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Detect and correlate information system events through verbose logging messages analysis

机译:通过详细的日志记录消息分析来检测和关联信息系统事件

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摘要

Detecting and tracking events from logging data is a critical element for security and system administrators and thus attracts more and more research efforts. However, there exists a major limitation in current processes of Event Logging analysis, related to the verbosity and language-dependence of messages produced by many logging systems. In this paper, a novel methodology was proposed to tackle this limitation by analysing event messages through a Natural Language Processing task in order to annotate them with semantic metadata. These metadata are further used to enable semantic searches or domain ontology population that help administrator to filter only relevant event and to correlate them for a prompt and efficient response and incident analysis.
机译:从日志记录数据中检测和跟踪事件是安全和系统管理员的关键要素,因此吸引了越来越多的研究工作。但是,在当前事件日志分析的过程中存在一个主要限制,与许多日志系统生成的消息的详细程度和语言相关性有关。在本文中,提出了一种新颖的方法来解决此限制,方法是通过自然语言处理任务分析事件消息,以便使用语义元数据对其进行注释。这些元数据还用于启用语义搜索或领域本体填充,以帮助管理员仅过滤相关事件并将它们关联起来,以进行快速有效的响应和事件分析。

著录项

  • 来源
    《Computing》 |2019年第7期|819-830|共12页
  • 作者单位

    Univ Naples Federico II, Informat Technol & Elect Engn Dept DIETI, Via Claudio 21, I-80125 Naples, Italy;

    Univ Naples Federico II, Informat Technol & Elect Engn Dept DIETI, Via Claudio 21, I-80125 Naples, Italy;

    Univ Naples Federico II, Informat Technol & Elect Engn Dept DIETI, Via Claudio 21, I-80125 Naples, Italy;

    Univ Campania Luigi Vanvitelli, Polit Sci Dept Jean Monnet, Caserta, Italy;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Semantic; Logging; Event; NLP;

    机译:语义;记录;事件;NLP;

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