2 Differential privacy for machine learning

This chapter covers

  • What differential privacy is
  • Using differential privacy mechanisms in algorithms and applications
  • Implementing properties of differential privacy

In the previous chapter, we investigated various privacy-related threats and vulnerabilities in machine learning (ML) and concepts behind privacy-enhancing technologies. From now on, we will focus on the details of essential and popular privacy-enhancing technologies. The one we will discuss in this chapter and the next is differential privacy (DP).

Differential privacy is one of the most popular and influential privacy protection schemes used in applications today. It is based on the concept of making a dataset robust enough that any ...

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