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Journal articles on the topic 'Cybersecurity dashboard'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Shaikh, Arafat Tabrez. "An Innovative Approach to Job Placement through a Training and Placement Portal." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem46264.

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Abstract - This research focuses on the development of a Training and Placement Portal, a web-based application designed to streamline the process of connecting job seekers and employers. The portal allows users to create profiles, upload resumes, search for available job opportunities, and apply for relevant positions. Employers can post job vacancies, manage applicant information, and send interview invitations. The system is divided into key modules such as Admin, User, Company, Vacancy, and Dashboard, with each module performing distinct tasks to ensure smooth operation. The research emplo

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S., Yaswanthraj, Adhithyan M., Kowshik T., Logha Surya N., and Mihaash Dharan M. "URLs Threat Identification Dashboard." Research and Reviews: Advancement in Cyber Security 2, no. 2 (2025): 41–50. https://doi.org/10.5281/zenodo.15573303.

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<em>The growth in malware-hosting and phishing sites represents a fundamental threat to cybersecurity in all industries. This document introduces an in-time URLs Threat Identification Dashboard that scan s, aggregates, and visualizes malicious URLs based on </em><em>Abuse.ch (URL Haus) and AbuseIPDB data. The system periodically retrieves and processes threat feeds, stores them in a MariaDB database, and presents them on a Flask-built web interface. Developed with proactive defense in mind, the system updates information in real time, and it's designed for integration with future versions of f

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Clarke, Karla, Yair Levy, Laurie Dringus, and Shonda Brown. "How workplace satisfaction affects insider threat detection as a vital variable for the mitigation of malicious cyber insiders." Online Journal of Applied Knowledge Management 7, no. 1 (2019): 40–52. http://dx.doi.org/10.36965/ojakm.2019.7(1)40-52.

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Insider threat mitigation is a growing challenge within organizations. The development of a novel alert visualization dashboard for the identification of potentially malicious cyber insider threats was identified as necessary to alleviate this challenge. This research developed a cyber insider threat dashboard visualization prototype for detecting potentially malicious cyber insider activities QUICK.v™. This study utilized Subject Matter Experts (SMEs) by applying the Delphi Method to identify the most critical cyber visualization variables and ranking. This paper contains the detailed results

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Saeed, Saqib, Sarah A. Suayyid, Manal S. Al-Ghamdi, Hayfa Al-Muhaisen, and Abdullah M. Almuhaideb. "A Systematic Literature Review on Cyber Threat Intelligence for Organizational Cybersecurity Resilience." Sensors 23, no. 16 (2023): 7273. http://dx.doi.org/10.3390/s23167273.

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Cybersecurity is a significant concern for businesses worldwide, as cybercriminals target business data and system resources. Cyber threat intelligence (CTI) enhances organizational cybersecurity resilience by obtaining, processing, evaluating, and disseminating information about potential risks and opportunities inside the cyber domain. This research investigates how companies can employ CTI to improve their precautionary measures against security breaches. The study follows a systematic review methodology, including selecting primary studies based on specific criteria and quality valuation o

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Espinha Gasiba, Tiago, Ulrike Lechner, and Maria Pinto-Albuquerque. "Cybersecurity Challenges in Industry: Measuring the Challenge Solve Time to Inform Future Challenges." Information 11, no. 11 (2020): 533. http://dx.doi.org/10.3390/info11110533.

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Cybersecurity vulnerabilities in industrial control systems have been steadily increasing over the last few years. One possible way to address this issue is through raising the awareness (through education) of software developers, with the intent to increase software quality and reduce the number of vulnerabilities. CyberSecurity Challenges (CSCs) are a novel serious game genre that aims to raise industrial software developers’ awareness of secure coding, secure coding guidelines, and secure coding best practices. An important industry-specific requirement to consider in designing these kinds

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Balogun, Adebayo Yusuf. "Strengthening Compliance with Data Privacy Regulations in U.S. Healthcare Cybersecurity." Asian Journal of Research in Computer Science 18, no. 1 (2025): 154–73. https://doi.org/10.9734/ajrcos/2025/v18i1555.

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This study evaluates the state of data privacy and cybersecurity compliance within the U.S. healthcare sector, leveraging data from the U.S. Department of Health & Human Services Breach Portal, Verizon Data Breach Investigations Report, and the Health IT Dashboard. A quantitative methodology comprising descriptive statistical analysis, K-means clustering, and multivariate regression was employed to examine healthcare data breaches, categorize cybersecurity threats, and identify compliance challenges. Findings revealed a persistent increase in breaches, with hacking/IT incidents comprising

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Subha K, Benitlin. "AI-Driven Cybersecurity Model for Real-Time Threat Detection and Prevention." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem47712.

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Abstract - As cyber threats become more dynamic and sophisticated, traditional intrusion detection systems often fall short in identifying emerging attacks in real-time. This project introduces a hybrid AI-driven cybersecurity model that combines supervised machine learning and deep reinforcement learning for adaptive, explainable, and real-time threat detection and prevention. It uses an XGBoost classifier trained on the UNSW-NB15 dataset to predict initial threats and a Deep Q-Network (DQN) agent, built with PyTorch, to make optimal security decisions based on evolving threats. The DQN inter

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S, KAVIYA. "REAL-TIME FIREWALL EVENT ALERT SYSTEM FOR NETWORK PROTECTION." International Scientific Journal of Engineering and Management 04, no. 04 (2025): 1–7. https://doi.org/10.55041/isjem02862.

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The proposed system addresses the limitations of traditional firewalls by introducing real-time alert functionality using Django and Python. It monitors firewall logs to detect suspicious activities like brute-force login attempts, port scans, and large data transfers. Alerts are generated immediately and sent via email, ensuring quick response. The system includes a web dashboard for admin visibility and uses SQLite for lightweight storage. It is affordable, scalable, and suitable for small organizations and educational institutions. By automating detection and alerts, it minimizes manual wor

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Ogunmolu, Akinde Michael. "Leveraging Generative AI and Behavioral Biometrics to Strengthen Zero Trust Cybersecurity Architectures in Healthcare Systems." Journal of Engineering Research and Reports 27, no. 5 (2025): 194–213. https://doi.org/10.9734/jerr/2025/v27i51502.

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This study investigates the integration of Generative Artificial Intelligence (AI) and Behavioral Biometrics within Zero Trust cybersecurity frameworks tailored for healthcare systems. Drawing on public datasets—including MITRE ATT&CK for Enterprise, UNSW Behavioral Biometrics, and the HHS HC3 Healthcare Cybersecurity Dashboard—the study employs a quantitative design featuring Two-Sample T-Tests, ROC-AUC analysis, and Exploratory Factor Analysis (EFA). Findings indicate a marked improvement in threat detection rates, rising from 65.21% to 82.06% following Generative AI deployment. Addition

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Ahmad, Siti Arpah, Muhammad Al’Imran Mohd Khairuddin, Nor Shahniza Kamal Bashah, and Nurul Aishah Ab Raman. "An integrated framework for data breach on the dark web in brand monitoring data hunting." International Journal of Electrical and Computer Engineering (IJECE) 15, no. 3 (2025): 3162. https://doi.org/10.11591/ijece.v15i3.pp3162-3170.

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In today's digital landscape, data breaches pose a substantial threat, with the dark web serving as a prevalent platform for malevolent actors to perpetrate such incidents. Currently, security analysts use various tools to solve the problem, which is very time-consuming. This paper introduces a novel framework that integrates data breach monitoring within the dark web, focusing on brand monitoring and data hunting. The framework starts from the scraping process and continues with the utilisation of the Splunk dashboard. The dashboard provides an exhaustive overview of data breaches related to

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DR. K. Maharajan, Mugeshwaran K, Dumala Nithish, Dinesh S, and Uday N. "Threat Intelligence Platform Empowered by Generative Ai with Quantum-Security." International Research Journal on Advanced Engineering Hub (IRJAEH) 3, no. 04 (2025): 1336–42. https://doi.org/10.47392/irjaeh.2025.0190.

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The rapid evolution in types of cyber threats and anticipated threats through quantum computing requires a change in cybersecurity strategy. The traditional Threat Intelligence Platforms (TIPs) usually use static rule-based systems and reactive measures to provide real-time solutions to address attacks that are either emerging or sophisticated. This paper proposes a next-generation Threat Intelligence Platform (TIP) incorporating Generative Artificial Intelligence (GenAI) to enable predictive threat scenario modelling, anomaly detection, and autonomous mitigation strategies using quantum-secur

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Berríos, Sebastián, Sebastián Garcia, Pamela Hermosilla, and Héctor Allende-Cid. "A Machine-Learning-Based Approach for the Detection and Mitigation of Distributed Denial-of-Service Attacks in Internet of Things Environments." Applied Sciences 15, no. 11 (2025): 6012. https://doi.org/10.3390/app15116012.

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The widespread adoption of Internet of Things (IoT) devices has significantly increased the exposure of cloud-based architectures to cybersecurity risks, particularly Distributed Denial-of-Service (DDoS) attacks. Traditional detection methods often fail to efficiently identify and mitigate these threats in dynamic IoT/Cloud environments. This study proposes a machine-learning-based framework to enhance DDoS attack detection and mitigation, employing Random Forest, XGBoost, and Long Short-Term Memory (LSTM) models. Two well-established datasets, CIC-DDoS2019 and N-BaIoT, were used to train and

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Mohammed Razmirahman khan, Mohammed safiuddin, Syed Faisal, and Mohammed Rahmat Ali. "Ai Based Cyber Security Assistant For Non -Technical Users." International Journal of Information Technology and Computer Engineering 13, no. 2s (2025): 560–66. https://doi.org/10.62647/ijitce2025v13i2spp560-566.

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This project presents the development of an intelligent,offline-capable cybersecurity platform called Cyber-Wraith, integrated with AI-powered phishingdetection, password risk analysis, and simulatedbreach monitoring. The system uses SQLite for localstorage of scan history and user preferences, while thefront end is built with React and packaged into adesktop application via Electron, offering aresponsive, modular, and privacy-focused userexperience. Cyber-Wraith simulates real-time threatdetection by analyzing URLs, domain metadata, andpassword strength using rule-based logic and entropyscori

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sankar U, Dhilip. "AUTOMATED DDOS SIMULATION IN A VIRTUAL ENVIRONMENT USING PYTHON AND TELEGRAM BOT." International Scientific Journal of Engineering and Management 04, no. 04 (2025): 1–7. https://doi.org/10.55041/isjem02959.

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This project presents an automated system for simulating and mitigating DDoS attacks in a virtual environment. The system mimics DDoS attacks based on TCP, UDP, and ICMP using Python scripts and the hping3 tool. Incoming traffic is watched for harmful patterns by a real- time packet sniffing mechanism. An automated reaction that blocks the attacker's IP address is triggered when threats are detected. Remote management and immediate alerts are made possible by a Telegram bot integration. The system has a web dashboard that shows blocked IPs and attack logs. It guarantees practical experience wi

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JEYAPRAKASH S, Mr. "Cyber Threat Intelligence for Industrial Control System." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem46481.

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Abstract - The ICS Sentinel platform is a state-of-the-art cyber threat intelligence (CTI) solution intended to protect Industrial Control Systems (ICS) against emerging cyber threats. It is developed with a contemporary web architecture, utilizing a React 18.2.0 frontend with Vite, Tailwind CSS, and markdown rendering for user-friendly threat analysis and reporting. The platform includes a secure, role-based authentication mechanism with guarded routing, providing authorized access to key functionalities. Its RESTful API allows for hassle-free communication with a backend for real-time data r

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AlHaddad, Ulaa, Abdullah Basuhail, Maher Khemakhem, Fathy Elbouraey Eassa, and Kamal Jambi. "Ensemble Model Based on Hybrid Deep Learning for Intrusion Detection in Smart Grid Networks." Sensors 23, no. 17 (2023): 7464. http://dx.doi.org/10.3390/s23177464.

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The Smart Grid aims to enhance the electric grid’s reliability, safety, and efficiency by utilizing digital information and control technologies. Real-time analysis and state estimation methods are crucial for ensuring proper control implementation. However, the reliance of Smart Grid systems on communication networks makes them vulnerable to cyberattacks, posing a significant risk to grid reliability. To mitigate such threats, efficient intrusion detection and prevention systems are essential. This paper proposes a hybrid deep-learning approach to detect distributed denial-of-service attacks

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Olawale, Habeeb Olatunji, Ngozi Joan Isibor, and Joyce Efekpogua Fiemotongha. "A Predictive Compliance Analytics Framework Using AI and Business Intelligence for Early Risk Detection." International Journal of Management and Organizational Research 2, no. 2 (2023): 190–95. https://doi.org/10.54660/ijmor.2023.2.2.190-195.

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In an era of escalating regulatory complexity and costly compliance breaches, this paper proposes a predictive compliance analytics framework that harnesses artificial intelligence and business intelligence tools to enable early risk detection in financial and insurance sectors. By integrating machine learning models with interactive dashboard platforms such as Tableau, SQL, and Python, the framework transforms traditional reactive compliance approaches into a proactive, data-driven system. The framework incorporates diverse data sources, advanced algorithms, and real-time visualization to ide

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Saepudin, Asep, Dzahra Al Madinah, Makhsun Makhsun, and Taswanda Taryo. "ANALISIS DAN PENGEMBANGAN SISTEM MONITORING RADIOAKTIF ALAMIAH RADON MENGGUNAKAN DETEKTOR SINTILASI BERBASIS WEB SECARA REAL TIME." Infotech: Journal of Technology Information 11, no. 1 (2025): 137–46. https://doi.org/10.37365/jti.v11i1.384.

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Monitoring radon gas concentrations in various environments, such as residential areas, buildings, caves, and mining sites, is crucial to minimizing health risks associated with radon exposure exceeding the 100 Bq/m³ threshold set by the World Health Organization (WHO). Additionally, anomalies in radon concentration in fault zones are often considered precursors to seismic activity. Therefore, this study develops a real-time Internet of Things (IoT)-based radon gas monitoring system using a cost-effective approach. The system utilizes a ZnS(Ag)-based scintillation detector combined with a Phot

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Okunlola, Folasade. "Integrating Emergency Data Management Systems in Energy and Natural Resources Industries." International Journal of Business and Management 3, no. 1 (2024): 1–7. https://doi.org/10.70560/j1ch2v40.

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Effective emergency data management is critical in the energy and natural resources industries, where operational disruptions can lead to significant economic and environmental consequences. This study proposes a scalable framework for emergency data management that integrates real-time data collection, predictive analytics, and interactive dashboard visualization to enhance decision-making and operational readiness. The framework is validated through a mixed-methods approach involving industry case studies, expert interviews, and simulation exercises. Key findings reveal that the framework re

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Folasade, Okunlola. "Integrating Emergency Data Management Systems in Energy and Natural Resources Industries." International Journal of Environmental Science and Sustainability 2, no. 1 (2023): 11–16. https://doi.org/10.70560/t6n7fh13.

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Effective emergency data management is critical in the energy and natural resources industries, where operational disruptions can lead to significant economic and environmental consequences. This study proposes a scalable framework for emergency data management that integrates real-time data collection, predictive analytics, and interactive dashboard visualization to enhance decision-making and operational readiness. The framework is validated through a mixed-methods approach involving industry case studies, expert interviews, and simulation exercises. Key findings reveal that the framework re

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Khan, Mohd Imran, Aditya Kadu, Rahul Hulke, et al. "Artisan Hub." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 03 (2025): 1–9. https://doi.org/10.55041/ijsrem43061.

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The emergence of internet platforms has revolutionized the art industry by providing artists with fresh avenues for displaying, marketing, and selling their creations. This essay examines the creation and effects of Artisan Hub, an online resource for aspiring and seasoned artists. This platform offers a unique dual-functionality system that enables artists to offer online seminars and boot camps in addition to selling their artistic endeavors, in contrast to standard online art galleries. With a dedicated control panel, artists keep control over their art, whereas the system integrates admin-

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Hamada, Razi, and Ievgeniia Kuzminykh. "Exploitation Techniques of IoST Vulnerabilities in Air-Gapped Networks and Security Measures—A Systematic Review." Signals 4, no. 4 (2023): 687–707. http://dx.doi.org/10.3390/signals4040038.

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IP cameras and digital video recorders, as part of the Internet of Surveillance Things (IoST) technology, can sometimes allow unauthenticated access to the video feed or management dashboard. These vulnerabilities may result from weak APIs, misconfigurations, or hidden firmware backdoors. What is particularly concerning is that these vulnerabilities can stay unnoticed for extended periods, spanning weeks, months, or even years, until a malicious attacker decides to exploit them. The response actions in case of identifying the vulnerability, such as updating software and firmware for millions o

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Qin, T., C. Li, and G. F. Liu. "Control infrastructure monitoring system at the NSRL facility cluster." Journal of Instrumentation 17, no. 11 (2022): P11005. http://dx.doi.org/10.1088/1748-0221/17/11/p11005.

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Abstract The National Synchrotron Radiation Laboratory (NSRL) facility cluster is a collection of user facilities developed by NSRL, including the Hefei Light Source-II (HLS-II), Tunable Infrared Laser for Fundamental of Energy Chemistry (FELiChEM), and THz near-field high-flux material physical property test system (NFTHZ). User facilities generally have high operational availability requirements. The NSRL facility cluster relies on the control infrastructure to provide computing, network, and storage resources, as well as various services that must be available 24 hours a day, 7 days a week.

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Dr. G. Vasavi, G. T. S. Satyanarayana, B. Vivek Sai, and B. Chaitanya S. S. Phani. "Design and Implementation of Smart-H Pot: A Custom Intrusion Detection System." International Research Journal on Advanced Engineering Hub (IRJAEH) 3, no. 04 (2025): 1851–56. https://doi.org/10.47392/irjaeh.2025.0268.

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In the digital world with all new cyber threats evolving constantly, protecting digital world from unauthorized access with new threats is more important than ever. Traditional Intrusion Detection Systems (IDS) often fail in capturing real-world attacker behavior due to this constant evolving. To fill the gap of evolving, we are introducing Smart-HPot a lightweighted, custom-built IDS that basically uses a honeypot approach to detect and monitor malicious activities in real time. The system provides the services such as SSH and HTTP within a controlled virtual environment, tempting attackers t

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Anil Kumar Pakina. "AI Governance via Explainable Reinforcement Learning (XRL) for Adaptive Cyber Deception in Zero-Trust Networks." Journal of Information Systems Engineering and Management 10, no. 43s (2025): 98–115. https://doi.org/10.52783/jisem.v10i43s.8308.

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This study presents the design and evaluation of an Explainable Reinforcement Learning (XRL) system guided by AI governance principles for adaptive cyber deception within a Zero-Trust Architecture (ZTA). The proposed approach integrates a Monte Carlo Tree Search (MCTS)-based reinforcement learning agent with SHAP (SHapley Additive exPlanations) to deliver transparent and effective deception strategies against advanced persistent threats (APTs). The simulated environment consists of a containerized network with user workstations, honeypots, and a file server, governed by strict Zero-Trust polic

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Dziubanovska, Nataliia, and Ivan Tsegelnyy. "Digital tools for ensuring transparency in investment attraction: challenges and opportunities for post-war Ukraine." Economic Analysis, no. 35(1) (2025): 525–35. https://doi.org/10.35774/econa2025.01.525.

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Introduction. This article substantiates the importance of transparency in investment attraction processes amid the full-scale military conflict in Ukraine, where openness and accountability of financial flows are key factors in strengthening the trust of donors and private investors and laying the groundwork for the effective restoration of critical infrastructure. Purpose. To develop scientifically grounded recommendations for implementing integrated digital instruments that will ensure end-to-end traceability of investment processes during wartime and the post-war period, minimize corruptio

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Ekaterina, Kapustina. "Corporate Governance in the Context of Business Digital Transformation." American Journal of Management and Economics Innovations 07, no. 05 (2025): 90–98. https://doi.org/10.37547/tajmei/volume07issue05-11.

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This article examines the transformation of traditional corporate governance mechanisms amid the accelerated adoption of digital technologies, where the pace of innovation and the escalation of IT-related risks demand from Boards of Directors not only monitoring but also active strategic engagement in digital initiatives. The relevance of this study is driven by the fact that global spending on digital transformation reaches trillions of dollars. In contrast, only a small fraction of companies manage to adapt the structure of their governing bodies: standing IT committees exist in only 15% of

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Kirti, Vasdev. "Building Geospatial Dashboards for IT Decision-Making." INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH AND CREATIVE TECHNOLOGY 6, no. 4 (2020): 1–6. https://doi.org/10.5281/zenodo.14384096.

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In today’s data-driven world, the integration of geospatial analytics into IT decision-making is a transformative approach. This paper explores the theory, design principles, and application of geospatial dashboards, which provide real-time visualizations for informed IT decisions. Using case studies from sectors such as cybersecurity, logistics, and urban planning, this research demonstrates how geospatial dashboards enhance data interpretation and operational efficiency. Challenges such as data integration, real-time processing, and user interface design are also addressed.

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Alfaadhel, Afnan, Iman Almomani, and Mohanned Ahmed. "Risk-Based Cybersecurity Compliance Assessment System (RC2AS)." Applied Sciences 13, no. 10 (2023): 6145. http://dx.doi.org/10.3390/app13106145.

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Cybersecurity attacks are still causing significant threats to individuals and organizations, affecting almost all aspects of life. Therefore, many countries worldwide try to overcome this by introducing and applying cybersecurity regularity frameworks to maintain organizations’ information and digital resources. Saudi Arabia has taken practical steps in this direction by developing the essential cybersecurity control (ECC) as a national cybersecurity regulation reference. Generally, the compliance assessment processes of different international cybersecurity standards and controls (ISO2700x,

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Rahanuma Tarannum, Sakhawat Hussain Tanim, Md Sabbir Ahmad, and Md Manarat Uddin Mithun. "Business analytics for IT infrastructure projects: Optimizing performance and security." International Journal of Science and Research Archive 14, no. 3 (2025): 783–92. https://doi.org/10.30574/ijsra.2025.14.3.0729.

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In modern IT infrastructure projects, optimizing system performance and security is crucial for ensuring reliability, efficiency, and compliance. This study explores the role of business analytics in improving IT infrastructure performance and mitigating cybersecurity risks. By utilizing real-world datasets rather than literature-based models, this research applies predictive analytics, machine learning algorithms, and business intelligence tools to enhance IT operations. The findings reveal a 26.7% reduction in CPU usage, 25% improvement in memory utilization, and a 29.2% decrease in network

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Shelke, Palvi, and Tapio Frantti. "Exploring the Possibilities of Splunk Enterprise Security in Advanced Cyber Threat Detection." International Conference on Cyber Warfare and Security 20, no. 1 (2025): 605–13. https://doi.org/10.34190/iccws.20.1.3326.

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Cybersecurity is a critical concern for organizations as cyber threats grow increasingly frequent and sophisticated. Real-time detection and response to these threats are essential for safeguarding data and maintaining operational continuity. Splunk Enterprise Security (ES), a robust Security Information and Event Management (SIEM) platform, offers advanced tools for identifying and mitigating cyber threats. This paper explores the possibilities of using Splunk ES to enhance advanced cyber threat detection, focusing on its features, capabilities, and real-world applications. Splunk ES collects

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Srikanth Yerra. "Enhancing Inventory Management through Real-Time Power BI Dashboards and KPI Tracking." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 2 (2025): 944–51. https://doi.org/10.32628/cseit25112458.

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Effective inventory management is essential for op- timizing supply chain operations, reducing costs, and ensuring seamless product availability. Traditional inventory tracking methods often lead to inefficiencies due to delayed data updates and a lack of real-time insights. This study explores how Power BI dashboards and Key Performance Indicator (KPI) tracking can revolutionize inventory management by providing real-time visibility, data-driven decision-making, and predictive analytics. Power BI integrates with databases like SQL Server and cloud- based platforms such as Microsoft Azure, ena

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Chignell, Mark H., Mu-Huan Chung, Yuhong Yang, Greg Cento, and Abhay Raman. "Human Factors in Interactive Machine Learning: A Cybersecurity Case Study." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 65, no. 1 (2021): 1495–99. http://dx.doi.org/10.1177/1071181321651206.

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Cybersecurity is emerging as a major issue for many organizations and countries. Machine learning has been used to recognize threats, but it is difficult to predict future threats based on past events, since malicious attackers are constantly finding ways to circumvent defences and the algorithms that they rely on. Interactive Machine learning (iML) has been developed as a way to combine human and algorithmic expertise in a variety of domains and we are currently applying it to cybersecurity. In this application of iML, implicit knowledge about human behaviour, and about the changing nature of

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Kumar, Aman, Nikhil Rathod J,, Sandeep Achar, Chandan P. Shirni, and Kishore K R. "Optimizing Student and Faculty Experiences Through University Management Platforms." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 01 (2025): 1–9. https://doi.org/10.55041/ijsrem40530.

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The University Management Platforms (UMPs) are very vital in the management of the day to day activities and improvement of the students and the instructors. This paper aims at establishing how UMPs, through features such as self-service portals, real-time notifications, automated class management tools, and performance dashboards can enhance user engagement, productivity, and satisfaction. Through the analysis of case studies and user feedback, this study identifies the advantages of minimizing the time and energy spent on administrative functions and the easy access to required materials. ad

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Lezhanina, Viktoriia. "Peculiarities of Auditing Small and Medium-Sized Enterprises in the Context of Digitalization." Universal Library of Business and Economics 02, no. 01 (2025): 49–53. https://doi.org/10.70315/uloap.ulbec.2025.0201009.

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This article provides a comprehensive examination of audit practices in small and medium-sized enterprises (SMEs) undergoing digital transformation. Drawing on contemporary research and industry insights, it explores how cloud-based systems, artificial intelligence, and automation tools reshape auditors’ roles, methodological approaches, and risk management strategies. The discussion highlights critical cybersecurity concerns, risks of data misrepresentation in cloud environments, and evolving expectations for transparency and reliability in financial reporting. In addressing these challenges,

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Năstasă, Iulian, Mihaela Mandu, and Dana-Galieta Mincă. "Confidentiality of Medical Data in the Proposed Romanian National Cardiac Rehabilitation Registry: Ethical, Technical, and Legal Considerations." Balneo and PRM Research Journal 16, Vol 16 No. 2 (2025): 826. https://doi.org/10.12680/balneo.2025.826.

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Romania is deficient in a centralized infrastructure to monitor outcomes in cardiac rehabilitation (CR), and this contributes to high cardiovascular mortality, which nevertheless remains high despite clinical guidelines and EU strategic actions. This paper articulates the process that led to the establishment of the National Cardiac Rehabilitation Registry (NCRR), which is a digital infrastructure compliant with the GDPR and NIS2 framework, intended to close a significant policy and clinical void in Romania's cardiovascular care system. Applying a multi-tiered methodology to consider the NCRR

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Mr. D. Pavun kumar, Mr. K. Gokul, Mr. PA. Janamithran, Mr. B. Kalanidhi Kadhirr, and Mr. R. Lokesh. "Al-Orchestrated Intelligent Microcredit Framework for Optimized Financial Accessibility and Proactive Risk Mitigation." International Research Journal on Advanced Engineering Hub (IRJAEH) 3, no. 04 (2025): 1971–80. https://doi.org/10.47392/irjaeh.2025.0288.

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Micro Credit Application is an avant-garde platform engineered to streamline, automate, and optimize the microloan acquisition process for salaried individuals. Leveraging a cutting-edge technology stack-including a MERN-based interactive front-end, Firebase for real-time authentication and secure data management, Flask for resilient backend services, and a Python-powered Al model-the application meticulously gathers. synthesizes, and analyzes extensive personal and financial datasets. This intelligent decision-making framework enables Al-driven assessment of financial stability, creditworthin

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Oluoha, Oluchukwu Modesta, Abisola Odeshina, Oluwatosin Reis, Friday Okpeke, Verlinda Attipoe, and Omamode Henry Orieno. "AI-Enabled Framework for Zero Trust Architecture and Continuous Access Governance in Security-Sensitive Organizations." International Journal of Social Science Exceptional Research 3, no. 1 (2024): 343–64. https://doi.org/10.54660/ijsser.2024.3.1.343-364.

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In today’s increasingly complex cybersecurity landscape, traditional perimeter-based security models are no longer sufficient to protect sensitive data and systems. Security-sensitive organizations, such as those in finance, healthcare, and government, are facing heightened risks from insider threats, credential misuse, and sophisticated cyberattacks. This paper proposes an AI-enabled framework for implementing Zero Trust Architecture (ZTA) and Continuous Access Governance (CAG) to enhance identity and access management (IAM) and strengthen organizational security posture. The Zero Trust model

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Ma, Zhiyuan, Shumeng Zhang, and Zhiyu Liu. "Digital Twin Technology: A Comprehensive Overview of Concepts, Applications, and Innovations." Undergraduate Research in Natural and Clinical Science and Technology (URNCST) Journal 9, no. 6 (2025): 1–7. https://doi.org/10.26685/urncst.877.

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Introduction: Digital Twin (DT) refers to a real-time virtual representation of a physical object, system, or process, maintained through continuous data exchange between physical and digital spaces. Originating from NASA’s early simulation models and formally conceptualized in the early 2000s, DTs have become foundational to digital transformation, particularly in Industry 4.0. Supported by developments in Internet of Things (IoT), machine learning, and cloud computing, DTs are now widely adopted across sectors including manufacturing, infrastructure, and environmental management. Body: The o

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Kabahing, Sepfanner, Rikie Kartadie, Sigit Aditomo, Ivònia Fàtima Ruas Da silva, Francisco Xavier, and Nur aini Nur aini. "Prediction of Cyber Attack Losses by Attack Type and Country with Visual Approach and Quantitative Statistics." Journal of Intelligent Software Systems 4, no. 1 (2025): 5. https://doi.org/10.26798/jiss.v4i1.2002.

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Cyberattacks continue to be a major threat to the digital infrastructure of countries around the world, significantly impacting economic stability, data security and public trust. This research aims to analyze financial losses due to cyberattacks by country, attack type, and affected industry sector, utilizing a visual exploratory approach through interactive dashboards and descriptive statistical analysis. The data used includes 3,000 cyber incidents from 10 countries, covering various attack types such as DDoS, Phishing, Malware, and Man-in-the-Middle. Visualization was developed using Power

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Chibogwu Igwe-Nmaju and Chidozie Anadozie. "Digital trust and communication in tech-critical industries: Frameworks for managing stakeholder confidence at scale or commanding digital trust in high-stakes sectors: Communication strategies for sustaining stakeholder confidence amid technological ris." World Journal of Advanced Research and Reviews 15, no. 3 (2022): 609–30. https://doi.org/10.30574/wjarr.2022.15.3.0920.

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As digital infrastructure becomes the backbone of critical industries—from financial systems and telecoms to energy grids and healthcare—stakeholder confidence hinges increasingly on how organizations communicate trust amid rising technological complexity and risk. This paper examines the evolution of digital trust as a central component of organizational resilience and its direct relationship to communication strategies in high-stakes, tech-driven sectors. Focusing on sectors where system failures, data breaches, or algorithmic bias could trigger catastrophic outcomes, the study introduces ro

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Ajayi, Ajibola Joshua, Oluwole Oluwadamilola Agbede, Experience Efeosa Akhigbe, and Nnaemeka Stanley Egbuhuzor. "Enhancing Public Sector Productivity with AI-Powered SaaS in E-Governance Systems." International Journal of Judicial Law 3, no. 1 (2024): 76–92. https://doi.org/10.54660/ijjl.2024.3.1.76-92.

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The integration of Artificial Intelligence (AI) into Software-as-a-Service (SaaS) platforms is revolutionizing e-governance systems, driving unprecedented productivity in the public sector. This paper explores the transformative potential of AI-powered SaaS in enhancing efficiency, transparency, and decision-making within e-governance frameworks. Traditional governance systems often face challenges such as bureaucratic inefficiencies, limited resource optimization, and inadequate service delivery. By incorporating AI capabilities, SaaS platforms offer scalable, cost-effective, and data-driven

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Nnaemeka Stanley Egbuhuzor, Ajibola Joshua Ajayi, Experience Efeosa Akhigbe, and Oluwole Oluwadamilola Agbede. "Leveraging AI and cloud solutions for energy efficiency in large-scale manufacturing." International Journal of Science and Research Archive 13, no. 2 (2024): 4170–92. https://doi.org/10.30574/ijsra.2024.13.2.2314.

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The integration of Artificial Intelligence (AI) and cloud solutions is revolutionizing energy efficiency in large-scale manufacturing, offering transformative potential to address the sector's pressing challenges. Manufacturing industries face growing pressure to optimize energy use, reduce operational costs, and meet stringent sustainability targets. This paper explores how AI-driven cloud technologies can enhance energy efficiency through predictive analytics, real-time monitoring, and intelligent automation, ensuring sustainable and cost-effective operations. AI-powered systems leverage mac

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Ajayi, Ajibola Joshua, Oluwole Oluwadamilola Agbede, Experience Efeosa Akhigbe, and Nnaemeka Stanley Egbuhuzor. "Enhancing Public Sector Productivity with AI-Powered SaaS in E-Governance Systems." International Journal of Multidisciplinary Research and Growth Evaluation 5, no. 1 (2024): 1243–59. https://doi.org/10.54660/.ijmrge.2024.5.1-1243-1259.

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The integration of Artificial Intelligence (AI) into Software-as-a-Service (SaaS) platforms is revolutionizing e-governance systems, driving unprecedented productivity in the public sector. This paper explores the transformative potential of AI-powered SaaS in enhancing efficiency, transparency, and decision-making within e-governance frameworks. Traditional governance systems often face challenges such as bureaucratic inefficiencies, limited resource optimization, and inadequate service delivery. By incorporating AI capabilities, SaaS platforms offer scalable, cost-effective, and data-driven

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Nuruzzaman, Md, and Sohel Rana. "IOT-ENABLED CONDITION MONITORING IN POWER DISTRIBUTION SYSTEMS: A REVIEW OF SCADA-BASED AUTOMATION, REAL-TIME DATA ANALYTICS, AND CYBER-PHYSICAL SECURITY CHALLENGES." Journal of Sustainable Development and Policy 01, no. 01 (2025): 25–43. https://doi.org/10.63125/pyd1x841.

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The evolution of modern power distribution systems has been profoundly influenced by the rapid integration of Internet of Things (IoT) technologies, which enable advanced condition monitoring, enhance operational visibility, and facilitate early fault detection across critical infrastructure. This systematic review investigates the multifaceted role of IoT in transforming conventional Supervisory Control and Data Acquisition (SCADA) systems into intelligent, interoperable platforms that support automation, real-time analytics, and adaptive control within power distribution networks. Emphasis i

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Shete, Shriyash. "Information Visualization for a Comprehensive Cybersecurity Risk Quantification and Measurement." Journal of Artificial Intelligence & Cloud Computing, June 30, 2023, 1–5. http://dx.doi.org/10.47363/jaicc/2023(2)170.

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This paper presents an innovative dashboard design for cybersecurity risk management, addressing the urgent need for effective visualization and quantification of cyber threats in organizations. Through semi-structured interviews with security executives, we identify key challenges in cybersecurity operations and propose a user-centric dashboard. This tool integrates an overall risk score, trend analysis, global threat mapping, and a three-step workflow from risk insights to remediation, all aimed at enhancing decision-making for Chief Information Security Officers (CISOs) and their teams. Usa

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Shete, Shriyash. "Visualizing Data Security with AI/ML-Powered Data Classification." Journal of Artificial Intelligence & Cloud Computing, December 31, 2022, 1–4. http://dx.doi.org/10.47363/jaicc/2022(1)172.

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Data Protection is an integral part of cybersecurity. With enormous amounts of data being produced, transferred, and consumed every day, securing an organization’s sensitive data from leaking to the external internet is one of the challenges companies and cybersecurity professionals deal with every day. We found that the existing policy and criteria-based approach in cybersecurity software to identify anomalous activities limits the visibility, makes security administrators’ jobs time-consuming and ultimately leads to weakened data security. In this paper, we investigate how cybersecurity prof

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G, Manjula, Samhith G, Kartik Lutimath, Monisha Raj H N, and Preethi K R. "A Hybrid Machine Learning Approach for Network Intrusion Detection with Real-Time Visualization." Indian Journal of Computer Science and Technology, May 10, 2025, 91–100. https://doi.org/10.59256/indjcst.20250402009.

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ntrusion Detection Systems (IDS) are critical components of modern cybersecurity infrastructure, designed to identify and mitigate threats within network traffic. However, traditional detection methods often struggle to detect novel or zero-day attacks. This paper presents a hybrid IDS that leverages both supervised and unsupervised machine learning techniques – specifically Random Forest for classification and Isolation Forest for anomaly detection – to provide robust threat identification. Utilizing the CICIDS2017 dataset, chosen for its realistic representation of network traffic, the syste

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S. Abdulaziz, Rafid. "RESOLVE PROBLEMS FACING APPLICATION PROGRAMMING INTERFACES (APIS) IN THE WAZUH (SIEM) SOLUTION." Anbar Journal of Modern Sciences, February 15, 2025, 32–42. https://doi.org/10.63298/ajms.2025.186488.

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In this research, a problem facing the application programming interfaces (APIs) in the Wazuh (SIEM) solution system was pointed out, which leads to a malfunction in the system user interface (dashboard). The problem causes the inability to deal with the user interface (Dashboard) and manage the basic system functions, which negatively affects the efficiency of system operation and cybersecurity management. The main problem was identified as the incompatibility between the installed Ubuntu operating system and the operating requirements of the Wazuh (SIEM) solution system. The aim of this rese

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Sharma, Madhav, and Roger McHaney. "Bots and insights: Combining perspectives of analytics and software development in systems analysis and design projects." Decision Sciences Journal of Innovative Education 23, no. 2 (2025). https://doi.org/10.1111/dsji.70005.

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AbstractMany management information systems (MIS) faculty have adopted a project‐oriented approach in their systems analysis and design courses. In these courses, students use a software development methodology to create a web or mobile application project, which can be based on a predefined case or developed for an external stakeholder. Because most information systems programs emphasize cybersecurity, analytics, and artificial intelligence (AI), traditional systems analysis and design courses for web applications may seem one‐dimensional in comparison. To address this limitation, we develope

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