A Pattern Recognition Scheme for Distributed Denial of Service (DDoS) Attacks in Wireless Sensor Networks

We define distinct attack patterns depicting distributed denial of service (DDoS) attacks against target nodes within wireless sensor networks for three most commonly used network topologies. We propose a graph neuron (GN)-based, decentralized pattern recognition scheme for attack detection. The scheme does analysis of internal traffic flow of the network for DDoS attack patterns. We stipulate that the attack patterns depend on both the current energy levels, as well as the energy consumption rates of individual target nodes. The results of varying pattern update rates on the pattern recognition accuracies for the three network topologies are included in the end to test the effectiveness of our implementation