Smart phishing detection system: Using Machine Learning Model Integrated with Virustotal API

Phishing is one of the most important and challenging areas in the spectrum of cybersecurity, always adapting to overcome traditional techniques of detection. We present the Smart Phishing Detection System based on reinforcement learning coupled with the VirusTotal API to improve the identification of harmful links and executables. In essence, our platform allows users to upload any suspicious link or file recognized as phishing, and then analyzes it via a machine able to apply VirusTotal API functionality. The reinforcement learning mechanism is responsive to new techniques being deployed in the phishing space; hence, with time, improving the precision of detection. Furthermore, it provides users with a comprehensive view of how different antivirus vendors perceive the file or URL as malicious to ensure transparency in threat assessment. The approach tackles the weaknesses of traditional signature detection by adopting a flexible, data-centric approach. The system has been verified with sufficient testing against a large variety of phishing threats, thus yielding real-time responses with great accuracy. In particular, the task is designed to assist both individual end-users as well as cybersecurity professionals in identifying and responding to phishing threats efficiently, thereby increasing the overall awareness of various cyber threats.