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What is Phishing Detection via Machine Learning about?

This document summarizes a research paper that proposes using machine learning classifiers to detect phishing attacks. Specifically: 1) It compares benign and malicious websites from the PhishTank database to train machine learning models. 2) It uses feature selection and particle swarm optimization to enhance the classification of phishing website characteristics. 3) It finds that random forest classification achieves an accurate positive detection rate of 98.37% for phishing attacks.

Author

Lppm Politeknik Jambi

Language

EN