Optimization of Malicious Traffic in Optimal Source Based Filtering

Traffic and spam are the main problems in the data transmission through the network. Many traffic filtering systems have been proposed to find and filter the traffic over the network. The system Optimal Source Filtering (OSF) has implemented a new and optimal filtering mechanism. The new mechanism named as DROP, which monitors and filters the spam and malicious traffic over a network effectively. Traffic filtering systems have been proposed to detect the spammer and malicious traffic, using the optimal rules and policies.

Further these systems are highly ineffective when they encounter malicious traffic. The proposed system introduced OSF protocol, which helps to improve the efficiency of the firewall and filters based on the user rule. The proposed filtering scheme provides TFS false filtering when the flash crowd occurred. The protocol verifies users and firewall rules and policies with the data priority model, which makes the filtering process more robust and fastest manner.

The Proposed spam detection project identifies and eliminates unwanted messages by monitoring outgoing messages. The spam detection is the main challenging task in the network. In the existing system spam detection has implemented after the data received. According to the user rule and request the current system identifies the spam and zombies by monitoring every outgoing message from the sender.