MalURLDozer: A lightweight real-time malicious URL detection platform
SOFTWAREX, cilt.35, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 35
- Basım Tarihi: 2026
- Doi Numarası: 10.1016/j.softx.2026.102846
- Dergi Adı: SOFTWAREX
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC, Directory of Open Access Journals
- Ondokuz Mayıs Üniversitesi Adresli: Evet
Özet
While navigating the internet, users frequently encounter malicious URLs, including phishing, malware, defacement, and spam, which pose significant risks to individuals with limited digital literacy. Although extensive academic research has proposed various machine learning models for URL detection, a critical gap remains in translating these theoretical frameworks into practical, accessible tools for everyday users. To bridge this gap, this study introduces a fully deployable URL verification system. Unlike existing purely academic models or isolated algorithms, our solution transitions theoretical accuracy into real-world application. It employs a twopronged approach-combining syntactic URL analysis with a machine learning filter-integrated directly into a user-friendly browser extension and a dedicated web platform. By enabling both automated real-time detection and manual verification, this applied system actively empowers uninformed users to circumvent potential cyber threats in a live browsing environment.