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🤝 MPC: Compute on Encrypted Data
Learn how multiple parties compute without revealing inputs
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0 / 5 completedWhat is Multi-Party Computation?
**Multi-Party Computation (MPC)** is a cryptographic protocol that allows multiple parties to jointly compute a function over their private inputs without revealing those inputs to each other. It's like computing with encrypted data—each party contributes their secret, the computation happens collaboratively, and only the final result is revealed.
MPC solves the fundamental problem of **trust in computation**: how can mutually distrusting parties compute something together without a trusted third party? The answer: cryptographic protocols that guarantee privacy even if some participants are malicious.
🔐 The MPC Problem
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Multiple Parties
Each party has private input (salary, bid, vote, data)
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Shared Goal
Compute function f(x₁, x₂, ..., xₙ) together (average, max, sum)
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Privacy Guarantee
No party learns others' inputs, only the final result
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Security Even with Adversaries
Protocol works even if some parties are malicious (Byzantine fault tolerant)
Interactive: MPC Use Case Explorer
Explore real-world scenarios where MPC solves critical privacy problems.
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Average Salary Calculation
❌ The Problem
Three employees want to know their average salary without revealing individual salaries
Traditional Approach
Share salaries openly (privacy leak)
MPC Solution
Each splits salary into shares, compute on shares, reveal only average
✅ Privacy Guarantee
Individual salaries remain secret
Example
Alice ($60k), Bob ($80k), Carol ($70k) → Average: $70k (no one learns others' salaries)
MPC vs Traditional Approaches
❌ Trusted Third Party
- •Single point of failure (hack, corruption)
- •Sees all private data (privacy risk)
- •Must be trusted not to collude
- •Centralized control (censorship risk)
✅ MPC Protocol
- •Decentralized (no single point of failure)
- •Privacy guaranteed cryptographically
- •Works even with malicious participants
- •No trust required (trustless computation)
🔑 Core MPC Principles
1
Secret Sharing
Split private data into shares distributed among participants
2
Computation on Shares
Perform operations on encrypted shares without decrypting
3
Result Reconstruction
Combine output shares to reveal only the final result
4
Security Proof
Mathematical guarantee that no information leaks beyond the result
Real-World MPC Applications
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Financial Services
AML detection, fraud analysis, credit scoring without sharing customer data
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Healthcare
Multi-hospital research, genome analysis, drug discovery with patient privacy
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Blockchain
Threshold signatures, private smart contracts, confidential transactions