DoS attack detection technique using back propagation neural network
Monika Khandelwal, Deepak Kumar Gupta, Pradeepkumar Bhale · 2016
Denial of Service attack is an endeavor to make a gadget or framework resources occupied to its proposed clients. DoS attack expends casualty's framework assets, for example, data transfer capacity, memory, CPU by sending gigantic number of fake requests so that the intended user cannot obtain services and denial of service happens. This paper presents an intelligent technique for the detection of denial of service attack. This technique can easily detect DoS attack by using back-propagation neural network (BPNN). The parameters used in this technique are CPU usage, frame length and flow rate. In this technique, analysis of server assets and network traffic for training and testing the ability of detection method and the results shows that the proposed method can detect DoS attack with 96.2% accuracy.