A Systematic Literature Review on Phishing and Anti-Phishing Techniques

TL;DR

This paper systematically reviews various phishing types and anti-phishing techniques, highlighting machine learning as the most effective approach for detection and prevention based on analyzed literature.

Contribution

It provides a comprehensive classification of phishing methods and evaluates the effectiveness of anti-phishing techniques, emphasizing the role of machine learning.

Findings

Spear phishing, email spoofing, email manipulation, and phone phishing are most common.

Machine learning approaches have the highest detection accuracy.

80 articles analyzed using systematic review and Tollgate Approach.

Abstract

Phishing is the number one threat in the world of internet. Phishing attacks are from decades and with each passing year it is becoming a major problem for internet users as attackers are coming with unique and creative ideas to breach the security. In this paper, different types of phishing and anti-phishing techniques are presented. For this purpose, the Systematic Literature Review(SLR) approach is followed to critically define the proposed research questions. At first 80 articles were extracted from different repositories. These articles were then filtered out using Tollgate Approach to find out different types of phishing and anti-phishing techniques. Research study evaluated that spear phishing, Email Spoofing, Email Manipulation and phone phishing are the most commonly used phishing techniques. On the other hand, according to the SLR, machine learning approaches have the highest accuracy of preventing and detecting phishing attacks among all other anti-phishing approaches.