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Machine Learning with the Elastic Stack

You're reading from   Machine Learning with the Elastic Stack Expert techniques to integrate machine learning with distributed search and analytics

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Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781788477543
Length 304 pages
Edition 1st Edition
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Authors (2):
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Bahaaldine Azarmi Bahaaldine Azarmi
Author Profile Icon Bahaaldine Azarmi
Bahaaldine Azarmi
Rich Collier Rich Collier
Author Profile Icon Rich Collier
Rich Collier
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Toc

Table of Contents (12) Chapters Close

Preface Machine Learning for IT FREE CHAPTER Installing the Elastic Stack with Machine Learning Event Change Detection IT Operational Analytics and Root Cause Analysis Security Analytics with Elastic Machine Learning Alerting on ML Analysis Using Elastic ML Data in Kibana Dashboards Using Elastic ML with Kibana Canvas Forecasting ML Tips and Tricks Other Books You May Enjoy

Threat hunting architecture

In this section, we'll go through the basic building blocks of a threat hunting architecture structure. These include a multiple ingestion layer starting with Beats to collect the data from different sources and Logstash to enrich the data for threat intelligence. Once the data has been properly prepared, the next step will be to focus on the investigation analytics.

Layer-based ingestion

A threat hunting architecture relies on rich and reliable data ingestion that will allow you to detect and investigate anomalous behaviors. In our scenario, we need to use both data coming from end user workstations and data coming from the network. Luckily, we have Packetbeat and Winlogbeat, which capture...

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