Data-Driven Security: Analysis, Visualization and Dashboards

Book description

Uncover hidden patterns of data and respond with countermeasures

Security professionals need all the tools at their disposal to increase their visibility in order to prevent security breaches and attacks. This careful guide explores two of the most powerful data analysis and visualization. You'll soon understand how to harness and wield data, from collection and storage to management and analysis as well as visualization and presentation. Using a hands-on approach with real-world examples, this book shows you how to gather feedback, measure the effectiveness of your security methods, and make better decisions.

Everything in this book will have practical application for information security professionals.

  • Helps IT and security professionals understand and use data, so they can thwart attacks and understand and visualize vulnerabilities in their networks

  • Includes more than a dozen real-world examples and hands-on exercises that demonstrate how to analyze security data and intelligence and translate that information into visualizations that make plain how to prevent attacks

  • Covers topics such as how to acquire and prepare security data, use simple statistical methods to detect malware, predict rogue behavior, correlate security events, and more

  • Written by a team of well-known experts in the field of security and data analysis

  • Lock down your networks, prevent hacks, and thwart malware by improving visibility into the environment, all through the power of data and Security Using Data Analysis, Visualization, and Dashboards.

    Table of contents

    1. Cover
    2. Introduction
    3. Chapter 1: The Journey to Data-Driven Security
      1. A Brief History of Learning from Data
      2. Gathering Data Analysis Skills
      3. Centering on a Question
      4. Summary
      5. Recommended Reading
    4. Chapter 2: Building Your Analytics Toolbox: A Primer on Using R and Python for Security Analysis
      1. Why Python? Why R? And Why Both?
      2. Jumpstarting Your Python Analytics with Canopy
      3. Introducing Data Frames
      4. Organizing Analyses
      5. Summary
      6. Recommended Reading
    5. Chapter 3: Learning the Hello World of Security Data Analysis
      1. Solving a Problem
      2. Getting Data
      3. Reading In Data
      4. Exploring Data
      5. Homing In on a Question
      6. Summary
      7. Recommended Reading
    6. Chapter 4: Performing Exploratory Security Data Analysis
      1. Dissecting the IP Address
      2. Augmenting IP Address Data
      3. Mapping Outside the Continents
      4. Summary
      5. Recommended Reading
    7. Chapter 5: From Maps to Regression
      1. Simplifying Maps
      2. Introducing Linear Regression
      3. Summary
      4. Recommended Reading
    8. Chapter 6: Visualizing Security Data
      1. Why Visualize?
      2. Understanding the Components of Visual Communications
      3. Turning Your Data into a Movie Star
      4. Summary
      5. Recommended Reading
    9. Chapter 7: Learning from Security Breaches
      1. Setting Up the Research
      2. Considerations in a Data Collection Framework
      3. An Introduction to VERIS
      4. Seeing VERIS in Action
      5. Working with VCDB Data
      6. Summary
      7. Recommended Reading
    10. Chapter 8: Breaking Up With Your Relational Database
      1. Realizing the Container Has Constraints
      2. Exploring Alternative Data Stores
      3. Summary
      4. Recommended Reading
    11. Chapter 9: Demystifying Machine Learning
      1. Detecting Malware
      2. Benefiting from Machine Learning
      3. Specific Learning Methods
      4. Hands On: Clustering Breach Data
      5. Summary
      6. Recommended Reading
    12. Chapter 10: Designing Effective Security Dashboards
      1. What Is a Dashboard, Anyway?
      2. Communicating and Managing “Security” through Dashboards
      3. Summary
      4. Recommended Reading
    13. Chapter 11: Building Interactive Security Visualizations
      1. Moving from Static to Interactive
      2. Developing Interactive Visualizations
      3. Summary
      4. Recommended Reading
    14. Chapter 12: Moving Toward Data-Driven Security
      1. Moving Yourself toward Data-Driven Security
      2. Moving Your Organization toward Data-Driven Security
      3. Summary
      4. Recommended Reading
    15. Appendix A: Resources and Tools
    16. Appendix B: References
      1. Chapter 1
      2. Chapter 2
      3. Chapter 3
      4. Chapter 4
      5. Chapter 5
      6. Chapter 6
      7. Chapter 7
      8. Chapter 8
      9. Chapter 9
      10. Chapter 10
      11. Chapter 11
      12. Chapter 12
      13. R Packages Used

    Product information

    • Title: Data-Driven Security: Analysis, Visualization and Dashboards
    • Author(s): Jay Jacobs, Bob Rudis
    • Release date: February 2014
    • Publisher(s): Wiley
    • ISBN: 9781118793725