord, Hossain Shahriar

Journal of Cybersecurity Education, Research and Practice

Since 2016, it has been the mission of the Journal of Cybersecurity Education, Research, and Practice (JCERP) to be a premier outlet for high-quality information security and cybersecurity-related articles of interest to teaching faculty and students. This is the 13^th edition of the (JCERP) and, as ever, we are seeking authors who produce high-quality research and practice-oriented articles focused on the development and delivery of information security and cybersecurity curriculum, innovation in applied scholarship, and industry best practices in information security and cybersecurity in the enterprise for double-blind review and publication. The journal invites submissions on Information Security, Cybersecurity, …

Gr-078 - Ai For Social Good: Assisting The Elderly/Visually Impaired In Reading Prescription Labels, Stacie P. Allen, Jessica Barnes, Lauren Pope, Chennelle Hill

C-Day Computing Showcase

No abstract provided.

Gr-083 - Analysis Of Malware Detection Techniques, Joel Stansbury, Robert White, Keifer Bazan

C-Day Computing Showcase

No abstract provided.

Gr-114 - Decentralized Network Architecture On Git Platform, Jonathan D. Lashgari, Kiran Mai M. Narnavaram, Rohit Gowru

C-Day Computing Showcase

No abstract provided.

Gr-104 - Diabetic Retinopathy Detection Using Deep Neural Networks Without Pre-Processing Techniques, Suman Bharti, Swetha Pailla

C-Day Computing Showcase

No abstract provided.

Gr-121 - Binary Image Processing For Computation Of Connected Components, Image Holes And Euler Number Using Graph Theory, Sravya Sabbu, Prasuna Reddy Salepela, Yamini Hanisha Talluri, Sruthi Vaidyula

C-Day Computing Showcase

No abstract provided.

Gr-129 - Using Machine Learning Techniques For Early Alzheimer’S Disease Detection, Sudarshan Badireddi, Shalaka Kulal, Gayatri Sravanthi Kuntla, Travis Meeks

C-Day Computing Showcase

No abstract provided.

Gr-131 - Privacy Preserved Federated Learning Approach For Diabetic Retinopathy Detection, Mohammad Nasajpour

C-Day Computing Showcase

No abstract provided.

Gr-095 - Using Machine Learning To Detect Alzheimer's Disease, Rhema Razzak, Yang Fu

C-Day Computing Showcase

No abstract provided.