Introduction

Overview

Teaching: 10 min
Exercises: 0 min

Questions

• What is machine learning?

• What are some applications of machine learning in cybersecurity?

Objectives

• Understand some potential applications of machine learning in cybersecurity

Machine Learning

Machine learning refers to algorithms that help computers learn to solve problems through experience. In its most common form, supervised learning, this involves providing the machine with labeled examples that are each a pair of data and desired output and tasking the machine with learning to produce the output when a new unlabeled example is provided. For instance, the data could be pictures of animals and the desired output could be the identification of what kind of animal the picture represents. Machine learning algorithms work around models that transform the input data (that has been suitably pre-processed to work with the model) into a predicted output value. The goal of machine learning is to derive the necessary parameters of these models such that the computed output value is as close as possible to the actual output value.

Machine Learning in Cybersecurity

Machine learning can be used to process large quantities of data and derive some useful insights. In cybersecurity, this most commonly involves the detection of anomalies in various kinds of system data. For instance, we can apply machine learning to detect network traffic data that resembles a DDoS style attack and flag the source IPs of this traffic for further inspection or monitoring.

In this set of lessons we will learn about various such applications of machine learning for cybersecurity.

Key Points

• Machine learning can be used to analyze and identify cybersecurity issues