Course Code: aicybersecurityadv
Duration: 28 hours
Prerequisites:
  • 對網路安全框架和威脅檢測有深入的理解
  • 在安全領域使用機器學習和 AI 應用程式的經驗
  • 熟悉安全環境中的腳本編寫和自動化

觀眾

  • 中高級網路安全專業人員
  • 安全運營中心 (SOC) 分析師
  • 威脅獵人和事件回應團隊
Overview:

高級 AI 驅動的網路安全側重於使用複雜的 AI 技術來檢測、分析和回應複雜的網路威脅。本課程深入探討高級演算法、即時威脅檢測以及 AI 模型的定製以增強安全操作。

這種由講師指導的現場培訓(在線或現場)面向希望提升 AI 驅動型威脅檢測和事件回應技能的中高級網路安全專業人員。

在本次培訓結束時,參與者將能夠:

  • 實施高級 AI 演算法以進行即時威脅檢測。
  • 針對特定的網路安全挑戰定製 AI 模型。
  • 開發用於威脅回應的自動化工作流程。
  • 保護 AI 驅動的安全工具,抵禦對抗性攻擊。

課程形式

  • 互動講座和討論。
  • 大量的練習和練習。
  • 在即時實驗室環境中動手實施。

課程自定義選項

  • 要申請本課程的定製培訓,請聯繫我們進行安排。
Course Outline:

AI 增強型威脅檢測技術

  • 高級監督式和無監督式機器學習模型
  • 使用 AI 進行即時異常檢測
  • 實施 AI 驅動的威脅搜尋技術

構建自定義的網路安全 AI 模型

  • 開發針對特定安全需求量身定製的模型
  • 網路安全數據的特徵工程
  • 使用網路安全數據集訓練和驗證模型

使用 AI 實現事件回應自動化

  • 基於 AI 的自動回應手冊
  • 將 AI 與 SOAR 平臺整合以增強自動化
  • 通過 AI 驅動的決策縮短響應時間

用於網路威脅分析的 Advanced Deep Learning

  • 用於檢測複雜惡意軟體的神經網路
  • 使用深度學習進行高級持續性威脅 (APT) 檢測
  • 威脅分析中深度學習的案例研究

網路安全中的對抗性 Machine Learning

  • 瞭解和防禦對 AI 模型的對抗性攻擊
  • 為 AI 安全模型實施穩健性技術
  • 在動態威脅環境中保護 AI 演算法

將 AI 與現有網路安全基礎設施整合

  • 將 AI 模型與 SIEM 和威脅情報平臺連接起來
  • 優化網路安全工作流程中的 AI 性能
  • Scalable 部署 AI 驅動的安全措施

使用 AI 和 Big Data 的威脅情報

  • 利用 AI 分析大規模威脅數據
  • 實時威脅情報收集和分析
  • 使用 AI 預測和預防未來的網路威脅

總結和後續步驟

Sites Published:

United Arab Emirates - AI-Powered Cybersecurity: Advanced Threat Detection & Response

Qatar - AI-Powered Cybersecurity: Advanced Threat Detection & Response

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