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Phishing Detection in E-mails using Machine Learning
| International Journal of Applied Information Systems |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 12 - Number 7 |
| Year of Publication: 2017 |
| Authors: Srishti Rawal, Bhuvan Rawal, Aakhila Shaheen, Shubham Malik |
10.5120/ijais2017451713
|
Srishti Rawal, Bhuvan Rawal, Aakhila Shaheen, Shubham Malik . Phishing Detection in E-mails using Machine Learning. International Journal of Applied Information Systems. 12, 7 ( October 2017), 21-24. DOI=10.5120/ijais2017451713
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.
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