DFCL: DYNAMIC FUZZY LOGIC CONTROLLER FOR INTRUSION DETECTION

Abstract

Intrusions are a problem with the deployment of Networks which give misuse and abnormal behavior in running reliable network operations and services. In this work, a Dynamic Fuzzy Logic Controller (DFLC) is proposed for an anomaly detection problem, with the aim of solving the problem of attack detection rate and faster response process. Data is collected by PingER project. PingER project actively measures the worldwide Internet’s end-to-end performance. It covers over 168 countries around the world. PingER uses simple ubiquitous Internet Ping facility to calculate number of useful performance parameters. From each set of 10 pings between a monitoring host and a remote host, the features being calculated include Minimum Round Trip Time (RTT), Jitter, Packet loss, Mean Opinion Score (MOS), Directness of Connection (Alpha), Throughput, ping unpredictability and ping reachability. A set of 10 pings is being sent from the monitoring node to the remote node every 30 minutes. The received data shows the current characteristic and behavior of the networks. Any changes in the received data signify the existence of potential threat or abnormal behavior. D-FLC uses the combination of parameters as an input to detect the existence of any abnormal behavior of the network. The proposed system is simulated in Matlab Simulink environment. Simulations results show that the system managed to catch 95% of the anomalies with the ability to distinguish normal and abnormal behavior of the network.