"Combating Phishing Attacks Using AI and Machine Learning Technologies"

The advancement of Artificial intelligence (AI) technology and the ease with which the general public can access it has given attackers powerful new capabilities to create more convincing phishing messages for victims. However, AI technology can also be used for good. Before phishing attacks can cause damage to organizations' finances and reputations, defenders are effectively detecting and preventing them. Traditional security solutions cannot completely stop phishing attacks, especially those involving the exploitation of zero-day vulnerabilities. Despite their success in reducing the number of phishing attacks that enable malicious actors to gain access to enterprise Information Technology (IT) environments, many phishing emails can still evade these solutions and reach end users' devices. To use Machine Learning (ML) algorithms to detect phishing attacks, they must be trained on a large dataset of normal (honest) and phishing (suspicious) emails to learn how to catch anomalies and identify common malicious patterns in phishing emails. There are three main ML techniques for detecting phishing emails: social graph analysis, employee communication profiling, and email structural analysis. This article continues to discuss phishing attacks and how ML algorithms are used to fight them. 

Cybernews reports "Combating Phishing Attacks Using AI and Machine Learning Technologies"