Digital Commons Network^™

An Interdisciplinary Approach To Experiential Learning In Cyberbiosecurity And Agriculture Through Workforce Development, Kellie Johnson, Tiffany Drape, Joseph Oakes, Joseph Simpson, Ann Brown, Donna M. Westfall-Rudd, Susan Duncan

Journal of Cybersecurity Education, Research and Practice

Cyberbiosecurity and workforce development in agriculture and the life sciences (ALS) is a growing area of need in the curriculum in higher education. Students that pursue majors related to ALS often do not include training in cyber-related concepts or expose the ‘hidden curriculum’ of seeking internships and jobs. Exposing students through workforce development training and hands-on engagement with industry professionals can provide learning opportunities to bridge the two and is an area of growth and demand as the workforce evolves. The objectives of this work were 1) to learn key concepts in cybersecurity, including data security, visualization, and analysis, to …

Evocative And Provocative Image-Making In The Age Of Generative Ai, Julian Kilker

Tradition Innovations in Arts, Design, and Media Higher Education

Editorial for inaugural AI-focused special issue of Tradition-Innovations in Arts, Design, and Media Higher Education, published under the auspices of the Alliance for the Arts in Research Universities (a2ru). Discusses three articles by five authors in this issue: (1) Choreographing Shadows: Interdisciplinary collaboration to orchestrate ethical image-making by Mark Burchick and Diana Pasulka; (2) Giving Up Control: Hybrid AI-augmented workflows for image-making by Joshua Vermillion; and (3) Hands are Hard: Unlearning how we talk about machine learning in the arts by Adam Hyland and Oscar Keyes.

Editing this special issue explored several key questions: What does “innovation” mean when …

Aroutcrop: An Augmented Reality Mobile Application For Enhancing Geoscience Learning And Comprehension In The Field And Classroom, Benjamin S. Wilkerson, Zachary Wilkerson, M. Scott Wilkerson

Student Research

Most geologists have long recognized the educational value of immersive opportunities and hands-on experiences that teaching geology in the field and using natural rock samples in the classroom offer students. However, these instructional approaches also give rise to distinct logistical and pedagogical challenges. For example, in the field, students sometimes struggle to fully connect concepts, models, and interpretations from classroom lectures with seemingly amorphous masses of rock that they encounter. Or, in the classroom, students may only have limited time for analysis when passing individual hand specimens person-to-person, and may not have access to valuable or fragile samples outside of …

Leading K-12 Community Responsiveness To Cyber Threats Via Education Of School Community, Michele Kielty, A. Renee Staton

Journal of Cybersecurity Education, Research and Practice

Cyber threats have escalated in recent years. Many of these threats have been direct and vicious attacks on K-12 systems. Educators are rarely trained on how to address cyber threats from a systemic and educational perspective when such challenges arise in their school buildings. This article explains the cyber threats that are looming large for K-12 systems and provides concrete tools for school leaders to employ in order to provide preventive education to their school communities.

“After She Fell Asleep, It Went To My Next Podcast, Which Was About A Serial Killer”: Unveiling Needs And Expectations Regarding Parental Control Within Digital Assistant, Prakriti Dumaru, Mahdi Nasrullah Al-Ameen

Computer Science Student Research

Voice-based digital assistants (for brevity, we term them as ‘digital assistants’ in this paper, unless otherwise specified) are getting increasingly popular in the household to automate digital routines. Hence, with communal usage of digital assistants in the household, children can gain access to content through digital assistants that are intended for adult audiences and parents are concerned about such risks. To this end, we created a low-fidelity prototype with designs of existing Google’s parental control for Google Assistant (termed as baseline), along with our features deriving from prior literature (termed as treatment). Then, we …

Understanding The Challenges In Academia To Prepare Nursing Students For Digital Technology Use At Workplace, Ankit Shrestha, Prakriti Dumaru, Rizu Paudel, Mahdi Nasrullah Al-Ameen

Computer Science Student Research

Digital technology has transformed workplaces in recent years. The technology adoption in medical institutions has challenged nurses to evolve in using complex digital systems. However, academic institutions often fail to keep up with the rapid changes in professional practice in preparing their students. To this end, we conducted semi-structured interviews with five nursing faculties in the USA. In our study, we examined the current status of digital technology and privacy education, and identified the challenges in adequately preparing nursing students to embrace and adapt to the changes in digital technology use at healthcare organizations. Overall, our findings provide valuable insights …

"It Doesn't Just Feel Like Something A Lawyer Slapped Together." Mental-Model-Based Privacy Policy For Third-Party Applications On Facebook, Rizu Paudel, Ankit Shrestha, Prakriti Dumaru, Mahdi Nasrullah Al-Ameen

Computer Science Student Research

Users are often unaware of the information that applications collect and are surprised by unexpected data collection and sharing practices. With numerous third-party applications on Facebook potentially accessing the personal information of billions of users, it is essential to understand users’ mental models of data sharing to help them make informed decisions. To achieve this, we conducted semi-structured interviews using drawings and think-aloud protocol with 32 participants. Our participants had misconceptions regarding third-party applications’ data sharing practices with varied mental models. Based on these findings, we created mental model-based privacy policy design that prompts users to consider a specific scenario …

Ai In The College Classroom: From Communication To Animation, Stefanie Powers, Erika Grodzki, Gary Carlin, Hung Chum Kao

Faculty and Staff Publications & Presentations

No abstract provided.

Interval-Valued Fermatean Neutrosophic Shortest Path Problem Via Score Function, Said Broumi, S. Krishna Prabha, Vakkas Uluçay

Neutrosophic Systems with Applications

Contemporary mathematical techniques have been crafted to address the uncertainty of numerous real-world settings, including Fermatean neutrosophic fuzzy set theory. Fermatean neutrosophic fuzzy set is an extension of combining Fermatean and neutrosophic sets. A Fermatean neutrosophic set was developed to enable the analytical management of ambiguous data from relatively typical real-world decision-making scenarios. Decision-makers find it challenging to determine the degree of membership (MG) and non-membership (NG) with sharp values due to the insufficient data provided. Intervals MG and NG are suitable options in these circumstances. In this article, the shortest route issue is formulated using an interval set of …

Deep Learning For Plant Bioinformatics: An Explainable Gradient-Based Approach For Disease Detection, Muhammad Shoaib, Babar Shah, Nasir Sayed, Farman Ali, Rafi Ullah, Irfan Hussain

All Works

Emerging in the realm of bioinformatics, plant bioinformatics integrates computational and statistical methods to study plant genomes, transcriptomes, and proteomes. With the introduction of high-throughput sequencing technologies and other omics data, the demand for automated methods to analyze and interpret these data has increased. We propose a novel explainable gradient-based approach EG-CNN model for both omics data and hyperspectral images to predict the type of attack on plants in this study. We gathered gene expression, metabolite, and hyperspectral image data from plants afflicted with four prevalent diseases: powdery mildew, rust, leaf spot, and blight. Our proposed EG-CNN model employs a …

Exploring Network Security Educator Knowledge, Jennifer B. Chauvot, Deniz Gurkan, Cathy Horn

Journal of Cybersecurity Education, Research and Practice

It is critical for nations to have trained professionals in network security who can safeguard hardware, information systems, and electronic data. Network security education is a key knowledge unit of the National Centers of Academic Excellence in Cybersecurity and various information systems security curricula at the master's and bachelor's levels in higher education. Network security units are components of computer science curricula in high school contexts as well. Educators who teach these concepts play a significant role in developing a skilled workforce of network security experts for both governmental and non-governmental organizations. Understanding the necessary knowledge and skills of network …

Like Treating The Symptom Rather Than The Cause - The Omission Of Courses Over Terrorism In Nsa Designated Institutions, Ida L. Oesteraas

Journal of Cybersecurity Education, Research and Practice

The National Security Agency (NSA) awards Center of Academic Excellence (CAE) designations to institutions that commit to producing cybersecurity professionals who will work in careers that reduce vulnerabilities in our national infrastructure. A review of the curricula in the 327 institutions and their degree programs reveal that only two programs offer a required course about terrorism. Given the fluid nature of terrorism and its threat to national infrastructure, the omission is concerning. It is recommended that NSA-certified cybersecurity programs begin implementing educational content that aim to teach about this emerging crime and justice issue. One suggestion is to embrace the …

What You See Is Not What You Know: Studying Deception In Deepfake Video Manipulation, Cathryn Allen, Bryson R. Payne, Tamirat Abegaz, Chuck Robertson

Journal of Cybersecurity Education, Research and Practice

Research indicates that deceitful videos tend to spread rapidly online and influence people’s opinions and ideas. Because of this, video misinformation via deepfake video manipulation poses a significant online threat. This study aims to discover what factors can influence viewers’ capability to distinguish deepfake videos from genuine video footage. This work focuses on exploring deepfake videos’ potential use for deception and misinformation by exploring people’s ability to determine whether videos are deepfakes in a survey consisting of deepfake videos and original unedited videos. The participants viewed a set of four videos and were asked to judge whether the videos shown …

Privacy Harm And Non-Compliance From A Legal Perspective, Suvineetha Herath, Haywood Gelman, Lisa Mckee

Journal of Cybersecurity Education, Research and Practice

In today's data-sharing paradigm, personal data has become a valuable resource that intensifies the risk of unauthorized access and data breach. Increased data mining techniques used to analyze big data have posed significant risks to data security and privacy. Consequently, data breaches are a significant threat to individual privacy. Privacy is a multifaceted concept covering many areas, including the right to access, erasure, and rectify personal data. This paper explores the legal aspects of privacy harm and how they transform into legal action. Privacy harm is the negative impact to an individual as a result of the unauthorized release, gathering, …

Cybersecurity Challenges And Awareness Of The Multi-Generational Learners In Nepal, Raj Kumar Dhungana, Lina Gurung Dr, Hem Poudyal

Journal of Cybersecurity Education, Research and Practice

Increased exposure to technologies has lately emerged as one of the everyday realities of digital natives, especially K-12 students, and teachers, the digital immigrants. Protection from cybersecurity risks in digital learning spaces is a human right, but students are increasingly exposed to high-risk cyberspace without time to cope with cybersecurity risks. This study, using a survey (N-891 students and 157 teachers) and in-depth interviews (27 students and 14 teachers), described the students' cybersecurity-related experiences and challenges in Nepal. This study revealed that the school’s cybersecurity support system is poor and teachers has very low awareness and competencies to protect students …

Cybervandalism Detection In Wikipedia Using Light Architecture Of 1d-Cnn, Azha Talal Mohammed Ali, Huda Hallawi, Noor D. Al-Shakarchy

Karbala International Journal of Modern Science

The rapid expansion of human-software-agent interaction has come with new issues. Accordingly, different engage-ments are necessary to adapt to changing human needs in dynamic socio-technical systems. Generally, cybervandalism is the act of leaving any negative impact on any piece of writing in an attempt to modify it. In Wikipedia, vandalism is any attempt to modify an article in a way that negatively affects the article's quality. Recently, several automatic detec-tion techniques and related features have been developed to address this issue. This work introduces a deep learning model with a new and light architecture to detect vandalism in Wikipedia articles. …

Service-Oriented Framework For Developing Interoperable E-Health Systems In A Low-Income Country, Bonface Abima, Agnes Nakakawa, Geoffrey Mayoka Kituyi

The African Journal of Information Systems

e-Health solutions in low-income countries are fragmented, address institution-specific needs, and do little to address the strategic need for inter-institutional exchange of health data. Although various e-health interoperability frameworks exist, contextual factors often hinder their effective adoption in low-income countries. This underlines the need to investigate such factors and to use findings to adapt existing e-health interoperability models. Following a design science approach, this research involved conducting an exploratory survey among 90 medical and Information Technology personnel from 67 health facilities in Uganda. Findings were used to derive requirements for e-health interoperability, and to orchestrate elements of a service oriented …

Yolo And Lsh-Based Video Stream Analytics Landscape For Short-Term Traffic Density Surveillance At Road Networks, Lavanya K, Stuti Tiwari, Rahul Anand, Jude Hemanth

Turkish Journal of Electrical Engineering and Computer Sciences

The duty of monitoring traffic during rush hour is difficult due to the fact that modern roadways are getting more crowded every day. The automated solutions that have already been created in this area are ineffective at processing enormous amounts of data in a short amount of time, leading to ineffectiveness and inconsistent results. The YOLO (you only look once) and LSH (locality sensitive hashing) algorithms are combined with the Kafka architecture in this study to create a method for assessing traffic density in real-time scenarios. Our concept, which is specifically designed for vehicular networks, predicts the traffic density in …

Deep Feature Extraction, Dimensionality Reduction, And Classification Of Medical Images Using Combined Deep Learning Architectures, Autoencoder, And Multiple Machine Learning Models, Ahmet Hi̇dayet Ki̇raz, Fatime Oumar Djibrillah, Mehmet Emi̇n Yüksel

Turkish Journal of Electrical Engineering and Computer Sciences

Accurate analysis and classification of medical images are essential factors in clinical decision-making and patient care. A novel comparative approach for medical image classification is proposed in this study. This new approach involves several steps: deep feature extraction, which extracts the informative features from medical images; concatenation, which concatenates the extracted deep features to form a robust feature vector; dimensionality reduction with autoencoder, which reduces the dimensionality of the feature vector by transforming it into a different feature space with a lower dimension; and finally, these features obtained from all these steps were fed into multiple machine learning classifiers (SVM, …

Synthesizing Sentience: Integrating Large Language Models And Autonomous Agents For Emulating Human Cognitive Complexity, Jay Ratican, James Hutson, Daniel Plate

Faculty Scholarship

The paper aims to present a novel methodology for emulating the intricacies of human cognitive complexity by ingeniously integrating large language models with autonomous agents. Grounded in the theoretical framework of the modular mind theory-originally espoused by Fodor and later refined by scholars such as Joanna Bryson—the study seeks to venture into the untapped potential of large language models and autonomous agents in mirroring human cognition. Recent advancements in artificial intelligence, exemplified by the inception of autonomous agents like Age in GPT, auto GPT, and baby AGI, underscore the transformative capacities of these technologies in diverse applications. Moreover, empirical studies …

Local-Global Support For Earth Sciences: Economic Analysis, Uyen Hoang Pham, Aaron Velasco, Vladik Kreinovich

Departmental Technical Reports (CS)

Most funding for science comes from taxpayers. So, it is very important to be able to convince taxpayers that this funding is potentially beneficial for them. This task is easier in Earth sciences, e.g., in meteorology, where there are clear local benefits. The problem is that while many people support local studies focused on their region, they do not always have a good understanding of the fact that effective local benefits require also studying surrounding areas -- and what should be the optimal balance between local and (more) global studies. In this paper, on a (somewhat) simplified model of the …

Understanding How To Diversify The Cybersecurity Workforce: A Qualitative Analysis, Maria Chaparro Osman, Maureen Namukasa, Cherrise Ficke, Isabella Piasecki, Tj Oconnor, Meredith Carroll

Aeronautics Faculty Publications

A robust cybersecurity workforce is critical for protection against a range of malicious attacks. However, it has been noted that there are many vacancies and a shortage of individuals entering the cybersecurity workforce. The workforce shortage has been partially attributed to the lack of diversity in the cybersecurity domain, with women, African Americans, and Hispanics remaining underrepresented in educational and professional settings. Using a qualitative approach, this work sought to investigate what led underrepresented minorities currently involved in cybersecurity to the industry, with the goal of determining methods to attract underrepresented minorities and diversify the workforce. A thematic analysis was …

Diversity Similarity Join For Big Data, Yasin N. Silva, Juan Martinez, Pedro Castro Cea, Humberto Razente, Maria Camila N. Barioni

Computer Science: Faculty Publications and Other Works

The Similarity Join (SJ) has become one of the most popular and valuable data processing operators in analyzing large amounts of data. Various types of similarity join operators have been effectively used in multiple scenarios. However, these operators usually generate a large output size and many similar output pairs that represent almost the same information. In previous work, a new operator called Diversity Similarity Join (DSJ) has been proposed to address these issues. DSJ generates a smaller scale output and more meaningful and diverse result pairs. This operator, however, was proposed as a single node operator crucially limiting its scalability …

Rigid: Recurrent Gan Inversion And Editing Of Real Face Videos, Yangyang Xu, Shengfeng He, Kwan-Yee K. Wong, Pingluo Luo

Research Collection School Of Computing and Information Systems

GAN inversion is indispensable for applying the powerful editability of GAN to real images. However, existing methods invert video frames individually often leading to undesired inconsistent results over time. In this paper, we propose a unified recurrent framework, named Recurrent vIdeo GAN Inversion and eDiting (RIGID), to explicitly and simultaneously enforce temporally coherent GAN inversion and facial editing of real videos. Our approach models the temporal relations between current and previous frames from three aspects. To enable a faithful real video reconstruction, we first maximize the inversion fidelity and consistency by learning a temporal compensated latent code. Second, we observe …

Smart Homes And You: Iot Device Data Risks In An Ever-Changing World, Autumn Person

Theses and Dissertations

Social media applications are increasingly seen as a national security threat and a cause for concern because they can be used to create user profiles on government personnel and on US citizens. These profiles could be used for big data and artificial intelligence purposes of interest to foreign governments. With the rise of big data and AI being used, foreign governments could use this data for a variety of purposes that can affect normal everyday citizens, not just high value personnel. IoT (Internet of Things) devices that the population uses everyday can also pose the same threat. These devices can …

Docker Technology For Small Scenario-Based Excercises In Cybersecurity, Zeinab Ahmed

Theses and Dissertations

This study aims to better prepare students for cybersecurity roles by providing practical tools that bridge the gap between theory and real-world applications. We investigate the role of small scenario-based exercises for students’ understanding of cybersecurity concepts. In particular, we assess the use of Docker technology to deliver training that includes a simple small scenario on html code injection. The effectiveness of scenario-based learning has long been defined and by using SBL, we are going to create hands-on activity that involves the fundamental topics in cybersecurity using Docker technology, allowing students to see the exploitation of the vulnerabilities and defense …

Attention-Based Human Age Estimation From Face Images To Enhance Public Security, Md. Ashiqur Rahman, Shuhena S. Aonty, Kaushik Deb, Iqbal H. Sarker

Research outputs 2022 to 2026

Age estimation from facial images has gained significant attention due to its practical applications such as public security. However, one of the major challenges faced in this field is the limited availability of comprehensive training data. Moreover, due to the gradual nature of aging, similar-aged faces tend to share similarities despite their race, gender, or location. Recent studies on age estimation utilize convolutional neural networks (CNN), treating every facial region equally and disregarding potentially informative patches that contain age-specific details. Therefore, an attention module can be used to focus extra attention on important patches in the image. In this study, …

A System For The Detection Of Adversarial Attacks In Computer Vision Via Performance Metrics, Sarah Reynolds

Doctoral Dissertations and Master's Theses

Adversarial attacks, or attacks committed by an adversary to hijack a system, are prevalent in the deep learning tasks of computer vision and are one of the greatest threats to these models' safe and accurate use. These attacks force the trained model to misclassify an image, using pixel-level changes undetectable to the human eye. Various defenses against these attacks exist and are detailed in this work. The work of previous researchers has established that when adversarial attacks occur, different node patterns in a Deep Neural Network (DNN) are activated within the model. Additionally, it is known that CPU and GPU …

Deconstructing The Software Factory: A Practical Application Of Interorganizational Network Analysis, Zachary O. Ryan, Mark Reith, Clay Koschnick

Faculty Publications

Over the past 5 years, the number of DoD software organizations that employ nontraditional organizational structures has increased. These organizations, commonly referred to as software factories, often employ the network-based organizational structures found within high-technology industries. This article details ways in which network analysis techniques can be used to create a big picture view of these nontraditional organizations. Drawing on methodologies employed by network researchers, the authors develop and present an interorganizational analysis process that highlights a program's social and economic structures. Following the case history approach, they demonstrate the applicability of this approach by analyzing an emergent DoD software …

Intelligence Versus Inferno: How Artificial Intelligence Can Be Used To Monitor And Manage Wildfires In Europe, Maxwell Feldman

Independent Study Project (ISP) Collection

Escalating wildfire occurrences in Europe, particularly in the southern Mediterranean region, are presenting significant challenges to socioeconomic, environmental, and ecosystem services. The increasing frequency and severity of these wildfires are straining resources and emphasizing the need for a better understanding of the relationship between suppression capacity and fire behavior in wildfire management. The following research addresses the urgent need for more proactive, knowledge-based, and technologically driven fire management strategies, throughout all four stages of wildfire response – fuel and land management, fire preparedness, fire suppression, and post-fire management. Artificial Intelligence (AI) is becoming increasingly significant in climate change adaptation, especially …