Secure Multi-Party Computation (MPC)
What is Secure Multi-Party Computation (MPC)?
Secure Multi-Party Computation (MPC)A family of cryptographic protocols that lets several parties jointly compute a function over their private inputs while revealing nothing beyond the output.
Secure Multi-Party Computation (MPC) lets a set of mutually distrusting parties compute a joint function of their private inputs and learn only the output. Foundational constructions include Yao's garbled circuits for two-party computation and protocols based on secret sharing (BGW, GMW, SPDZ) for many parties; modern implementations achieve practical throughput using preprocessing, ABY3, and silent OT extensions. MPC underpins threshold signing of cryptocurrency wallets and HSMs, privacy-preserving analytics across organizations, cross-bank fraud detection, and federated key management. It is often combined with zero-knowledge proofs or homomorphic encryption to harden assumptions or reduce communication.
● Examples
- 01
Threshold ECDSA wallets that split a Bitcoin signing key across several MPC nodes.
- 02
Cross-organization analytics that compute fraud signals without sharing raw transaction logs.
● Frequently asked questions
What is Secure Multi-Party Computation (MPC)?
A family of cryptographic protocols that lets several parties jointly compute a function over their private inputs while revealing nothing beyond the output. It belongs to the Cryptography category of cybersecurity.
What does Secure Multi-Party Computation (MPC) mean?
A family of cryptographic protocols that lets several parties jointly compute a function over their private inputs while revealing nothing beyond the output.
How does Secure Multi-Party Computation (MPC) work?
Secure Multi-Party Computation (MPC) lets a set of mutually distrusting parties compute a joint function of their private inputs and learn only the output. Foundational constructions include Yao's garbled circuits for two-party computation and protocols based on secret sharing (BGW, GMW, SPDZ) for many parties; modern implementations achieve practical throughput using preprocessing, ABY3, and silent OT extensions. MPC underpins threshold signing of cryptocurrency wallets and HSMs, privacy-preserving analytics across organizations, cross-bank fraud detection, and federated key management. It is often combined with zero-knowledge proofs or homomorphic encryption to harden assumptions or reduce communication.
How do you defend against Secure Multi-Party Computation (MPC)?
Defences for Secure Multi-Party Computation (MPC) typically combine technical controls and operational practices, as detailed in the full definition above.
What are other names for Secure Multi-Party Computation (MPC)?
Common alternative names include: MPC, Multi-party computation.
● Related terms
- cryptography№ 1152
Threshold Cryptography
A class of cryptographic schemes in which a secret key is split across n parties so that any t of them — but no smaller subset — can sign, decrypt, or perform any other key operation.
- cryptography№ 481
Homomorphic Encryption
An encryption scheme that allows computations to be performed directly on ciphertexts, producing encrypted results that match the operations on the underlying plaintexts.
- cryptography№ 1265
Zero-Knowledge Proof (ZKP)
A cryptographic protocol in which a prover convinces a verifier that a statement is true without revealing anything beyond the validity of the statement itself.
- cryptography№ 859
Private Set Intersection (PSI)
A cryptographic protocol that lets two or more parties compute the intersection of their private sets while learning nothing about the elements that are not in common.
- cryptography№ 410
Federated Learning
A distributed machine-learning paradigm in which many clients collaboratively train a model under a central coordinator while keeping their raw data on-device.
- cryptography№ 248
Cryptographic Key
A high-entropy secret or public value that parameterizes a cryptographic algorithm to encrypt, decrypt, sign or authenticate data.