Malicious objects trafficking in the network

Traffic control and management is the crucial factor for the smooth running of the network and network management. When a packet travels in the cyber space it moves according to the routing protocols. But still there are traffic problems and an attempt is made to solve this problem with mathematical modeling using querying theory. Internet traffic contains different type of packets such as IP, TCP, UDP, SMTP, FTP, ARP, etc. These packets are vulnerable to cyber attacks, which leads to various problems in the network and cost damages in the network. Various cyber attacks such as DDoS which consume excessive bandwidth can easily be detected by using queuing model. In this paper we propose a queuing model for the incoming traffic. Our aim is to filter malicious information in the early stage of the attack and reduce the unnecessary false positives. We consider the Poisson distribution of the traffic arrival and model the system as M/M/1/∞/∞ queuing model to detect the malicious traffic. We also incorporate the concept of self-similarity to detect the self-similar patterns in the traffic (which a major cause of the cyber attacks) and the abnormal behavior of the internet traffic.