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)
1
Part 1: Understanding Different QRadar Components and Architecture
5
Part 2: QRadar Features and Deployment
10
Part 3: Understanding QRadar Apps, Extensions, and Their Deployment

QRadar search tuning

Earlier, we looked at the different types of searches. QRadar searches are one of the most computationally expensive functions. If done right by following a few rules, the searches will work smoothly and efficiently. Otherwise, you will end up with performance issues on various fronts. All the searches are initiated from the QRadar Console and hence, if searches are done wrong, it might affect the other functionalities or services on the Console.

Here are a few rules when it comes to QRadar searches. Let’s dive in!

Indexing and index management

An index is metadata that is generated for the data in the Ariel database. This index data can be generated as soon as the events or flows are ingested in QRadar, or the index can also be generated before running searches (i.e., post-data ingestion). Indexing is used to make the QRadar searches fast and efficient.

Indexing is enabled on the property of the events/flows. For example, source IP would be...