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Data Mining and Machine Learning in Cybersecurity

Data Mining and Machine Learning in Cybersecurity

Interesting Research Book in Data Mining and Machine Learning in Cybersecurity

Author(s) Name:  Sumeet Dua, Xian Du

About the Book:

   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.
   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.

Table of Contents

  • Introduction
  • Classical Machine-Learning Paradigms for Data Mining
  • Supervised Learning for Misuse/Signature Detection
  • Machine Learning for Anomaly Detection
  • Machine Learning for Hybrid Detection
  • Machine Learning for Scan Detection
  • Machine Learning for Profiling Network Traffic
  • Privacy-Preserving Data Mining
  • Emerging Challenges in Cybersecurity
  • ISBN:  9781439839423

    Publisher:  Auerbach Publications

    Year of Publication:  2011

    Book Link:  Home Page Url