Paper Title
A REVIEW OF PHISHING WEBSITE DETECTION TECHNIQUES

Abstract
As the technology develops this increases the chance of cybercrimes happening. Phishing attacks based on URLs are among the most common threats toward Internet users. Such attacks are not built upon technical vulnerabilities instead, they exploit a weakness in humans and are often launched against organizations and individuals. Attackers deceive users by clicking on URLs that appear trustworthy,leading them to reveal sensitive information or install malware. Various techniques of machine learning(ML) used for phishing URL detection classify URLs into phishing and legitimate ones. Models remain under development and refinement because of researchers' determination to develop them as accurate and efficient as possible. Different machine learning techniques for detecting phishing URLs accompanied by URL features and datasets that train the models are reviewed. The paper further discusses the many different methods put forth by the researchers to enhance the detection accuracy of these models. Keywords - Phishing detection; feature extraction; machine learning;