- Identify the goals of network security.
- Distinguish types of firewalls.
- Explain intrusion detection and prevention systems.
- Describe packet capture.
- Collect packet sniffer, IDS, and IPS data.
- Explain how to use machine learning to process network data.
- Use data science to conduct a network forensics investigation.
- Identify data visualization targets and tools.
Skill Level Intermediate
- Hi, I'm Jungwoo Ryoo, and welcome to Data-driven Network Security Essentials. In this course I'll teach you the critical role of data and how to leverage it to improve network security. I'll start by reviewing the basic network security concepts such as firewalls, virtual private networks, intrusion detection and prevention systems, vulnerability management systems, and security information and event management systems, also known as SIEM.
Then I'll show you different type of network security data sources, and how to collect data from them. We'll check the current development in data science, especially in the area of data analytics. I'll also provide an overview of how services like Microsoft Azure can help solve classic network security problems such as detecting anomalies.
In addition, I'll be covering network forensics and how the field can benefit from data science. Now, let's get started with data-driven network security essentials.
1. Network Security Review
2. Network Data Sources
3. Data Collection
4. Data Analytics
Network forensics2m 25s
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