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.

Contents:

1.    Introduction

2.    What is Data Analytics?

3.    Security: Basics and Security Analytics

4.    Statistics

5.    Data Mining – Unsupervised Learning

6.    Machine Learning – Supervised Learning

7.    Text Mining

8.    Natural Language Processing

9.    Big Data Techniques and Security A. Linear Algebra Basics B. Graphs C. Probability

About the Authors:

Rakesh Verma is a professor of computer science at the University of Houston where he is leading a research group that applies reasoning and data science to cybersecurity challenges. He teaches a course on security analytics that includes some of the material here. Since 2015, he has been co-organizing and editing the proceedings of the ACM International Workshop on Security and Privacy Analytics. He is an editor of Frontiers of Big Data in the Cybersecurity Area, an ACM Distinguished Speaker (2011-2018), and the winner of two Best Paper Awards. He received the Lifetime Mentoring Award from the University of Houston and he is a Fulbright Senior Specialist in Computer Science.