针对分布式靶场大规模网络多粒度节点高效构建方法的研究

Research on Efficient Construction Method of Large-scale Network Multi-granularity Nodes for Distributed Cyber Range

目前网络威胁严峻,网络靶场作为网络风险评估、攻防对抗演练等场景下的安全技术验证手段备受瞩目。合理使用网络靶场内计算资源的开销,高效地完成目标网络构建是当前亟须解决的问题。文章提出了一种大规模、多粒度节点融合的动态网络构建方法,一方面通过多粒度节点协同工作的方式使用靶场内资源,扩大了网络规模;另一方面通过改进E-CCD算法,优化节点间链路添加的时间复杂度,降低网络构建时间。经验证,构建10万级节点规模的大规模网络可在235分钟内完成,可面向目前主流的分布式异构靶场。

The increasing severity of cyber security threats has led to a growing interest in the use of network cyber range as a means of assessing risks,conducting defensive exercises in complex scenarios.A pressing issue is how to reasonably utilize the computational resources within network cyber range to efficiently construct target networks.This paper proposes a largescale,multi-granularity node fusion method for dynamically building networks,which leverages the computational resources by coordinating the work of multiple granularity nodes and expand the network scale.Furthermore,the method improves the E-CCD algorithm to optimize the time complexity of the inter-node link addition,thus reducing time in network construction.Results have shown that the construction of large-scale networks with a node scale of 100000 can be completed within 235 minutes,making it applicable to mainstream distributed and heterogeneous cyber range.