Neural network based secure media access control protocol for wireless sensor networks

This paper discusses an application of a neural network in wireless sensor network security. It presents a multilayer perceptron (MLP) based media access control protocol (MAC) to secure a CSMA-based wireless sensor network against the denial-of-service attacks launched by adversaries. The MLP enhances the security of a WSN by constantly monitoring the parameters that exhibit unusual variations in case of an attack. The MLP shuts down the MAC layer and the physical layer of the sensor node when the suspicion factor, the output of the MLP, exceeds a preset threshold level. Backpropagation and particle swarm optimization algorithms are used for training the MLP. The MLP-guarded secure WSN is implemented using the Vanderbilt Prowler simulator. Simulation results show that the MLP helps in extending the lifetime of the WSN.