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Analyst Burnout in the Cyber Security Operation Center - CSOC: A Phenomenological Study

机译:网络安全运营中心的分析员倦怠-现象学研究

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摘要

If you are connected to the Internet, your device is susceptible to unwanted intrusions which lead to compromises where 89% of attacks are financially or espionage focused according to Verizon's 2016 Data Breach Investigations Report (Verizon, 2016). Cyber security that is a relatively new phenomenon has a variety of different suppliers, methods, and contexts with the mission to prevent intrusions and attacks from those that have malicious intentions. The people who work to identify these intrusions are the core of any cyber defense strategy and operation. Until the time that Artificial Intelligence -- AI will become the reasoning, logic, and action behind cyber intrusion detections it is necessary that Cyber Security Operation Centers (CSOC) be given the best analysts, management, tools, training, and working environment to enable these operations. The current state of cyber security from a resourcing perspective is that there is a critical shortage of cyber security skilled workers projected into 2020 (Vogel, 2016). It is within the CSOC environment that cyber security workers: analysts can and do become burned out from the daily activity of event analysis that affects analysis accuracy, one emotional and physical health, and the retention of cyber security professionals. The literature examined has revealed the problem to investigate further through a phenomenological interpretive analysis of the experiences of CSOC analysts as they experience burnout.
机译:根据Verizon的《 2016年数据泄露调查报告》(Verizon,2016年),如果您连接到Internet,则设备容易受到有害入侵,从而导致妥协,在这些攻击中,有89%的攻击是经济或间谍活动重点。作为一种相对较新的现象,网络安全具有多种不同的供应商,方法和环境,其任务是防止恶意企图的入侵和攻击。致力于识别这些入侵的人员是任何网络防御策略和运营的核心。在人工智能(AI)成为网络入侵检测背后的推理,逻辑和行动之前,有必要为网络安全运营中心(CSOC)提供最佳的分析师,管理,工具,培训和工作环境,以实现这些操作。从资源配置的角度来看,网络安全的当前状态是,预计到2020年,网络安全熟练工人将严重短缺(Vogel,2016年)。正是在CSOC环境中,网络安全工作者才能做到:分析师会并且确实会从事件分析的日常活动中精疲力尽,这些事件会影响分析的准确性,一种身心健康以及网络安全专业人员的保留。所研究的文献揭示了需要通过对CSOC分析人员经历的职业倦怠进行的现象学解释性分析来进一步研究的问题。

著录项

  • 作者

    Hull, James L.;

  • 作者单位

    Colorado Technical University.;

  • 授予单位 Colorado Technical University.;
  • 学科 Computer science.;Information science.
  • 学位 D.C.S.
  • 年度 2017
  • 页码 174 p.
  • 总页数 174
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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