Automatic based framework by using PCA and deep learning for website phishing classification

An example of online identity theft is phishing. Phishers utilize social engineering to obtain victims' financial account information and personal digital identity information. Social engineering scams utilize phony emails to deceive unsuspecting victims into visiting bogus websites that ask for financial information and is called as deceptive phishing attack (PA). Deep learning (DL) algorithms are constantly improving, for making it simpler to identify phishing websites and reducing human errors and minimizing detection times. The overall objective of this research was to achieve high accuracy (Acc) that would aid in spotting phishing websites. DL algorithms, branches of artificial intelligence (AI) are applied in this work to capture the inherent characteristics of the website and classify websites as phishing or non-phishing. The results show that the proposed CNN model achieved the highest Acc of 97.28%.