Detection of Phishing Attacks on Online Collaboration Tools Using Logistic Regression

Abstract

Phishing is a process and activity related to the security of the internet, and it does not target only the software but to data that is vulnerable to day-to-day activity in human life. This can also be narrated as striking or pouncing on innocent online users to steal very sensitive information eventually causing financial losses and damaging the credentials of individuals. Phishing is a very commonly used means of threat on the internet which resulted into the growth of the World Wide Web in volume significantly in recent times. In general, Phishing criminals use the latest and highly sophisticated methods to fool online users i.e. zero-day. Therefore, it is very essential that the anti-phishing system be real fast, real time and holds from the intelligent phishing detection solution. The need of the hour is that we establish a detection system that will adjustably meet the transposing environment and phishing websites. As the approach proposed extracts various kinds of perceptive aspects from the source-code of webpages and URLs, it is completely a tailor-made solution from the clientele side and it does not require any third-party service. In this paper, the system is intelligent; it provides a brilliant system for detecting or to finding out phishing websites. The entire system is a machine learning based, significantly monitor learning in particular. As the best presentation in categorization the Logistic Regression Technique has been selected.