A Novel Traffic Reduction technique and ANFIS Based Botnet Detection

摘要

This work proposes a new approach to detect botnet activity based on traffic behavior analysis by classifying network traffic behavior using adaptive neuro fuzzy inference system with traffic reduction. Network traffic information is retrieved from various network elements without affecting network performance. We study the possibility of finding botnet activity without analyzing the whole network flow. Adaptive Neuro Fuzzy Inference System (ANFIS) is used to train the system for future prediction. In addition to botnet detection, we develop a traffic reduction algorithm to reduce the amount of network traffic and to improve the overall system performance. Simulation results show that the proposed system achieves a high detection rate (98.75%) and a low false positive rate. The traffic reduction algorithm reduces an average traffic by 90%.