Robustness of interdependent networks with implicit higher-order support and dependency mitigation mechanisms

In recent years, the robustness of higher-order interdependent networks has become a prominent topic in complex network research. Most previous network models have focused on node failures triggered by initial attacks, overlooking the network’s inherent resilience to external disruptions. To better reflect real-world networks, this paper proposes an implicit higher-order interdependent network model, which captures higher-order interactions more effectively by implicitly representing higher-order information. Additionally, implicit higher-order support and dependency mitigation mechanisms are introduced to study robustness. The mechanism comprises two types of protection: One focuses on the preservation of higher-order information, where nodes receive additional support from their implicit higher-order structures, and the other protects dependent connections, where dependencies between nodes mitigate the effects of attacks. By integrating this mechanism, the paper uses percolation theory to examine changes in the percolation threshold and the giant component under varying protection strengths. The theoretical analysis aligns closely with the simulation results. The study demonstrates that implicit higher-order support and dependency mitigation mechanisms can enhance the robustness of randomly generated networks, as well as in real-world datasets.