Identification of Spam Data in Cloud Environment

These days, most of the people using electronic mail for communication. Mostly all the industries, from business to education use email for communication. But there are many useless emails are received by spammers called as spam emails. Emails are the good opportunity for spammers since they able to use it for bad purposes like for their financial benefits, credit card information, market growth etc. The primary goal of spammer is to hack the sensitive and personal information of the user like contact details, bank account details etc. The spam emails are rapidly increased and fills with a lot of ridicules and useless mails which degrades our internet speed. Cloud computing is the user demand availability for data storage and security of user's personal information. In this paper, different machine learning techniques are used Naive bayes(multinomial and bernoulli), Support Vector Machine and decision tree to identify spam emails. First, taking a dataset and perform Exploratory Data Analysis and after that preprocess the data and pick features and build model and find the accuracy. In this paper, experiments have shown that the multinomial naive bayes technique return the good accuracy.