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.
