Fighting cyber crime in email spamming: An evaluation of fuzzy clustering approach to classify spam messages
Arie Wahyu Wijayanto, Takdir Takdir · 2014
The rising of the modern Internet brought with it heap opportunities for attackers to gain illegal benefit from spreading spam mail. Spam is irrelevant or inappropriate messages sent on the Internet to a large number of recipients. Many researchers use a large number of classification method in machine learning to filter spam messages. But, there is still limited research which evaluate the use of clustering task in data mining to perform spam email segmentation. In this paper we endorse for fighting cyber crime by evaluating the fuzzy clustering approach in classifying spam emails using one of the most popular and efficient method in this field, Fuzzy C-Means. The experimental studies on public spam data set using various different parameter give promising result in this process.