An Anomaly Detection Framework for Internal and External Interaction of Power Grid Information Network based on the Attack-chain Knowledge Graph

Qianqian Jin, Mingyan Li, Peng Gao, Yenjou Wang
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Abstract

With the gradual opening of the interaction method between the internal and external network, how to effectively detect the attack for the internal network through the external network becomes more and more important. However, traditional security protection measures cannot well detect unknown attacks and multi-step attacks, which leads to a constant threat. This paper proposes a network security knowledge graph model based on an extended attack-chain, combined with a multi-layer anomaly detection system to detect the threat lurked in the network. Finally, the application of the multi-layer anomaly detection framework in the security protection for internal and external boundary of state grid information network is prospected.
基于攻击链知识图的电网信息网络内外交互异常检测框架
随着内外网交互方式的逐渐开放,如何通过外部网络有效检测对内部网络的攻击变得越来越重要。然而,传统的安全防护措施无法很好地检测未知攻击和多步骤攻击,导致威胁持续存在。本文提出了一种基于扩展攻击链的网络安全知识图模型,结合多层异常检测系统来检测网络中潜伏的威胁。最后,展望了多层异常检测框架在国网信息网络内外边界安全保护中的应用。
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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