MAC Layer Misbehavior Detection Using Time Series Analysis

This paper presents a solution to the real-time detection of MAC layer misbehaviors in IEEE 802.11 networks. Among the wide range of misbehaviors, we focus on the sender side selfish behavior that creates a channel- capturing effect by using favorable parameters, and the receiver side selfish behavior that does not respond with CTS and ACK upon receiving RTS and data packets, which clears the channel for itself and causes its sender to waste resources. These misbehaviors are subtle to detect, and yet can undermine the performance of the well-behaved nodes significantly. This paper shows a powerful real-time detection method that can catch these misbehaviors as soon as they have started. The detection method requires collecting delay, throughput, and packet interval data to generate time series and applying a sequential change point detection algorithm on the data streams as soon as new data points come in. All attacks are simulated in ns-3 and the simulation results verified the effectiveness of the detection method.