• Anand S
• Gagan R
• Kartik Naik
• D M Likhit
• Prof. Aravind Naik,Dr. Suresha D,Prof. Shreya Shetty

Phishing attacks pose a severe cybersecurity risk websites to steal data, such as login credentials and financial information. Traditional detection methods like blacklists and rule-based systems often fail to adapt to rapidly evolving phishing techniques. This study proposes a machine learning (ML)-based solution to identify phishing websites by analyzing URL, domain, and content-based features. A diverse dataset of phishing and benign URLs is preprocessed and used to train multiple supervised learning algorithms. The system is designed for real-time deployment, offering scalability and minimal false positives to enhance user protection.

Phishing Web Sites Detection Using Machine Learning Project.

"Phishing Web Sites Detection Using Machine Learning Project.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 7, page no.9-12, July-2025, Available :http://www.jetir.org/papers/JETIRGX06003.pdf

"Phishing Web Sites Detection Using Machine Learning Project.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 7, page no. pp9-12, July-2025, Available at : http://www.jetir.org/papers/JETIRGX06003.pdf