"secure Multi Party Computation"

Privacy-Preserving Collaborative Computation

by Stefan Katzenbeisser (Author),‎ Niklas Büscher (Author)

This book presents a holistic view on compiler assisted practical secure multi-party computation (MPC) over Boolean circuits. It discusses that two or more parties jointly evaluate a function over their inputs in such a way that each party

We generate and gather a lot of data about ourselves and others, some of it highly confidential. The collection, storage and use of this data is strictly regulated by laws, but restricting the use of data often limits the benefits which could be obtained from its analysis. Secure multi-party computation (SMC), a cryptographic technology, makes it possible to execute specific programs on confidential data while ensuring that no other sensitive information from the data is leaked.

Unlocking Data Value, Respecting Privacy.

This book consists of refereed selected papers from the International Conference on Security & Privacy – ICSP 2020. The book is focused on the state-of-the-art developments of network security, secure cryptographic protocols, post-quantum cryptography, quantum cryptography, block-chain and cryptocurrency, IoT security and privacy, cloud security, machine learning in cybersecurity, and other disciplines related to security and privacy.

This book constitutes the proceedings of the first International Symposium on Cyber Security Cryptography and Machine Learning, held in Beer-Sheva, Israel, in June 2017.