An Efficient Phishing Attack Detection using Machine Learning Algorithms

Abstract

Phishing is an illegal method which involves user's personal information at high risk. Phishing websites prey individuals, the cloud storage hosting companies and government agencies. Though there are various anti-phishing approaches like hardware as they are not cost effective and they don't choose these approaches. To overcome this, many software-based techniques are used. Zero-day phishing problem cannot be omitted with the existing models. To prevail over these issues and detect phishing attack an approach using heuristic methodology has been proposed. We classify whether a link is phishing or non-phishing based on the input features we take like Web Traffic and Uniform Resource Locator (URL). The proposed methodology is executed by retrieving datasets from phishing cases and Machine Learning model using algorithms like Random Forest, SVM, Genetic.