Book Image

Practical Threat Intelligence and Data-Driven Threat Hunting

By : Valentina Costa-Gazcón
Book Image

Practical Threat Intelligence and Data-Driven Threat Hunting

By: Valentina Costa-Gazcón

Overview of this book

Threat hunting (TH) provides cybersecurity analysts and enterprises with the opportunity to proactively defend themselves by getting ahead of threats before they can cause major damage to their business. This book is not only an introduction for those who don’t know much about the cyber threat intelligence (CTI) and TH world, but also a guide for those with more advanced knowledge of other cybersecurity fields who are looking to implement a TH program from scratch. You will start by exploring what threat intelligence is and how it can be used to detect and prevent cyber threats. As you progress, you’ll learn how to collect data, along with understanding it by developing data models. The book will also show you how to set up an environment for TH using open source tools. Later, you will focus on how to plan a hunt with practical examples, before going on to explore the MITRE ATT&CK framework. By the end of this book, you’ll have the skills you need to be able to carry out effective hunts in your own environment.
Table of Contents (21 chapters)
Section 1: Cyber Threat Intelligence
Section 2: Understanding the Adversary
Section 3: Working with a Research Environment
Section 4: Communicating to Succeed
Appendix – The State of the Hunt

Distinguishing good-quality data from bad-quality data

So far in this book, we have repeated over and over the importance of having good visibility of our assets. A lack of good visibility can lead to a false sense of security. But what happens if we have the visibility but the quality of the data we are gathering isn't good? Bad-quality data can have significant consequences: it can cause operational problems, lead to poor business strategies, cause inaccurate analytics, or even generate huge economic losses. Bad-quality data is a problem that goes far beyond the threat hunting realm, but that doesn't mean that the threat hunter shouldn't be wary of it.

Generally, data quality is measured on a range, and what is considered acceptable quality data will depend on the process relying on it. In a way, data would be of good quality if it's helping you meet your requirements. A good data management program should help your organization combine the technology and data...