Machine Learning based E Mail Phishing Detection and Prevention Technique: A Survey
Email has widely used for generate the intrusion over the network. NLP based techniques alreadyintroduced to extract the features from available data set and select the important features, and build thetrain model for background knowledge (BK) TF IDF is very popular technique which has been used byrecent researches. Correlation co occurrence, weighted term frequency and Stanford NLP features hasused to build the train module. In this research we propose email phishing detection and prevention usingvarious machine learning algorithms. Initially system deals with synthetic female stammer data set whichalready contains some normal as well as malicious contains. Many existing systems have already donestatistical approaches to detect malicious emails. The proposed idea illustrates supervised learningapproach to detect email spam's. This research also focused on how system works with machine learningas well as deep learning algorithms. The estimated results for propose system should be higher thanclassical detection approaches.