Algorithms for Data and Computation Privacy

This book introduces the state-of-the-art algorithms for data and computation privacy. It mainly focuses on searchable symmetric encryption algorithms and privacy preserving multi-party computation algorithms. This book also introduces algorithms for breaking privacy, and gives intuition on how to design algorithm to counter privacy attacks. Some well-designed differential privacy algorithms are also included in this book.

Driven by lower cost, higher reliability, better performance, and faster deployment, data and computing services are increasingly outsourced to clouds. In this computing paradigm, one often has to store privacy sensitive data at parties, that cannot fully trust and perform privacy sensitive computation with parties that again cannot fully trust. For both scenarios, preserving data privacy and computation privacy is extremely important. After the Facebook–Cambridge Analytical data scandal and the implementation of the General Data Protection Regulation by European Union, users are becoming more privacy aware and more concerned with their privacy in this digital world.

This book targets database engineers, cloud computing engineers and researchers working in this field. Advanced-level students studying computer science and electrical engineering will also find this book useful as a reference or secondary text.

Rui Li received his Ph.D. Degree in Computer Science from Hunan University in 2012. He is currently an Associate Professor of Dongguan University of Technology. He received the Outstanding Young Teacher Award of Hunan Province in 2009 and the Distinguished Young Teacher Award by Luanxiong Liu Funding in 2010. He received a core young teacher award of Hunan Province in 2015. His research interests are in cloud computing, sensor networks and security.