Abstract:
The growing number of cyber threats, especially malware and phishing, poses
serious risks to both personal and sensitive information in today’s digital world. This
research aims to develop a user-oriented web application to assist individuals in
identifying and mitigating cybersecurity threats originating from various digital inputs
such as URLs, emails, and file attachments. The system was developed using the Agile
methodology, which enabled iterative development, continuous user feedback, and
flexible refinement throughout the project lifecycle. The system combines machine
learning, reputation analysis, and external service integration to detect suspicious
behaviour effectively. Designed to be accessible for all users, the application provides a
simple interface and clear, interactive scan results. It also helps users recognize threats
hidden in the digital content they commonly interact with. Testing shows that the system
can detect different types of threats accurately and supports user awareness of digital
security.
