Paper Contents
Abstract
The most dangerous criminal activity in cyberspace is phishing. The huge number of populated people access administrative and financial institution services online, phishing attacks have rapidly developed over the past decades. The first time scammers made money, they turned it into a lucrative business. Phishing is a tactic used frequently to trick people into providing their sensitive content by implementing phoney websites. Phishing website domains are used to raid sensitive information like userids, countersigns, and other bank content. Phishers use web browsers that aesthetically and linguistically resemble the genuine websites. Phishing techniques started to advance quickly as technology continued to advance, and this should to be terminated by using anti-social techniques to identify unsafe browsers. To combat phishing attacks, machine learning is a potent tool. This study examines machine learning-based detection methods and the features that go into those methods.
Copyright
Copyright © 2023 Pavan Suhas Reddy Medapati. This is an open access article distributed under the Creative Commons Attribution License.
