Big Data Analytics in Cybersecurity

Onur Savas, Julia Deng

September 20, 2017 by Auerbach Publications
Reference - 336 Pages - 74 Color Illustrations
ISBN 9781498772129 - CAT# K29486
Series: Data Analytics Applications

USD$99.95

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Features

  • Uses big data to analyze and detect threats, as well as identify vulnerablities
  • Presents practical analytical tools to monitor and manage network security
  • Covers analytics applications for securing cloud and internet of things environments
  • Written by experts in academia, industry, and government
  • Includes case study that shows practical applications of big data analytics

Summary

Big data is presenting challenges to cybersecurity. For an example, the Internet of Things (IoT) will reportedly soon generate a staggering 400 zettabytes (ZB) of data a year. Self-driving cars are predicted to churn out 4000 GB of data per hour of driving. Big data analytics, as an emerging analytical technology, offers the capability to collect, store, process, and visualize these vast amounts of data. Big Data Analytics in Cybersecurity examines security challenges surrounding big data and provides actionable insights that can be used to improve the current practices of network operators and administrators.

Applying big data analytics in cybersecurity is critical. By exploiting data from the networks and computers, analysts can discover useful network information from data. Decision makers can make more informative decisions by using this analysis, including what actions need to be performed, and improvement recommendations to policies, guidelines, procedures, tools, and other aspects of the network processes.

Bringing together experts from academia, government laboratories, and industry, the book provides insight to both new and more experienced security professionals, as well as data analytics professionals who have varying levels of cybersecurity expertise. It covers a wide range of topics in cybersecurity, which include:

  • Network forensics
  • Threat analysis
  • Vulnerability assessment
  • Visualization
  • Cyber training.

In addition, emerging security domains such as the IoT, cloud computing, fog computing, mobile computing, and cyber-social networks are examined.

The book first focuses on how big data analytics can be used in different aspects of cybersecurity including network forensics, root-cause analysis, and security training. Next it discusses big data challenges and solutions in such emerging cybersecurity domains as fog computing, IoT, and mobile app security. The book concludes by presenting the tools and datasets for future cybersecurity research.