Differential Privacy Overview and Fundamental Techniques
It is an incremental overview chapter for a book, aimed at readers seeking foundational knowledge in privacy-preserving AI.
This chapter provides an introduction to differential privacy, defining its formal properties and reviewing basic implementation techniques, but presents no new research results or concrete numbers.
This chapter is meant to be part of the book "Differential Privacy in Artificial Intelligence: From Theory to Practice" and provides an introduction to Differential Privacy. It starts by illustrating various attempts to protect data privacy, emphasizing where and why they failed, and providing the key desiderata of a robust privacy definition. It then defines the key actors, tasks, and scopes that make up the domain of privacy-preserving data analysis. Following that, it formalizes the definition of Differential Privacy and its inherent properties, including composition, post-processing immunity, and group privacy. The chapter also reviews the basic techniques and mechanisms commonly used to implement Differential Privacy in its pure and approximate forms.