Real-Time Web Page Malware Detection

Abstract

Real-time mobile web page malware detection is essential for safeguarding users from online threats. With the rapid growth of mobile browsing, malicious web pages have become a major security concern. This approach detects malware instantly as users access web pages through their mobile devices. It uses lightweight machine learning algorithms to analyze webpage content, scripts, and behavior. Features such as URL structure, embedded JavaScript, and external links are evaluated. Real-time detection ensures immediate blocking of harmful sites, minimizing user risk. Cloud-based scanning and on device filters enhance performance and scalability. The system updates threat databases continuously for evolving attacks. It avoids delays or excessive battery consumption, making it suitable for mobile use.

Privacy preserving techniques are integrated to protect user data. This method strengthens overall mobile cybersecurity. It offers a fast, efficient, and effective solution against web-based malware threats.