SPAMMER DETECTION USING MACHINE LEARNING ALGORITHM

Abstract

Due to the growth of communication technology common people also uses internet.
E-mail is one of the important applications of internet. E-mail is used send and
receives any type of information within a short period by using their Mail-Id. This is
the easiest way to create a communication to the people in all over the world.
Sometimes the unwanted mails are available in our inbox. These unwanted E-mails
are called spam. The main purposes of spam are send advertisements regarding their
services and products to the multiple persons at the same time. But rarely the
unwanted email contains malwares. The malwares are spoiling the user’s stored data
on the local system. Now the world is moving from traditional technologies to the
current communication technology such as IoT (Internet of Things). The applications
of IoT are very large. It is used in various domains. Most of the industries are also
move from their existing system to IoT concept. The main aim of the IoT is
connecting various devices and objects with the help of internet. In production
industries also used the concept IoT to connect various devices in an organization and
mobile cloud computing concept. It provides the actual task of machineries and
optimizes their production. But sometimes this option can be used by spammers to
spoil the power of manufacturing industries. Due to these spammers the production of
the company will be spoiled. To avoid this problem various type of machine learning
algorithms are used. Finally the various machine learning algorithms are compared
with their accuracy, true positive rate and false positive rate.