Abstract: Email Spam has become a major problem nowadays, with Rapid growth of internet users, Email spams are also increasing. People are using them for illegal and unethical conducts, phishing and fraud. Sending malicious links through spam emails which can harm our system and can also seek in into your system. Creating a fake profile and email account is much easier for the spammers, they pretend like a genuine person in their spam emails, these spammers target those people who are not aware about these frauds. So, it is necessary to Identify those spam mails which are fraudulent. This project will identify those spam by using techniques of machine learning, this paper will discuss the machine learning algorithms and apply all these algorithms on our data sets and the best algorithm is selected for the email spam detection having best precision and accuracy.
Keywords: Machine learning, Naïve Bayes, support vector machine-nearest neighbour, random forest, bagging, boosting, neural networks.
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DOI:
10.17148/IJARCCE.2023.125124
