In a data-driven society, individuals and companies encounter numerous situations where private information is an important resource. How can parties handle confidential data if they do not trust everyone involved? This text is the first to present a comprehensive treatment of unconditionally secure techniques for multiparty computation (MPC) and secret sharing. In a secure MPC, each party possesses some private data, while secret sharing provides a way for one party to spread information on a secret such that all parties together hold full information, yet no single party has all the information. The authors present basic feasibility results from the last 30 years, generalizations to arbitrary access structures using linear secret sharing, some recent techniques for efficiency improvements, and a general treatment of the theory of secret sharing, focusing on asymptotic results with interesting applications related to MPC.

�ber die Autorinnen und Autoren

Ronald Cramer leads the Cryptology Group at CWI Amsterdam, the national research institute for mathematics and computer science in the Netherlands, and is Professor at the Mathematical Institute, Leiden University. He is Fellow of the International Association for Cryptologic Research (IACR) and Member of the Royal Netherlands Academy of Arts and Sciences (KNAW).

Ivan Bjerre Damg�rd leads the Cryptology Group at Department of Computer Science, Aarhus University, and is a professor at the same department. He is a fellow of the International Association for Cryptologic Research and has received the RSA conference 2015 award for outstanding achievements in mathematics. He is a co-founder of the companies Cryptomathic and Partisia.

Jesper Buus Nielsen is an associate professor in the Department of Computer Science, Aarhus University. He is a co-founder of the company Partisia.

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