Data Privacy: Foundations, New Developments and the Big Data Challenge

This book covers everything you want to know about data privacy. Data privacy is a branch of data security that deals with the proper handling of data, ensuring that data is not misused or lost in the process of protecting it. The knowledge of data privacy is very important in today’s world as with the increasing no of firms and ever-increasing data in those companies; the need to protect data is just increasing day by day. And to do the same, the proper knowledge of the topic is a necessity.

In this book, we will learn about many different topics. Starting with the introduction, we will learn about machine learning and statistical learning in the second chapter. Then we will learn about data protection implications and compliance tools. After that, we will study about classification approach for Big Data security. Then we will see about users’ privacy and innovation with time and then learn about big data privacy, which is a very important chapter. After this, we will see privacy models and disclosure risk measures, learn about data masking methods, and measure the performance of big data analytics. At last, we will learn about how to understand and select data masking. Then to conclude, we will see a case study on data forensics as well.