Detection and classification of phishing websites

Abstract

‘Phishing sites’ are some type of the internet security issues that mainly targets the human vulnerabilities compared to software vulnerabilities. Phishing sites are malicious websites that imitate as legitimate websites or web pages and aim to steal user’s personal credentials like user id, password, and financial information. Spotting these phishing websites is typically a challenging task because phishing is mainly a semantics-based attack, that mainly focus on human vulnerabilities, not the network or software vulnerabilities. Phishing can be elaborated as the process of charming users in order to gain their personal credentials like user-id’s and passwords. In this paper, we come up with an intelligent system that can spot the phishing sites. This intelligent system is based on a machine learning model. Our aim through this paper is to stalk a better performance classifier by examining the features of the phishing site and choose appropriate combination of systems for the training of the classifier.