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Secure Multi-Party Computation(SMPC)
Privacy-preserving collaboration between multiple agents without revealing private data
In 30 seconds
- What
- Multiple agents compute results on encrypted data without any party seeing others' inputs, using secret sharing and homomorphic encryption.
- When to use
- Competing organizations need to collaborate on analysis (fraud detection, risk assessment) while keeping sensitive data completely private.
- Watch out
- Cryptographic overhead makes this extremely slow; only viable for low-frequency, high-stakes computations, not real-time systems.
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Secure Multi-Party Computation: Overview
Privacy-preserving collaboration between multiple agents without revealing private data
- Secret sharing schemes
- Homomorphic encryption
- Garbled circuits
- Privacy-preserving protocols
- Multi-party privacy guarantees
- Verifiable computation
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References
The papers, specifications, and repositories this pattern is based on.
- IEEE Privacy Engineering
- ACM Computing Surveys SMPC
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