Efficient Modelling and Analysis on the Propagation Dynamics of Email Malware Filtering for Sustainable IT Development

TLDR: In this paper, the authors used Bloom filter to analyze the network traffic to identify the same email from a known IP address to various routes and identify disruptions on the network, and classified the email data into spam and harm mails.

Abstract: Email system is one of the most effective and commonly used sources of Communication. Unfortunately, the Email system is getting threatened by spam emails. Email spam, also known as junk”email or unsolicited bulk email (UBE),”is a category of electronic spam which includes almost identical messages sent by email to multiple recipients. In existing system highly parallel encoding technique was used to detect the spam campaigns. Privacy preserving collaborative spam detection is used at the Receiver side. In the proposed system the modern spam filtering techniques are deployed at Sender Side. To increase the internet bandwidth and storage of the mail server to deploy WorldNet and Spambot. In this paper to use bro Intrusion detection to analyze the network traffic. It counts the number and regularity of the same”email”sent from a known IP address to various routes, and identifies disruptions on the network. Because of the large number of emails reported in the SMTP sessions, we efficiently monitor and process them in the Bloom filters. The process of spam filtering classified the email data into spam and harm mails.