Improving the attack tolerance of scale-free networks by adding and hiding edges

An edge compensatory model with the tunable parameter α to guide the process of enhancing the robustness of scale-free (SF) networks by adding new edges is presented. In addition, the ability of the model with different α to resist intentional attacks, simulated as the breakdown of a group of network nodes chosen according to degree, is explored. Simulations show that the robustness against intentional attack can be improved when α< 2. Once α is decreased to − 2, reducing α further does little to enhance the robustness of SF networks. Moreover, a novel edge information protection strategy is proposed. Empirical results have demonstrated how robustness is affected by the strategy. We find that hiding a small quantity of new edges contributes to the improvement of SF networks on attack tolerance. Due to the low cost of hiding edge information and the strongly improved network robustness, the strategy is a cost-efficient enhancement of robustness.