Optimal Network Hardening Model Based on Parallel Genetic Algorithm

Because the existed approaches to harden networks have an unavoidable exponential worse-case complexity, and are not scalable to large networks, this paper proposes an optimal network hardening model (ONHM) based on parallel genetic algorithm by combining attack graphs and parallel genetic algorithm. Firstly, we describe the optimal network hardening problem; secondly, we establish a corresponding mathematical model, which converts the optimal network hardening problem to a non-restraint optimization problem with penalty. Through a large number of repeated laboratory tests, the experimental results show ONHM can find the optimal network hardening, and can be applied to large-scale networks.