An Effective Phishing Site Prediction using Machine Learning
Aman Raj Pandey, Tushar Sharma, Subarna Basnet, Ankesh Kumar, Sonia Setia · 2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) · 2022
As the human race is getting advanced with the technology in today’s era, the threat to get damage has also increased. In cyberspace in which we are using the internet and services, there are always some people who try to exploit users by many methods, which can lead to personal to financial loss. Over the past few years, phishing attacks are one which rapidly increased. In this paper, we have proposed API (application programming interface) to predict whether a particular website is malicious or not by providing a strong background to our model with the help of machine learning, regression, and naive Bayes algorithm, our system attains an accuracy of 98% which is better than most of the available systems. We have also presented the research accomplished as of now. Our method outperforms the currently available blacklisting methods.