Reconfigurable security protocols, with dynamic protocol configuration and flexible resource allocation, have become a state-of-the-art technology to guarantee the security of space-ground integrated network. However, reconfiguration decision-making for reconfigurable security protocols remains a major challenge in order to adapt to diverse secure service requirements and deploy higher security level but more complicated security strategies in nodes with limited resources and computing abilities. To handle this problem commendably, a hierarchically collaborative ant colony–based reconfiguration decision-making model called HiCoACR is proposed. This model, inspired by the ideas of hierarchical reinforcement learning and population collaboration, decomposes the reconfiguration decision-making problem into two sub-problems by introducing a two-level hierarchy ant colony consisting of the Explorer and the Worker. The Explorer controls directions of protocol reconfiguration and generates abstract scheduling sub-goals which are conveyed from the Worker. While the Worker schedules most suitable cryptogram resources for each sub-goal received and produces the optimal reconfiguration solution which is verified and re-optimized by a Lévy process–based stochastic gradient descent algorithm. Both the Explorer and the Worker adopt a modified version of ant colony algorithm to fulfill its targets, where a hierarchical pheromone is defined to reinforce positive behaviors of each ant colony. Experiment results suggest that HiCoACR outperforms baseline algorithms and possesses well model transferability.
展开▼
