Seperation of Phishing Emails Using Probabilistic Classifiers
R Ishwarya, S Muthumani, Siva Sharma Karthick, S. Suriya · 2023
The activity of phishing has been carried out in more area nowadays and it is growing with advancements. Till now there are few methods to overcome the phishing but those are not up to the level of expectation. Phishing attempts have grown 65% in the last year and it is still growing rapidly. So that cost of the damage caused by it for mid-size companies is $1.6 million. Our work is to detect malicious emails and do the codification by using probabilistic classification. Victims trust the emails so the phishers can easily hack the information. In this work, a phishing detection method is proposed by using Naive bayes algorithm, SVM, KNN and RF. It involves collecting the datasets, pre-process and filter the data using string to word vector filter. Then classification of email data as spam or not spam and finally analysis about the performance accuracy.