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In today's digital age, phishing attacks have become a frequent and advanced threat, targeting individuals and organizations. These attacks employ deceptive emails, websites, messages, etc. They aim to trick users into giving sensitive information, such as passwords, credit card details, account login details, etc. The increasing frequency and sophistication of phishing attacks emphasize the need for effective detection and prevention methods. This paper provides an analysis of various research on multiple algorithms to help prevent phishing by using artificial intelligence, such as Decision Tree, and Naive Bayes, among others.

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Artificial Intelligence-Driven Solutions for Phishing Detection: A Comparative Analysis of Machine Learning Models

  • 章节

  • 发表日期：

    2026年

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  • Renata Castellanos,
  • Ali Al-Sinayyid,
  • Elias Valencia,
  • Joshua Gilliland,
  • Esther Dhiramo,
  • Austin Higginbotham,
  • Natwange Chiwele

摘要

In today's digital age, phishing attacks have become a frequent and advanced threat, targeting individuals and organizations. These attacks employ deceptive emails, websites, messages, etc. They aim to trick users into giving sensitive information, such as passwords, credit card details, account login details, etc. The increasing frequency and sophistication of phishing attacks emphasize the need for effective detection and prevention methods. This paper provides an analysis of various research on multiple algorithms to help prevent phishing by using artificial intelligence, such as Decision Tree, and Naive Bayes, among others.