Learn how to use machine learning to process network data. Jungwoo shows how recent developments in data science such as big data, clould computing, and machine learning are revolutionalizing the field of network security.
- The diversity and value of network security data sources are increasing exponentially, even as I speak. Unfortunately, Data Processing and Analysis Systems in their conventional forms are incapable of dealing with this remarkable growth. Fortunately, immersing technologies, such as Cloud computing and machine learning are coming to our rescue.
The network security data we're talking about here has already reached the realm of big data. Cloud computing offers a distributed environment that helps with storing and processing the large volume and diversity of network security data, which is up to par with other types of big data out there. Machine learning provides network security professionals with useful insight and predicted power to reputedly make an informed decision on what actions to take against impending attacks to their network.
Building on the Cloud computing infrastructure solved the solutions like Hadoop and Spark feature-distributed file systems and parallel processing capabilities. They empower network security specialists by supplying them with unprecedented storage capacity and processing speed. Machine learning, in particular, has a potential to revolutionize the network security industry due to its realtime detection and forecasting functions.
- Network security concepts
- The basic functions of a firewall
- Intrusion detection and prevention systems
- Using network data to improve security
- Using log servers to collect data
- Collecting application data
- Collecting OS data
- Network forensics
- Network security visualization