Phishing Attack Detection using NLP and Machine Learning

It’s observed that in recent years, cyber-attacks are becoming a regular threat. In conventional phishing attacks, targeted users are redirected to visit a fake or counterfeit website, for taking out personal information and credentials like banking information, credentials, and even UPI wallets. Usually, phishing attacks happens using email, text messages, and voice calls by forwarding fake website URL. This attack is not only referring to users who have very little information about this fraud but also those who have good and sound knowledge of this type of attack. Detection of a Social engineering attack such as phishing is a challenging task due to its nature of affecting. In this research, the System uses the approach of detecting this sophisticated attack using ML, NLP, WDM, and MCAM which is the best suitable approach to identify the phishing attack. Machine Learning is the most advanced way of detecting targeted phishing attacks from URL, Email, or SMS. a Detection is done with NLP and Machine learning with attack vectors as a dataset with help of simulators performing data visualization work