Phishing Detection in E-mails using Machine Learning

Abstract

Emails are widely used as a means of communication for personal and professional use. The information exchanged over mails is often sensitive and confidential such as banking information, credit reports, login details etc. This makes them valuable to cyber criminals who can use the information for malicious purposes. Phishing is a strategy used by fraudsters to obtain sensitive information from people by pretending to be from recognized sources. In a phished email, the sender can convince you to provide personal information under false pretenses. This experimentation considers the detection of a phished email as a classification problem and this paper describes the use of machine learning algorithms to classify emails as phished or ham. Maximum accuracy of 99. 87% is achieved in classification of emails using SVM and Random Forest classifier. General Terms Phishing, security, classification