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Practical Threat Detection Engineering

You're reading from   Practical Threat Detection Engineering A hands-on guide to planning, developing, and validating detection capabilities

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Product type Paperback
Published in Jul 2023
Publisher Packt
ISBN-13 9781801076715
Length 328 pages
Edition 1st Edition
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Authors (3):
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Megan Roddie Megan Roddie
Author Profile Icon Megan Roddie
Megan Roddie
Jason Deyalsingh Jason Deyalsingh
Author Profile Icon Jason Deyalsingh
Jason Deyalsingh
Gary J. Katz Gary J. Katz
Author Profile Icon Gary J. Katz
Gary J. Katz
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Toc

Table of Contents (20) Chapters Close

Preface 1. Part 1: Introduction to Detection Engineering
2. Chapter 1: Fundamentals of Detection Engineering FREE CHAPTER 3. Chapter 2: The Detection Engineering Life Cycle 4. Chapter 3: Building a Detection Engineering Test Lab 5. Part 2: Detection Creation
6. Chapter 4: Detection Data Sources 7. Chapter 5: Investigating Detection Requirements 8. Chapter 6: Developing Detections Using Indicators of Compromise 9. Chapter 7: Developing Detections Using Behavioral Indicators 10. Chapter 8: Documentation and Detection Pipelines 11. Part 3: Detection Validation
12. Chapter 9: Detection Validation 13. Chapter 10: Leveraging Threat Intelligence 14. Part 4: Metrics and Management
15. Chapter 11: Performance Management 16. Part 5: Detection Engineering as a Career
17. Chapter 12: Career Guidance for Detection Engineers 18. Index 19. Other Books You May Enjoy

Calculating a detection’s efficacy

Mean time to detect, discussed earlier in this chapter, provides a historical view of the effectiveness against attacks performed against the organization. We will group additional efficacy metrics into three areas: low-fidelity coverage, automated validations, and high-fidelity coverage. When we refer to coverage, we are talking about a measure of how much of the potential attack space can be detected. The attack space is defined by what you are trying to measure. It could be a single technique or multiple MITRE ATT&CK matrixes. We’ll start by looking at some low-fidelity methods of determining coverage.

Low-fidelity coverage metrics

A common low-fidelity coverage visualization is mapping your detections to a MITRE ATT&CK matrix, as shown in Figure 11.7. Each technique is colored according to the number of detections that have been created for it. This visualization is easy to produce, and many tools will automatically...

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