Analysis of Machine Learning Techniques for Spam Detection

Abstract

This paper discusses the spam detection and different machine learning models to detect these spam messages. The present work also discusses the testing and evaluation of spam messages. Spam messages have always been very dangerous for computers and networks. They have a very bad effect on the computer security. With the emergence of social media platforms, many people are dependent on emails to communicate, and, with this, there is always a need to detect and prevent spam mails before it enters a user’s inbox. The paper also presents the analyses of different machine learning techniques to detect spam messages. Finally, the paper describes the algorithm which is best to detect spam messages. Spam messages are basically redundant messages which are sent in a large number at once. They can be seen in many forms like free services, cheap SMS plans, lottery, etc. Growing spam messages in your mail can make your inbox filled with ridiculous mails, slow down your Internet speed, and retrieve your private information like credit card details, and has many more drawbacks. Therefore, it is important to prevent it in the best way possible.