Detection of Phishing Websites using an Efficient Feature-Based Machine Learning Framework

V V Ramalingam,Paras Yadav, ,Prakhar Srivastava

doi:10.35940/ijeat.c5909.029320

Abstract

Phishing is a cyber-attack which is socially engineered to trick naive online users into revealing sensitive information such as user data, login credentials, social security number, banking information etc. Attackers fool the Internet users by posing as a legitimate webpage to retrieve personal information. This can also be done by sending emails posing as reputable companies or businesses. Phishing exploits several vulnerabilities effectively and there is no one solution which protects users from all vulnerabilities. A classification/prediction model is designed based on heuristic features that are extracted from website domain, URL, web protocol, source code to eliminate the drawbacks of existing anti-phishing techniques. In the model we combine some existing solutions such as blacklisting and whitelisting, heuristics and visual-based similarity which provides higher level security. We use the model with different Machine Learning Algorithms, namely Logistic Regression, Decision Trees, K-Nearest Neighbours and Random Forests, and compare the results to find the most efficient machine learning framework.

Highlights

IntroductionEach task ranging from buying groceries to handling bank statements can be done with just a few clicks
To make predictions we have evaluated the performance of 5 different Machine Learning Algorithms, namely, Logistic Regression, K-Nearest Neighbours, Support Vector Machines, Decision Trees and Random Forests
Machine Learning is the perfect candidate suited to identifying phishing web pages as it can automatically learn to identify phishing websites

Summary

Introduction

Each task ranging from buying groceries to handling bank statements can be done with just a few clicks. Governments are encouraging their people to join the movement be a part of the era of digitization which has motivated the masses to be more and more active on the Internet. A lot of these people are unversed to the threats that they are exposed to once they surf the internet. This forms a huge population of vulnerable people that can be targeted by an army of cyber criminals waiting to hunt down pregnable internet users.

Methods

Results

Conclusion