QoS based Optimal Source Filtering for Malicious Traffic Environment for Network Stability

Abstract

In data transmission, network faces two main problems namely Traffic and spam. Nowadays many researchers were working in traffic filtering systems to find and filter the traffic over the network. The Optimal Source Filtering (OSF) is a system which is proposed and implemented for filtering mechanism. The spam and malicious traffic over a network has been monitored and filtered by a method called DROP. While encounter malicious traffic these systems are highly ineffective. Based on the user rule the efficiency of the firewall and filters were improved by the OSF protocol, introduced by the proposed system. To recover the problem the proposed filtering scheme provides TFS false filtering while the flash crowd occurs. The data priority model verifies user and firewall’s rules and policies by the protocol, which makes the filtering process more efficient. By monitoring outgoing messages the proposed spam detection project identifies and eliminates unwanted messages. In the network the spam detection is the task which is more complicated. According to the user’s rule and request, the current system monitors every outgoing message from the sender and identifies the spam and zombies.