Abstract:
As online activities surge, the threat of fraudulent websites posing security risks escalates. This project introduces an innovative approach leveraging machine learning for the automated identification of fraudulent website URLs. The proposed system combines advanced algorithms and features to enhance accuracy and efficiency in distinguishing legitimate and malicious URLs, thereby fortifying cybersecurity measures.

Existing System:
Currently, identifying fraudulent website URLs r ....