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Machine Learning and Security by David Freeman, Clarence Chio

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Chapter 5. Network Traffic Analysis

The most likely way that attackers will gain entry to your infrastructure is through the network. Network security is the broad practice of protecting computer networks and network-accessible endpoints from malice, misuse, and denial.1 Firewalls are perhaps the best-known network defense systems, enforcing access policies and filtering unauthorized traffic between artifacts in the network. However, network defense is about more than just firewalls.

In this chapter, we look at techniques for classifying network traffic. We begin by building a model of network defense upon which we will base our discussions. Then, we dive into selected verticals within network security that have benefited from developments in artificial intelligence and machine learning. In the second part of this chapter, we work through an example of using machine learning to find patterns and discover correlations in network data. Using data science as an investigation tool, we discover how to apply classification on complex datasets to uncover attackers within the network.

Our discussion of network security is limited to packet-based information transmission. In packet-based transmission, a data stream is segmented into smaller units, each of which contains some metadata about the transmission origin, destination, and content. Each packet is transmitted over the network layer and formatted in an appropriate protocol by the transport layer, with the reconstruction of the information ...

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