Sensor network security defense strategy based on attack graph and improved binary PSO

Abstract

Attack graph is a common tool for qualitative analysis of Sensor network security and it can provide an important basis for security administrators to prevent malicious intrusion. In order to conduct Sensor network security assessment and active defense, this paper proposed a Sensor network security defense strategy based on attack graphs and improved binary PSO. Based on each intrusion action in the attack graph, it constructed a set of weighted defense strategies to emphasize the defense cost. In order to prevent Sensor network malicious intrusion with minimum cost, the strategy introduced and improved binary particle swarm optimization algorithm and obtains the minimum key strategy set of attack graph. Based on the principle of M-IDS combined with game theory and attack pattern mining algorithm of Markov Decision Process (MDP), the optimal protection strategy is determined by game theory, and MDP is used to predict future attacks and design corresponding protection strategies. Simulation experiments show that compared with the ant colony algorithm and greedy algorithm, the proposed strategy can effectively obtain the optimal solution of the minimum key strategy set and it is more efficient.