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Microsoft Sentinel in Action

Microsoft Sentinel in Action

By : Richard Diver, Gary Bushey
4.7 (3)
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Microsoft Sentinel in Action

Microsoft Sentinel in Action

4.7 (3)
By: Richard Diver, Gary Bushey

Overview of this book

Microsoft Sentinel is a security information and event management (SIEM) tool developed by Microsoft that helps you integrate cloud security and artificial intelligence (AI). This book will teach you how to implement Microsoft Sentinel and understand how it can help detect security incidents in your environment with integrated AI, threat analysis, and built-in and community-driven logic. The first part of this book will introduce you to Microsoft Sentinel and Log Analytics, then move on to understanding data collection and management, as well as how to create effective Microsoft Sentinel queries to detect anomalous behaviors and activity patterns. The next part will focus on useful features, such as entity behavior analytics and Microsoft Sentinel playbooks, along with exploring the new bi-directional connector for ServiceNow. In the next part, you’ll be learning how to develop solutions that automate responses needed to handle security incidents and find out more about the latest developments in security, techniques to enhance your cloud security architecture, and explore how you can contribute to the security community. By the end of this book, you’ll have learned how to implement Microsoft Sentinel to fit your needs and protect your environment from cyber threats and other security issues.
Table of Contents (23 chapters)
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1
Section 1: Design and Implementation
4
Section 2: Data Connectors, Management, and Queries
9
Section 3: Security Threat Hunting
15
Section 4: Integration and Automation
18
Section 5: Operational Guidance

Introduction to Azure Monitor Log Analytics

Azure Monitor is the name of a suite of solutions built within the Azure platform to collect logs and metrics, with that information then being used to create insights, visualizations, and automated responses. Log Analytics is one of the main services created to analyze the logs gathered. The platform supports near real-time scenarios, is automatically scaled, and is available to multiple services across Azure (including Microsoft Sentinel). The Kusto Query Language (KQL) is used to obtain information from logs, allows complex information to be queried quickly, and the queries can be saved for future use. In this book, we will refer to this service simply as Log Analytics.

To create a Log Analytics workspace, you must first have an Azure subscription. Each subscription is based on a specific geographic location that ties the data storage to that region. The region selection is decided based on where you want your data to be stored; consider...

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