Data-Driven Network Security Essentials

Description

In this course, you will :

• Explore the fundamental concepts, skills, and techniques for managing network security and forensics.
• explains how to use data to improve network security and forensics
• Begin by going over the fundamentals, such as firewalls, VPNs, and vulnerability management systems.
• explores various data sources and explains how data from various sources can be a powerful tool for improving network security.
• It also discusses network data collection techniques and tools, as well as machine learning and visualisation for processing network data and detecting anomalies.

Syllabus :

1. Network Security Review

• Network security
• Firewalls
• VPNs
• Intrusion detection and prevention systems
• Vulnerability management systems and security information and event management (SIEM)

 

2. Network Data Sources

• Use network data to improve security
• Packet Capture
• Firewall logs
• IDS and IPS data
• Vulnerability management system and SIEM data
• Application data
• Operating system (OS) data

 

3. Data Collection

• Use log servers to collect data
• Collect packet sniffer data
• Collect IDS and IPS data
• Collect vulnerability management system and SIEM data
• Collect application data
• Collect OS data

 

4. Data Analytics

• Machine learning to process network data
• Machine learning to detect a network anomaly
• Azure machine learning service
• Detect network anomalies using the Azure machine learning service

 

5. Forensics

• Network forensics
• Use data science to conduct a network forensics investigation

 

6. Visualization

• Network security visualization
• Visualization targets
• Visualization steps
• Use data visualization tools
• Learn by example

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