Research on optimal control model of complex networks security risk

Abstract

To solve the problems such as the security risk control and the optimization of the complex networks, an optimal control model of complex networks security risk based on discrete glowworm swarm optimization with key strategy adjustment is proposed. The basic framework of this model is built based on four functional modules including detection and evaluation, strategy selection, control optimization and performance feedback. The optimal evaluation criterions of the security control strategy are constituted of factors such as control cost, benefit reward and negative effect. The discrete glowworm swarm optimization algorithm with key strategy ad-justment is proposed to search for the optimal control strategy of complex network security risk. The concept of control parameter is introduced, whose feedback and adjustment make the optimal control model get evolution-ary. Finally, the model and the algorithm are tested for network security risk optimal control in the Nearest-Neighbor coupled with network, Erdos-Renyi random graph network, Watts-Strogatz small world network and Ba-rabasi-Albert power law network, separately. The availability of the model and the superiority of the algorithm are validated and the effect of the change for the attack strategy to the security risk optimal control model is analyzed by simulations.