This book presents the data privacy protection which has been extensively applied in our current era of big data. However research into big data privacy is still in its infancy.ampampnbsp Given the fact that existing protection methods can result in low data utility and unbalanced tradeoffs personalized privacy protection has become a rapidly expanding research topic.In this book the authors explore emerging threats and existing privacy protection methods and discuss in detail both the advantages and disadvantages of personalized privacy protection.ampampnbsp Traditional methods such as differential privacy and cryptography are discussed using a comparative and intersectional approach and are contrasted with emerging methods like federated learning and generative adversarial nets.The advances discussed cover various applications e.g. cyberphysical systems social networks and locationbased services.