MALWARE DETECTION AND URL SCANNER
Abstract
The increasing prevalence of cyber threats has made malware detection and secure web browsing critical components in cybersecurity. This project, Malware Detection and URL Scanner, focuses on developing an efficient system to identify and mitigate malicious software and unsafe URLs in real-time. By leveraging machine learning algorithms and heuristic analysis, the system scans files and web links to detect patterns indicative of malware, phishing attempts, and other cyber threats. The URL scanner component evaluates website credibility by analyzing domain features, URL structure, and associated metadata to flag potential risks. The system is designed with a user-friendly interface, ensuring accessibility for both individuals and organizations seeking to safeguard their digital environments. This project aims to enhance proactive threat detection and contribute to the broader field of cybersecurity by offering a reliable, scalable, and automated solution for identifying malicious entities online.
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