(untitled) (Journal of Pharmaceutical Negative Results, 2023)
Phishing is one of the biggest crimes in this world in which it involves thefting the user’s sensitive data. Usually, phishing websites targets individual’s websites, organizations, sites for cloud storages, and government websites. Most of the users while surfing on internet are unaware of the phishing attacks. Many existing phishing approaches have been failed for providing a proper way to the issues facing for E-mails attacks. Currently hardware based phishing approaches have been used due to software attacks it rises a large factor. Due to rise of these kinds of problems, the proposed research work focused on three stage phishing series attack for precisely detecting the problems in a content based manner and the method was named as Phishing Attack Mechanism. Three input values had been taken such as Uniform Resource Locators, traffics and web content as input features by based on features of phishing attack and non-attack of phishing website technique features are implemented. To implement the experimental analysis proposed Phishing Attack Mechanism, dataset is collected from the recent phishing cases. In which it has been founded that the real phishing cases from proposed giving a higher accuracy on both zero-day phishing attack and in both phishing attack detections. Three different classifiers were used to find out the classification accuracy in order to detect the phishing, which yields the 95.18%, 85.45%, 78.89%, by NN, SVM, & RF classifications respectively. The results suggested and recommended is better for detecting the phishing by machine learning approach among the different approach.