Logistic Regression based Machine Learning Technique for Phishing Website Detection
T. R. Soumya, Ramesh P, N. Arockia Rosy, N. Pughazendi, S. Padmapriya, Rashmita Khilar · 2022 4th International Conference on Inventive Research in Computing Applications (ICIRCA) · 2022
Nowadays, many people start switching from offline to online to save their precious time. They started buying products online and made their payments through online transactions across websites. These online buyers are asked to provide details such as their name, address, location, passwords, and other essential bank details on that particular website. The unaware online buyer got caught in these sites, which leads to a process of phishing. They are called phishing websites. This research work has proposed an efficient prediction method based on the machine learning technique to analyze and predict these phishing websites. Novel classification algorithm and techniques are used to analyze and extract the datasets that might maliciously cause phishing. The essential traits are helpful to identify these types of phishing sites such as domain, URL and encryption technique of a website while detecting malicious data. This research work will use a logistic regression algorithm for detecting the phishing website. A logistic regression algorithm is used to provide better performance than the traditional classification algorithm. To protect user sensitive information and for effective, secure transaction payments, many E-commerce enterprises are using this application to stay on the safer side.