Application of Back Propagation Neural Network with Simulated Annealing Algorithm in Network Intrusion Detection Systems

摘要

In this paper, we apply the back propagation neural network (BPNN) into the network intrusion detection system (NIDS). To overcome the training speed and local optimality, we propose a new algorithm of simulated annealing back propagation (SABP), incorporating BPNN with simulated annealing algorithm (SAA). The simulations results show that our proposed SABP outperforms the original BPNN in terms of the training speed.