Phishing website detection using machine learning algorithms

The objective of the work is to propose phishing website detection using machine learning. The online shoppers often provide sensitive information such as passwords, usernames, and credit card details, which makes them vulnerable to phishing websites that use such information for malicious purposes. To combat this problem, we have introduced an intelligent, adaptable, and efficient system that leverages machine learning techniques to detect and predict phishing websites. Our system utilizes a classification algorithm and methods for identifying phishing criteria to determine their authenticity. By analysing key features such as URL and domain identity, security, and encryption criteria, our system achieves a high rate of phishing detection. The system can be used by e-commerce businesses to secure their transaction process, and the machine learning algorithm used in our system outperforms conventional classification algorithms, providing online shoppers with a secure and confident shopping experience, our system willuse a machine learning algorithm to detect fraudulent websites. This application can be utilized by various e-commerce enterprises to secure the entire transaction process. Comparing this system’s machine learning method to other conventional classification algorithms, it performs better. The user can buy goods without any hesitation online with the aid of this method.