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Optimal Network Hardening Model Based on Parallel Genetic Algorithm

机译:基于并行遗传算法的最优网络硬化模型

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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.
机译:由于硬硬网络的方法具有不可避免的指数较差的案例复杂性,并且不可扩展到大型网络,本文通过组合攻击图和并行遗传算法基于并行遗传算法基于并行遗传算法的最佳网络硬化模型(ONHM)。首先,我们描述了最佳的网络硬化问题;其次,我们建立了一个相应的数学模型,它将最佳网络硬化问题转换为罚款的非约束优化问题。通过大量重复的实验室测试,实验结果显示ONHM可以找到最佳的网络硬化,并且可以应用于大规模网络。

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