Data Mining and Machine Learning in Cybersecurity (Hardcover)

Sumeet Dua, Xian Du

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商品描述

With the rapid advancement of information discovery techniques, machine learning and data mining continue to play a significant role in cybersecurity. Although several conferences, workshops, and journals focus on the fragmented research topics in this area, there has been no single interdisciplinary resource on past and current works and possible paths for future research in this area. This book fills this need.

From basic concepts in machine learning and data mining to advanced problems in the machine learning domain, Data Mining and Machine Learning in Cybersecurity provides a unified reference for specific machine learning solutions to cybersecurity problems. It supplies a foundation in cybersecurity fundamentals and surveys contemporary challenges—detailing cutting-edge machine learning and data mining techniques. It also:

  • Unveils cutting-edge techniques for detecting new attacks
  • Contains in-depth discussions of machine learning solutions to detection problems
  • Categorizes methods for detecting, scanning, and profiling intrusions and anomalies
  • Surveys contemporary cybersecurity problems and unveils state-of-the-art machine learning and data mining solutions
  • Details privacy-preserving data mining methods

This interdisciplinary resource includes technique review tables that allow for speedy access to common cybersecurity problems and associated data mining methods. Numerous illustrative figures help readers visualize the workflow of complex techniques and more than forty case studies provide a clear understanding of the design and application of data mining and machine learning techniques in cybersecurity.

商品描述(中文翻譯)

隨著資訊發現技術的快速發展,機器學習和數據挖掘在網絡安全中扮演著重要角色。儘管有幾個會議、研討會和期刊專注於這個領域的碎片化研究主題,但迄今為止還沒有一個跨學科的資源來整合過去和現在的研究成果,並提供未來研究的可能方向。這本書填補了這一需求。

從機器學習和數據挖掘的基本概念到機器學習領域的高級問題,《網絡安全中的數據挖掘和機器學習》提供了一個統一的參考資料,專門介紹了解決網絡安全問題的機器學習解決方案。它提供了網絡安全基礎知識的基礎,並調查了當代的挑戰,詳細介紹了尖端的機器學習和數據挖掘技術。它還包括:

- 揭示了檢測新攻擊的尖端技術
- 深入討論了機器學習解決檢測問題的方法
- 將檢測、掃描和分析入侵和異常的方法進行分類
- 調查了當代網絡安全問題,並揭示了最先進的機器學習和數據挖掘解決方案
- 詳細介紹了保護隱私的數據挖掘方法

這本跨學科的資源包括技術評論表,可快速查閱常見的網絡安全問題和相關的數據挖掘方法。大量的圖示幫助讀者視覺化複雜技術的工作流程,超過四十個案例研究清楚地說明了數據挖掘和機器學習技術在網絡安全中的設計和應用。