Statistical Techniques for Detecting Traffic Anomalies DFD Diagram and Documentation

The main aim of the project is to reduce the traffic caused by the network while transmitting data’s using an egress router and ingress router. In order to reduce the traffic that is caused by the network during the transmission of data with the help of ingress and egress router is the main focus of this project.

Attack on network infrastructure is very frequent and various types of  worms and denial service are used which lead to the need of several latest techniques for monitoring and analyzing the traffic work. If only some efficient tools would have existed then it could be possible to detect the anomalies and attacks. It would also make it possible to take necessary actions to reduce their actions before they can further propagate in the network. For detection of attacks and anomaly various studies are being carried on to know the possibilities of traffic analysis that are based on mechanisms. The onset of traffic can be estimated with a sudden hike in traffic on a particular port.

We approach two types of detection mechanisms that will help to detect the anomalies – real time modes and post mortem. The latter technique usually consumes a lot of time of data as a single set and also employ  rigorous processing methods. Further it is a technique that demands lots of resources for accurate analyzing.

This kind of analysis is usually very beneficial for engineering purposes and understanding the peak demand. On the other side, there is the real time method that analyzes and concentrate a small window of data traffic. It provides a quick dirty waning of the ongoing and impending anomalies of traffic. This analysis does no require any sophisticated equipment’s and resources. This is widely used because of its features like imminence of attacks and less demands. 

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