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Cybersecurity Analytics

Cybersecurity Analytics

Interesting Research Book in Cybersecurity Analytics

Author(s) Name:  Rakesh M. Verma, David J. Marchette

About the Book:

   Cybersecurity Analytics is for the cybersecurity student and professional who wants to learn data science techniques critical for tackling cybersecurity challenges, and for the data science student and professional who wants to learn about cybersecurity adaptations. Trying to build a malware detector, a phishing email detector, or just interested in finding patterns in your datasets? This book can let you do it on your own. Numerous examples and datasets links are included so that the reader can "learn by doing." Anyone with a basic college-level calculus course and some probability knowledge can easily understand most of the material.
   The book includes chapters containing: unsupervised learning, semi-supervised learning, supervised learning, text mining, natural language processing, and more. It also includes background on security, statistics, and linear algebra. The website for the book contains a listing of datasets, updates, and other resources for serious practitioners.

Table of Contents

  • What is Data Analytics?
  • Security: Basics and Security Analytics
  • Statistics
  • Data Mining – Unsupervised Learning
  • Machine Learning – Supervised Learning
  • Text Mining
  • Natural Language Processing
  • Big Data Techniques and Security
  • Linear Algebra Basics
  • Graphs
  • Probability
  • Bibliography
  • ISBN:  9780367346010

    Publisher:  Taylor & Francis Group

    Year of Publication:  2020

    Book Link:  Home Page Url