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7 articles for “URL analysis”
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Detection of Phished URLs Using Machine Learning
Abstract: Phishing attacks remain a significant cybersecurity challenge, requiring innovative detection strategies. This study investigates the use of machine learning to detect phishing URLs, to improve the accuracy and reliability of detection systems. Utilizing a diverse dataset of legitimate and phishing URLs we extracted the features such as lexical properties, domain-specific details, and HTML content to train various machine learning models. Algorithms including Random Forest, support vector machine (SVM), and gradient …
Published in Journal of Web Engineering & Technology · Vol. 11, Issue 3, 2024 · pp. 1–7 Read article
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Detection of Phishing Website Using URL
Abstract: Phishing attacks are one of the greatest threats to online security, where fraud websites deceive users into giving out sensitive information. Traditional methods of detection, such as blacklists and heuristic-based systems, often fail in identifying newly created or sophisticated phishing websites. This study proposes an intelligent phishing website detection system using Convolutional Neural Networks (CNNs) in analyzing URLs and associated features. Using labeled URLs, the system employs such attributes such …
Published in Journal Of Network security · Vol. 13, Issue 1, 2025 · pp. 10–15 Read article
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Advancements in Phishing Detection: Automated Systems in Real-World Scenarios
Abstract: The goal of the abstract is to offer an automated method that uses login URLs to identify real-world scenarios. Phishing is a type of cyberattack that involves social engineering, when malefactors trick victims into providing their login credentials via a login form that sends the information to a hostile site. In this research, we offer a system that uses URL analysis to detect phishing websites by comparing machine learning and …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 2, 2024 · pp. 12–17 Read article
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Webometric Indicators and Digital Impact: An Evaluation of Top Ten NIRF-Ranked Indian University Websites
Abstract: This paper compares the webometric performance and digital presence of the top ten NIRF 2025–ranked Indian universities through their official websites. Data regarding total links (internal and external), Google-indexed links, URLs, and the Web Impact Factor (WIF) were gathered and analyzed using Google as the main search engine. The data collection and interpretation are based on the use of link analysis tools and search engine optimization (SEO) techniques. The analysis …
Published in Journal of Advancements in Library Sciences · Vol. 13, Issue 1, 2026 · pp. 1–9 Read article
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Autonomous 6G Physical Layer Architectures for Space-Air-Ground Integrated Networks
Abstract: The emergence of sixth generation (6G) wireless systems calls for a significant shift away from conventional deterministic communication models. As communication infrastructures evolve into Space- Air-Ground Integrated Networks (SAGIN), traditional physical layer (PHY) techniques struggle to operate effectively under the severe Doppler effects and long propagation delays associated with space environments. This paper examines the role of artificial intelligence embedded directly within the 6G transceiver architecture to enable ultra-reliable and …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 2, 2026 Read article
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Accessibility and Design Analysis of Library Websites/Webpages of National Institute of Technology (NITs) in India
Abstract: The purpose of this study is to analyze and examine the design and content information presented in library website/webpages of institutes of NITs across India. Website content organization and effectiveness can be measured utilizing content analysis techniques specifically under a prepared checklist to evaluate the website design and content of the library websites/webpages. In this study the library website/webpages design, functionality, usability and productivity of NITs libraries websites/webpages have been …
Published in Journal of Advancements in Library Sciences · Vol. 13, Issue 1, 2026 · pp. 76–84 Read article
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AI-Based Machine Learning Web Application Firewall (ML-WAF)
Abstract: This research investigates the use of deep learning techniques for the real-time detection of malicious activities in web traffic and proposes an intelligent, AI-driven Web Application Firewall (WAF) designed to provide automated and adaptive security. The system analyzes diverse components of HTTP requests, including request methods, URLs, headers, cookies, and payload content, to accurately identify and classify malicious behavior. The proposed model targets a wide range of common and critical …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article