Theory of cryptography

Secure multi-party computation

Secure multi-party computation (also known as secure computation, multi-party computation (MPC) or privacy-preserving computation) is a subfield of cryptography with the goal of creating methods for parties to jointly compute a function over their inputs while keeping those inputs private. Unlike traditional cryptographic tasks, where cryptography assures security and integrity of communication or storage and the adversary is outside the system of participants (an eavesdropper on the sender and receiver), the cryptography in this model protects participants' privacy from each other. The foundation for secure multi-party computation started in the late 1970s with the work on mental poker, cryptographic work that simulates game playing/computational tasks over distances without requiring a trusted third party. Note that traditionally, cryptography was about concealing content, while this new type of computation and protocol is about concealing partial information about data while computing with the data from many sources, and correctly producing outputs. By the late 1980s, Michael Ben-Or, Shafi Goldwasser and Avi Wigderson, and independently David Chaum, Claude Crรฉpeau, and Ivan Damgรฅrd, had published papers showing "how to securely compute any function in the secure channels setting". (Wikipedia).

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Related pages

Private information retrieval | Privacy-preserving computational geometry | Universal composability | Secret sharing | Oblivious transfer | Garbled circuit | Proactive secret sharing | Secure two-party computation | Mental poker | Shamir's Secret Sharing | Edit distance | Homomorphic encryption | Adversary (cryptography) | Bitcoin | Verifiable secret sharing | Cryptography | Private set intersection