Summary
This introductory chapter provided a brief overview of cybersecurity and ML. We studied the fundamental goals of traditional cybersecurity and how those goals have now evolved to capture other tasks such as fake news, deep fakes, click spam, and fraud. User privacy, a topic of growing importance in the world, was also introduced. On the ML side, we covered the basics from the ground up: beginning with how ML differs from traditional computing and moving on to the methods, approaches, and common terms used in ML. Finally, we also highlighted the key differences in ML for cybersecurity that make it so much more challenging than other fields. The coming chapters will focus on applying these concepts to designing and implementing ML models for security issues. In the next chapter, we will discuss how to detect anomalies and network attacks using ML.