The Research on the expansion scheme of security operation center based on data self-balancing

Peng Lu, Wenjing Zeng, Hang Li, Ruobin Zhang
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Abstract

With the frequent occurrence of security incidents and the continuous growth of data levels, the processing of massive data places higher requirements on the analysis and storage capabilities of the security operation center. The cluster deployment mode makes the horizontal expansion a basic capability of the platform, but how to ensure data integrity and business continuity while expanding nodes is a key issue that needs to be solved. Based on the security operation center of the China Academy of Engineering Physics, this paper studied the technical details of the data migration expansion schemes and data self-balancing expansion schemes, and conducted comparative experiments in the laboratory. Finally, it proves the data self-balancing expansion schemes have more advance and feasibility than the data migration expansion schemes. The data self-balancing expansion schemes has been applied in the online system, which provides a certain reference for the expansion of other big platforms on the secret network in the future.
基于数据自平衡的安全运营中心扩展方案研究
随着安全事件的频繁发生和数据级别的不断增长,海量数据的处理对安全运营中心的分析和存储能力提出了更高的要求。集群部署模式使水平扩展成为平台的基本能力,但如何在扩展节点的同时保证数据的完整性和业务的连续性是需要解决的关键问题。本文以中国工程物理研究院安全运营中心为依托,研究了数据迁移扩展方案和数据自平衡扩展方案的技术细节,并在实验室进行了对比实验。最后,证明了数据自平衡扩展方案比数据迁移扩展方案更具先进性和可行性。数据自平衡扩展方案已在在线系统中得到应用,为今后秘密网络上其他大平台的扩展提供了一定的参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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