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检测横向运动:一个系统的调查调查.

Christos Smiliotopoulos1, Georgios Kambourakis1, Constantinos Kolias2

  • 1Department of Information and Communication Systems Engineering, University of the Aegean, Karlovasi 83200, Samos, Greece.

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PubMed
概括
此摘要是机器生成的。

本调查提供了使用入侵检测系统 (IDS) 识别侧向运动 (LM) 的全面概述,涵盖端点检测和响应 (EDR),机器学习和基于图形的策略.

关键词:
先进的持久性威胁 高级持久性威胁攻击 攻击 攻击这就是为什么物联网物联网物联网.侧向运动 侧向运动网络安全 网络安全

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科学领域:

  • 网络安全 网络安全
  • 网络入侵检测 网络入侵检测

背景情况:

  • 横向运动 (LM) 在MITRE ATT&CK等网络攻击框架中至关重要.
  • 现有的研究缺乏从入侵检测系统 (IDS) 的角度对LM识别的全面调查.

研究的目的:

  • 使用IDS提供横向运动识别的系统和整体概述.
  • 在LM检测的范围内涵盖诸如物联网 (IoT) 等新兴范式.

主要方法:

  • 在8年的时间里对53篇文章进行了系统的调查.
  • 将现有研究分类为三个主要重点领域:终点检测和响应 (EDR) 方案,机器学习解决方案和基于图形的策略.

主要成果:

  • 确定了LM检测研究中的关键趋势和相互关系.
  • 突出了EDR,机器学习和IDS的基于图形的方法的进展.

结论:

  • 该调查解决了通过IDS了解LM识别的差距.
  • 提供了关键观察结果,以指导未来的研究,以推进LM检测技术.