Book Image

Building a Next-Gen SOC with IBM QRadar

By : Ashish M Kothekar
Book Image

Building a Next-Gen SOC with IBM QRadar

By: Ashish M Kothekar

Overview of this book

This comprehensive guide to QRadar will help you build an efficient security operations center (SOC) for threat hunting and need-to-know software updates, as well as understand compliance and reporting and how IBM QRadar stores network data in real time. The book begins with a quick introduction to QRadar components and architecture, teaching you the different ways of deploying QRadar. You’ll grasp the importance of being aware of the major and minor upgrades in software and learn how to scale, upgrade, and maintain QRadar. Once you gain a detailed understanding of QRadar and how its environment is built, the chapters will take you through the features and how they can be tailored to meet specifi c business requirements. You’ll also explore events, flows, and searches with the help of examples. As you advance, you’ll familiarize yourself with predefined QRadar applications and extensions that successfully mine data and find out how to integrate AI in threat management with confidence. Toward the end of this book, you’ll create different types of apps in QRadar, troubleshoot and maintain them, and recognize the current security challenges and address them through QRadar XDR. By the end of this book, you’ll be able to apply IBM QRadar SOC’s prescriptive practices and leverage its capabilities to build a very efficient SOC in your enterprise.
Table of Contents (18 chapters)
Part 1: Understanding Different QRadar Components and Architecture
Part 2: QRadar Features and Deployment
Part 3: Understanding QRadar Apps, Extensions, and Their Deployment

What is historical rule correlation?

When you create a rule in QRadar, you would like to test the rule against sample data to understand the number of offenses created, the frequency of the offensees, and the performance impact on the system. The best way to test this is to create a rule and then run a historical correlation to test the rule. The historical correlation rule is run on past data. We can select the range of time for which data was collected to run the rule. For example, a newly created rule can be run on 6-month-old data. Usually, you should run the historical correlation during non-business hours so that the impact, if any, is minimal. Based on the results, you can further tune the rule.

Consider another scenario in which QRadar was down for some time because of, say, a system upgrade activity or any other reason. In such a scenario, we can run a historical correlation and generate the offenses that were lost if there are any.

Historical correlation is also used...