This document discusses the detection of phishing websites using machine learning algorithms. It begins with an abstract that defines phishing and explains why attackers use it. The introduction provides more details on phishing techniques and the need for anti-phishing detection methods. The document then reviews related work on phishing detection using machine learning features. It proposes using algorithms like artificial neural networks, k-nearest neighbors, support vector machines, and random forests. Features for these algorithms are discussed like URL-based, HTML/JavaScript-based, and domain-based features. The document concludes that machine learning classifiers can help detect phishing websites but future work is still needed to develop more effective detection systems.