… and implemented for detection and prevention of phishing attacks most of … detection. The
contribution of this study is to compare the predictive accuracy of six classifiers on a phishing …

… Therefore, effective counter measures that can accurately detect phishing are needed.
Machine learning (ML) is a popular tool for data analysis and recently has shown promising …

… Classification accuracy in our experiment is the rate of phishing and legitimate websites
which are identified correctly with respect to all the websites, defined as follows: …

… Networks holds the most promise for accurate phishing detection with accuracy of 99.4%. …
, s., Nappa, D., Wang, X., Nair, s.: a comparison of machine learning techniques for phishing …

… Thereafter, we searched and chose the classifiers that we will use for accuracy comparison.
The chosen classifier and split data module must be connected to the train model module. …

… Consequently, more effective phishing detection is required … accuracy detection of phishing
sites. The proposed approach utilizes convolutional neural networks (CNN) for high accuracy …

… , furthermore, give a far-reaching overview and comparison of these kinds of literatures to …
Woźniak, “Accurate and fast URL phishing detector: A convolutional neural network …

… less accuracy than the proposed model in detecting phishing … of accuracy in the proposed
model compared to the detector … comparison in terms of the accuracy of detection of phishing …

… to detect phishing websites, and comparisons were made. We … features for the detection
of phishing webpages extracted … had the best accuracy based on the comparison results (ie, …

… For evaluations, comparisons are provided between different … an accuracy of 95.02% on our
dataset and an accuracy of 98.58… The reason behind the comparison with these works is due …