An efficient flow based botnet classification using convolution neural network
Vattan Kant, Er. Mandeep Singh, Nitish Kumar Ojha · 2017
Botnets have the most propel group of malware, which appreciates the procedures of all other relatives including worms, rootkits, indirect accesses, and Trojan. The control (c2c) correspondence channel group a malware into botnet family. Systems in botnet writing are focusing on system header data just to arrange botnet conduct utilizing machine learning approaches. Despite the fact that these systems indicates promising outcome yet incorporated system stream accumulations are one of the real test in these systems. In this paper, we propose a botnet location in programming characterized organizes by gathering incorporated system stream measurements in type of Open Flow counters. In this paper use deep learning approach with convolution network, In our experiments CNN significance high accuracy compare to naïve Bayes, SVM and Random Forest.