Digital Commons Network^™

Ai-Powered Threat Hunting For Email Phishing Attack Detection Using Natural Language Processing (Nlp), Mohd Azriy Akmalhazim Mohd Nazariee, S Prabha Kumaresan, Alaa Haddad, Mohamed Uvaze Ahamed Ayoobkhan

Journal of Informatics and Web Engineering

Phishing attacks remain as a significant cybersecurity threat, aiming to steal sensitive information by exploiting human vulnerability. Traditional phishing email detection often struggles to keep up with the latest attack strategies developed by the attackers which results in high false positive rates and the limited contextual understanding on the email contents. Therefore, to address these challenges, this research proposes a solution via an AI-powered threat-hunting model integrating Natural Language Processing (NLP) techniques for phishing email detection in English through the development of PhishGuard AI application. The application is developed as a web-based software solution designed to be accessible to both …

Ai-Powered Dynamic Encryption And Decryption Defense Model, Chyanne Wen Qian Lor, Ibrahim Yusof, Anang Hudaya Muhamad Amin

Journal of Informatics and Web Engineering

Static cryptographic systems that rely on fixed algorithms and predetermined keys have proven increasingly ineffective in addressing today’s adaptive and AI-powered cyber threats. This paper proposes an Artificial Intelligence (AI)-enabled dynamic encryption and decryption defence model designed to enhance cybersecurity through real-time threat classification and context-aware cryptographic response. The framework combines the Suricata intrusion detection engine with a Random Forest model developed using the CIC-IDS2017 dataset, allowing it to identify and categorize network anomalies into unified groups, including Denial-of-Service (DoS), Distributed Denial of Service (DDoS), Brute Force, and PortScan. Once threats are identified, the system dynamically selects an appropriate encryption …

Gamification By Design: Methodological Foundations Of The Gamespro Speaking Model For Primary Education, Mohd Zulhairi Che Abd Rahman, Hasiah Mohamed, Siti Zulaiha Ahmad, Aurelio P. Vilbar

Journal of Informatics and Web Engineering

This study presents the development and validation of the GAMESPro model, a structured gamification model designed to enhance English-speaking proficiency among Malaysian primary school students. Despite national reforms and policy initiatives aimed at improving communicative competence, oral English skills remain underdeveloped, particularly in rural and resource-constrained schools. Existing gamification practices in Malaysian classrooms often rely on isolated digital tools and lack pedagogical coherence. Addressing this gap, the study employed the Design and Development Research (DDR) methodology, encompassing three phases: Needs Analysis, Design and Development, and Evaluation. A Systematic Literature Review identified key gamification principles, while validation of ten experts confirmed …

The Development Of Decentralized Ticketing System Using Web3, Yu-Xian Cheng, Kah-Ong Michael Goh, Check-Yee Law, Connie Tee, Yong-Wee Sek, Md Ismail Hossen

Journal of Informatics and Web Engineering

Traditional ticketing systems often suffer from major drawbacks such as ticket fraud, duplication, inflated resale prices, lack of transparency, and centralized control over transactions. These issues result in reduced trust and limited flexibility for both event organizers and ticket buyers, especially in unregulated secondary markets. To address these gaps, this paper presents the design and development of a Decentralized Ticketing System (DTS) using Web3 technologies. The system leverages Ethereum blockchain, smart contracts written in Solidity, and NFT-based ticket issuance to ensure security, transparency, and verifiable ownership. Features include wallet-based login via MetaMask, multi-ticket purchasing, QR-based validation, controlled resale pricing, and …

Ai-Driven Intrusion Detection System For Network Security, Zhi Lin Sarah Teoh, Wee How Khoh, Hui Yen Yap, Pin Shen Teh

Journal of Informatics and Web Engineering

In the evolving landscape of cybersecurity, Intrusion Detection Systems (IDS) play a vital role in safeguarding computer networks against malicious activity. Traditional signature-based IDS approaches are increasingly ineffective in detecting novel, complex, or zero-day attacks due to their reliance on predefined rules. To overcome these limitations, this study proposes an AI-driven IDS that integrates both classical machine learning and modern deep learning techniques. The framework introduces and compares three models such as Support Vector Machine (SVM), Convolutional Neural Network (CNN), and a hybrid CNN-SVM model. The system is designed to analyze network traffic patterns and classify them as either benign …

Deep Learning Model For Burn Injury Assessment With Enhanced Diagnosis Rate, C. Pabitha, K. Revathi, R. Krishna Priya

Journal of Informatics and Web Engineering

The skin is considered as the largest organ of our body specifically satisfies the environment. As a result, the skin is vulnerable to various injuries, especially burns. Burns are linked to high rates of morbidity and mortality and can be fatal. Effective diagnosis supported by precise evaluation of the burn area and the depth of wound is critical for enabling efficacy in clinical settings. The characteristics of a burn wound on the skin include: the wound is abnormal, the skin is infected, there is discomfort, the skin is tight, and there are raised areas of skin. To properly diagnose burn …

Editorial: Artificial Intelligence In Healthcare And Wellness — Emerging Frameworks, Intelligent Monitoring, And Precision Medicine, Sellappan Palaniappan

Journal of Informatics and Web Engineering

AI is changing our understanding of health and health-care systems in ways that go beyond the traditional one-click-fits-all approach to care. It is also making care more personalised than ever before, with delivery occurring on an ongoing basis and at all times. The six papers in this special issue of the Journal of Informatics and Web Engineering will give you a clear view of where we are headed. They examine several different areas, including: monitoring chronic illness through wearable technology; using deep learning techniques for contactless heart monitoring via rPPG; developing new cancer risk models; identifying neuroplasticity therapeutic pathways using …

Synthetic Data Generation For Healthcare And Wellness: Methods, Applications, And Future Directions, Sellappan Palaniappan, Kasthuri Subaramaniam, Oras Baker, Bui Ngoc Dung, Sumit Dhariwal

Journal of Informatics and Web Engineering

Artificial intelligence in healthcare relies heavily upon the availability of high-quality datasets, but very rigid privacy regimes, institutional silos, ethical issues, and heterogeneous data still serve to limit the availability of real-world clinical data. To combat these limitations, you focus on synthetic data generation as a privacy-preserving and scalable alternative to traditional data generation for healthcare and wellness studies. More relevant is a work on a broad and clear framework of synthesis methods based on statistical modelling, rule-based generation and domain-specific clinical logic, in contrast to recent studies that mainly target sophisticated methods for the deep learning architectures. The paper …

Ai-Powered Continuous Health Monitoring For Chronic Disease Management In Malaysia: Real-Time Risk Prediction Using Wearable Sensors And Digital Biomarkers, Umi Najiah Ahmad Razimi, Yong Yoke Leng, Nor Hapiza Mohd Ariffin, Mohammed Hazim Alkawaz

Journal of Informatics and Web Engineering

Chronic Non-Communicable Diseases (NCDs), such as diabetes mellitus, hypertension, and cardiovascular disease, make up a significant portion of the mortality cases in Malaysia, as well as impose consistent demands for costs related to health care expenditure. According to the cost reports at the national level, major NCDs (cardiovascular disease, diabetes, and cancer) are responsible for RM 9.65 billion annually as direct healthcare cost [3]. However, the current approach to managing chronic diseases focuses heavily on periodic assessments in clinic setting at weekly or monthly intervals. Here, a predictive analysis framework based on AI technology, leveraging continuous monitoring with patient data …

An Ai-Based Framework For Heart–Brain–Body Coherence In Wellness Monitoring: A Longitudinal Simulation Study, Asiah Lokman, Akalpita Tendulkar, Yujiao Zhang, Mantena Sireesha

Journal of Informatics and Web Engineering

Present wellness monitoring systems primarily emphasize single-modality metrics, neglecting the intricate, interdependent interactions among cardiac, neural, and behavioral regulatory systems. This paper introduces a machine learning framework that implements heart–brain–body coherence as a dynamic, longitudinally evaluated wellness metric. In contrast to previous simulation-based studies that utilized independently generated, cross-sectional data categorized by deterministic IF-THEN rules, the current study adopts a longitudinal simulation design featuring 80 virtual subjects monitored across 30 consecutive daily profiles (N=2,400 records). This design incorporates physiologically realistic inter-variable correlations and probabilistic coherence labelling derived from a continuous risk-scoring function. The subject-level train/test split (56 training subjects, 1,680 …

Intelligent Telemedicine Systems For Contactless Heart Rate Estimation Using Deep Learning-Based Rppg, Do Duc Thinh, Nguyen Duc Manh, Nguyen Thi Bich Ngoc, Vu Van Huan

Journal of Informatics and Web Engineering

Over the last ten years, telemedicine has undergone significant developments, from simple communication-based healthcare to smart and data-driven solutions. The solutions are now powered by Artificial Intelligence (AI), Machine Learning (ML), and Internet of Medical Things (IoMT) technologies. Physiological monitoring is traditionally done with contact-based sensors. The sensors include Electrocardiogram (ECG) and pulse oximeters. The sensors have various disadvantages, including hardware costs, difficulty in continuous usage, and discomfort for patients. Photoplethysmography (rPPG), a remote method of physiological monitoring, is a breakthrough technology. The method is used to estimate physiological signals, including Heart Rate (HR), from video streams captured by standard …

Digital Bodily Autonomy: Consent Issues, Labor Displacement, And Legal Understandings Of Ai Generated Deepfake Pornography, Mariah Barrett

Undergraduate Theses, Capstones, and Recitals

In the United States, nonconsensual pornographic deepfakes are becoming an increasingly prevalent problem as AI deepfake creation software improves and becomes widely available. Despite this, patchwork legislation across the country is inconsistent and conflicting regarding this issue. In this paper, I explore the background of pornography and obscenity laws and demonstrate how these frameworks are not properly constructed to apply to the digital sphere. Then, I address major themes within deepfake literature such as consent issues, bodily autonomy, labor displacement, and verifiable identity as a commodity through the case study of OnlyFans. I explore current and proposed legislation within the …

Data Governance Maturity, Ai Integration, And Equity In Colorado K-12 Public Schools, John R. Curtin

Electronic Theses and Dissertations

Colorado's 179 K-12 public school districts operate as autonomous governance units, each responsible for securing and managing student data assets that span health, financial, residential, and academic records. The accelerating integration of artificial intelligence (AI) and machine learning (ML) tools into administrative workflows, productivity software, and instructional platforms has fundamentally altered the risk landscape for student data, yet governance frameworks at the state, district, and school levels have not kept pace. This dissertation investigates whether Colorado's decentralized educational governance structure is institutionally capable of producing equitable, secure, and sustainable data governance outcomes in the AI era.

Drawing on Institutional Theory …

Ai In Education And Information: Tool, Threat, Or Teammate? How Academia Is Shaping The Future Of Intelligent Work, Essraa Nawar

Library Presentations, Posters, and Audiovisual Materials

Artificial intelligence is rapidly changing the future of intelligent work across education, healthcare, leadership, communication, workplace culture, and health information management. Yet while AI adoption continues accelerating, institutions and professionals are still trying to understand what this transformation actually means for people, learning, careers, ethics, trust, governance, and human judgment. This interactive and forward-thinking panel brings together voices from higher education and healthcare information management to explore how AI is reshaping classrooms, workplaces, healthcare systems, professional identity, and future workforce expectations across generations.

Rather than focusing only on technology itself, the conversation will examine the broader cultural and organizational shift …

Enhanced Uav Surveillance With Rf-Based Drone Identification Using Transfer Learning, Prajoy Podder, Maciej Jan Zawodniok, Sanjay Madria

Electrical and Computer Engineering Faculty Research & Creative Works

With the development of technology and the decrease in costs, drones are now becoming easily accessible to the public. As the accessibility of this technology continues to grow, the concerns of security and surveillance increase, and to ensure a sense of security, the need to have reliable drone detection and identification systems is more urgent than ever. Besides, many civilian applications have been found for drones, which play a huge role in modern security and warfare. Unauthorized drones can be very dangerous regarding security issues, as they can be used for spying, smuggling, or even attacks against critical infrastructure. We …

Predicting Cybermindfulness With The Cyber-Health Belief Model, James Robinson, Yan Tian, Thomas Skill

Journal of Cybersecurity Education, Research and Practice

This study describes the development of a Cyber-Health Belief Model (CHBM). The health belief model (HBM) is a message strategy that is widely and successfully used in public health research [1] and has been extended into phish training. Most phish training programs assume  end users are victimized because they have insufficient information to defend themselves. While near-term training effectiveness has shown to be effective, evidence for sustained behavioral change is thin [4]-[7].  This problem indicates that the traditional approaches need to be reconsidered and that new models are needed.  Recent research suggests attentional deficits, cyber-fatigue and fatalism and a sense …

The Intersection Between Mindfulness And Cybersecurity: A Tool To Reduce Burnout And Improve Operational Effectiveness, Ivo Ricardo Dias Rosa

Journal of Cybersecurity Education, Research and Practice

Abstract: This paper offers a conceptual discussion of how mindfulness, understood as present moment awareness and deliberate attention regulation, can support cybersecurity professionals. Drawing on a narrative synthesis of workplace mindfulness, burnout, and high pressure decision making literature, we map plausible self regulation mechanisms to typical cyber defense tasks. Rather than presenting new empirical data, we develop an explanatory framework linking attention, reactivity, and recovery to decision quality, team communication, and adherence to incident playbooks. We focus on two connected outcomes: reducing burnout in roles with sustained cognitive and emotional demands, and improving operational effectiveness during critical situations such as …

Cyber-Ready Libraries, Building Digital Fortresses For Tomorrow, Adeyinka B. Tella, Oluchi Precious Ogbonna Dr, Adebola Aderemi Olatoye Mrs

Journal of Cybersecurity Education, Research and Practice

Background and Purpose: Libraries are evolving into highly networked information ecosystems in this age of fast digital transformation, which increases their susceptibility to cybersecurity risks. The study "Cyber-Ready Libraries: Building Digital Fortresses for Tomorrow" looks into how prepared libraries are to face cyber threats and considers methods for creating information systems that are safe, robust, and ready for the future. To safeguard digital assets and user data, the study aims to assess existing cybersecurity practices in library settings and offer a roadmap for combining technological, human, and governance solutions.

Design/Method: The existing literature, case studies, and policy frameworks pertaining …

Parent Cultural Wealth: How Beliefs, Curriculum Familiarity, And Community Awareness Facilitate Home-Based Cs Conversations, Nicol Howard, Leiny Y. Garcia, Jean Ryoo, Julie Flapan, Michelle Choi, Paula Nazario, Wei Wei

Mathematics, Physics, and Computer Science Faculty Articles and Research

Parents are critical influences on children's computer science (CS) pathways, yet families’ involvement remains understudied. Guided by parental involvement and community cultural wealth frameworks, this work-in-progress examined survey data from 53 parents representing families historically underrepresented in computing within California (71% women; 54% Hispanic/Latin/x/e). Findings revealed that CS school curriculum familiarity and awareness of CS community events significantly predicted parent-child CS conversations, while parent CS confidence and attitudes did not, suggesting that curriculum transparency and community connections can promote equitable involvement. Future work will integrate qualitative interviews to examine how families draw upon their cultural wealth.

Describing Hidden Curriculum In An Undergraduate Computing Context, Joseph R. Teahen, Briana C. Bettin, Leo Ureel

Michigan Tech Publications

Hidden Curriculum (HC) is the set of essential knowledge, skills, and norms students are expected to know, but never explicitly taught. HC is disproportionately experienced across identities and communities. In computing education, most research addresses immediately identifiable HC within the researcher's context. While such work is important, without proper HC descriptive studies, we could miss more subtle HC that affects student success. This work presents results from interviews with undergraduate computing faculty, students, and peer mentors on their HC experiences. The results demonstrate several categories of HC including development tools, professional skills, institutional navigation, social well-being, and physical well-being. These …

Next-Generation Dns Rpz For Automated Threat Intelligence, Risk-Aware Filtering, And User-Centric Security, Jinu S, Kishore V. Krishnan, Rajarshi Middya, Annasamy Bagubali

Journal of Cybersecurity Education, Research and Practice

The Domain Name System (DNS) remains a critical attack vector exploited by adversaries for command-and-control (C2) communication, data exfiltration, and phishing campaigns. DNS Response Policy Zones (RPZ) have emerged as an effective defense mechanism by enabling the redirection or blocking of queries to malicious domains. However, current RPZ implementations encounter significant challenges related to scalability, adaptability, and user awareness, often resulting in static policies, delayed updates, and a high incidence of false positives. To address these limitations, this paper proposes an enhanced RPZ framework that integrates adaptive threat intelligence, machine learning-driven dynamic policy updates, and user-context-aware security controls. The proposed …

A Protestant Response To The Pope’S Magnifica Humanitas On Ai, Derek Schuurman

University Faculty Publications and Creative Works

Pope Leo XIV released his first papal encyclical, Magnifica Humanitas, on May 25, a roughly 42,000-word document outlining a Catholic response to recent developments in AI. I had been eagerly anticipating this encyclical and spent much of the release day poring over the text. While there have been other Christian efforts to release statements about AI, this is the first comprehensive statement from the Catholic Church. What follows is a summary of the document, followed by my own response.

Chatgpt, Where Should I Go? A Qualitative Exploration Of How Large Language Models Are Experienced As Support For Travel Planning, Mohammad Amin Kuhail, Asbjørn Følstad, Saifeddin Alimamy

All Works

Large language models (LLMs) are increasingly used for travel planning. Yet, little is known about how travellers experience and interact with such language models. This qualitative study explores how users employ LLMs to plan trips, drawing on the hedonic/pragmatic model of user experience to examine functional and affective dimensions. We collected data from 104 participants with prior experience using LLMs for travel advice through open-ended questionnaire responses. Thematic analysis revealed three key insights: (1) users value the pragmatic benefits of LLMs, such as efficiency, clarity, and confidence in decision-making, while also appreciating hedonic qualities, including inspiration, enjoyment, and authenticity; (2) …

A Machine Learning Framework For Contractor Scope Matching Using Profile Characteristics And Work Package Vector Similarity, Pedro Fonseca, Sergei Chuprov

Computer Science Faculty Publications

This paper presents a machine learning-based framework for predicting contractor performance in the construction industry by integrating contractor profile information with work package characteristics. The proposed approach addresses procurement challenges arising from the misalignment between contractor expertise and assigned scopes, a key contributor to cost overruns and schedule delays. Unlike existing models that rely on aggregated project-level indicators, the framework enables scope-aware performance prediction by leveraging the Work Breakdown Structure (WBS) to capture similarity among work packages. Contractor profiles are encoded using historical performance data, while WBS elements are vectorized to quantify scope similarity and contextualize predictions. Experimental results demonstrate …

[Birds-Of-A-Feather] A Tri-Level Roadmap To Ai-Ready Universities: Strategy, Operations, Deployment, Sarah Forzetting, Rochelle Lundy, Ahmad Pratama, Karryl Kim Sagun Trajano, Antara Chakraborthy, Yasmine Wong

FORCE 2026

This panel discussion by three institutions will offer three approaches to conceptualizing and supporting AI use at the national, local, and individual levels.

Nanyang Technological University will frame the discussion by examining AI as a social good, highlighting how even advanced initiatives such as Singapore’s face equity gaps that risk leaving vulnerable populations behind. The panelist will further outline how information professionals and other key stakeholders can play a critical role in bridging these gaps in the pursuit of widespread public AI literacy. Stanford University Libraries will outline difficulties institutions have in operationalizing guidelines to help researchers bring a project …

Developing An Assessment Framework To Support Critical Evaluation Of Ai-Powered Academic Search Engines, Huajin Wang

FORCE 2026

As AI-powered tools are emerging in all aspects of research, it’s challenging for researchers, students, and librarians alike to assess the benefit, usefulness, and risks associated with a new AI-powered tool or AI-enhanced features of an existing one. To address this challenge, Carnegie Mellon University Libraries is developing a Tool Evaluation Framework to help users understand how AI-powered tools work, initially focused on AI-enhanced academic search engines. By evaluating criteria such as mechanisms for document retrieval, processes for content generation, and the quality of outputs, this framework guides users to carefully consider the strengths and weaknesses of a tool before …

Supporting Fair Practices In Scholarly Publishing With The Editorial Reference Handbook, Susanna-Assunta Sansone, Allyson Lister, Rebecca Taylor-Grant, Matthew Cannon

FORCE 2026

Co-produced by academics and publishers (incl. CUP, Cell Press, EMBO Press, Taylor & Francis, GigaScience Press, OUP, PLOS, Springer Nature), the Editorial Reference Handbook (https://publishers.fairassist.org) assists scholarly publishers in supporting the sharing of digital research objects and in operationalising FAIR research practices by addressing gaps in editorial workflows, policy implementation and stakeholder alignment. The Handbook comprises three interrelated components—a checklist, detailed guidance documentation, and a flowchart—intended primarily for in-house editorial staff while also providing value to reviewers, authors, and service providers.

Beside this practical collaboratively developed product, the Handbook is also a socio-technical pilot to improve the culture …

Ten Years Of Tuwhera: A Commitment To Sustaining Open Access Publishing, Donna Coventry

FORCE 2026

Tucked away, far from the conference circuit, is a part of the world which doesn’t tend to make the headlines when it comes to open access initiatives. New Zealand and by extension, the South Pacific, is a region struggling with a history of colonisation and trying to make systematic change around decolonisation - open access to research about ‘our place in the world’ is vitally important. 

Ten years ago Auckland University of Technology’s library (Te Mātāpuna) made the decision to start hosting Diamond open access journals. Starting with two established journals, the service was named Tuwhera which can be translated …

Asian Open Research Data And Its Potential For Ai: Bridging The Digital Divide Through Strategic Data Sharing, Mark Hahnel, Simon Porter

FORCE 2026

The growing momentum for open research data in Asia intersects with global advances in artificial intelligence (AI). Open data policies and infrastructures are increasingly recognized as critical enablers of research equity, reproducibility, and innovation. This talk examines the current state of open academic data, highlights economic and scientific arguments for its adoption, and explores the transformative potential of Asian open data ecosystems in powering AI-driven discovery. Drawing on global examples such as the Protein Data Bank and emerging health datasets, the discussion positions Asian institutions to leverage open strategies that simultaneously meet compliance mandates, enhance visibility, and accelerate breakthroughs in …

Managing Ai Bot Access To Open Scholarly Infrastructures, Petr Knoth

FORCE 2026

The rapid rise of generative AI has created unprecedented demand for large, high-quality research corpora. Open access repositories and other open scholarly infrastructures have therefore become primary sources for AI bots, because they host research that is not universally reliable, but remains far more evidence-based than most web content. This is both an opportunity and a strain: repositories are now more valuable than ever, but machine traffic brings sustainability, capacity and policy challenges. Repositories may be able to scale, but who should fund that scaling, and under what conditions?

The core dilemma is how to curb abusive high-load bot activity …