Study of Botnet Attacks Using Rapid Miner

Abstract

Botnet attacks are on the upswing due to the speedy development of networks and network related technology. Botnets pose a serious security risk to our network since they are extensively utilized for cyber-attacks such as Denial of Service (DoS), Distributed Denial of Service (DDoS), backdoor attacks, and others. By combining the bandwidth and resources of the victim system, a botnet might do catastrophic harm to our network. The project will provide a comprehensive overview of botnet attacks, with an emphasis on DoS and DDoS. There are facts regarding bot traits and behaviours. To train our model for preventing Botnet attacks, we use Machine Learning Auto Modelling. We will do a benchmark of DoS and DDoS. We present the results on a static webpage. Wireshark will be used for opening the network monitored .pcap network files, while Rapid Miner will be used as an Auto modelling machine learning tool and for result visualization in this project