Book Image

Practical Threat Detection Engineering

By : Megan Roddie, Jason Deyalsingh, Gary J. Katz
5 (2)
Book Image

Practical Threat Detection Engineering

5 (2)
By: Megan Roddie, Jason Deyalsingh, Gary J. Katz

Overview of this book

Threat validation is an indispensable component of every security detection program, ensuring a healthy detection pipeline. This comprehensive detection engineering guide will serve as an introduction for those who are new to detection validation, providing valuable guidelines to swiftly bring you up to speed. The book will show you how to apply the supplied frameworks to assess, test, and validate your detection program. It covers the entire life cycle of a detection, from creation to validation, with the help of real-world examples. Featuring hands-on tutorials and projects, this guide will enable you to confidently validate the detections in your security program. This book serves as your guide to building a career in detection engineering, highlighting the essential skills and knowledge vital for detection engineers in today's landscape. By the end of this book, you’ll have developed the skills necessary to test your security detection program and strengthen your organization’s security measures.
Table of Contents (20 chapters)
1
Part 1: Introduction to Detection Engineering
5
Part 2: Detection Creation
11
Part 3: Detection Validation
14
Part 4: Metrics and Management
16
Part 5: Detection Engineering as a Career

Looking at data source issues and challenges

Unfortunately, a lot of variabilities are involved in what data sources will be available and the quality of those data sources. We’ll touch on several of the causes of such variability and the challenges they present in the following subsections.

Completeness

The completeness of the data provided by a data source is based on the value of the attributes captured for any given event. We do not want to waste storage resources and bandwidth on data sources that won’t add value to our investigation due to the data they expose. For example, if a system provides logs showing a network connection was established but there are no details on the source/destination of the connection with contextless timestamps and ambiguous time zones, there is likely not much that can be used from that to develop a quality detection. As such, we either ignore or de-prioritize this data source.

As an additional note regarding completeness, some...