Optimal Attack Strategy Based on Limited Cost Model on Complex Network

Abstract

The problem of network disintegration has broad applications and recently has received growing attention, such as network confrontation and disintegration of harmful networks. This paper first presents a limited cost model of attack strategy on complex networks, and the network performance is quantitatively measured by the size of the largest connected component. Here, we introduce the unequal probability sampling into the network disintegration problem to identify the optimal attack strategy, in which node coding is proposed. The efficiency of the proposed solution was verified by applying in model network and real-world network. Numerical experiments suggest that our solution can sift the optimal attack strategy regarding the attack cost. We get some insightful conclusions about the relationship between attack cost and the optimal attack strategy. We find that the low-degree nodes are attacked preferentially when the total cost is deficient, moreover, the high-degree nodes are attacked preferentially when the total cost is sufficient. However, there is a climax, the high-degree nodes won't be attacked preferentially if the cost of single node is more than a threshold. We believe our understanding will be helpful to decision-maker.