Detection of Phishing Websites Using Machine Learning

Abstract

Identity theft is a common and hazardous sort of cybercrime. The purpose of this attack is to obtain identities used by individuals and businesses to conduct transactions.Fraudulent hijacking websites are fake websites that contain various tricks between their content and web-based information. If a user opens a false web page and enters a secure username and password, the user information is retrieved by an attacker who can be used for malicious purposes. Criminal websites to steal sensitive information look very similar in appearance to their official websites in order to attract a large number of internet users. Feedforward neural networks frequently learn at a slower rate than is required. This research offers a new algorithm for hidden single-layer neural networks termed a comprehensive learning machine algorithm (ELM), which randomly chooses hidden nodes and does not overspend data.