Blocking Of Spam Mail Using K-Means Clustering Algorithm

Abstract

Email is a method of exchanging digital messages between people using digital devices such as computers, tablets and mobile phones. Email spam also known as junk email is unsolicited bulk messages send through email. The use of spam has been growing in popularity since 1990s and is a problem faced by most email users. Recipients of spam often have had their email addresses obtained by spambots which are automated programs that crawl the internet looking for email addresses. Origin blacklisting is used to detect and filter these kinds of emails. The sources of emails are provided by origin detection. In this origin identity, the spam blocking system finds the source and if any source matches with the user identity, the spammer is blocked to send email. But the system cannot check the contents of spam. The Propose system verifies the mail contents. If the spam content matches with the spam database cluster, then it blocked while sending to receiver. In this system blocks the mail and prevents the flow of data in a network. The porter stemmer and k-means clustering algorithms are using in this propose system.

K-Means Clustering with Local Distance Privacy

“…Manuscript received: 2022-08-01; revised: 2022-10-10; accepted: 2022-12-03 segmentation [1] , spam filtering [2] , malware detection [3] , and so on. However, this data analysis is based on users' personal data, which include users' sensitive and even confidential information [4][5][6] .…”