Elastic Machine Learning for Cybersecurity
Network security analysts have the daunting daily task of identifying potential threats in an endless ocean of network security data. In this class, you’ll see how Elastic machine learning can help you quickly and efficiently detect those threats, regardless of how much data you need to analyze. Elastic machine learning features can automatically model the behavior of your network security data trends, periodicity, and more, all in real time to identify issues faster, streamline root cause analysis, and reduce false positives. After completing this course, you’ll be able to use the powerful features of Elastic machine learning for identifying anomalies in your security data.
- Using Elastic Machine Learning for Security
- Exploring the Security Threat Landscape
- Detecting Security Anomalies
- DNS Data Exfiltration
This course is a module of the Security Analytics specialization. Find out how our focused Training Specializations can help you with your use case.
Network Security Analysts, Security Practitioners, Information Security Consultants, System Administrators
Virtual Classroom - 1 Day | 2-3 hours
- We recommend you have taken Kibana Data Analysis and Elasticsearch Engineer I or possess equivalent knowledge.
- General familiarity around security log data
- Basic networking knowledge
- Stable internet connection
- Mac, Linux, or Windows
- Latest version of Chrome or Firefox (Safari is not 100% supported)
Upcoming Classes — Elastic Machine Learning for Cybersecurity
It was awesome. Both instructors are great speakers. They have a wide and deep knowledge about the topic, and they know how to pass it on. They are infecting with their enthusiasm.