Why Multi-Party Computation and Blockchain Are Complementary, Not Redundant

Public blockchains are transparent ledgers, leaking sensitive data like trading strategies and institutional positions. This creates front-running risks and regulatory friction.

• MPC Solution: Enables private computation on public data, allowing for confidential DeFi transactions and shielded order routing via protocols like Aztec or FHE-based networks.
• Result: Institutions can participate without exposing their alpha, unlocking $10B+ in currently sidelined capital.

Proving every state transition on-chain (e.g., Ethereum's ~15 TPS) is fundamentally unscalable for high-frequency operations like order matching or real-time gaming.

• MPC Solution: Offloads complex computation (like batched trades or game logic) to an MPC network, settling only the cryptographic proof or final state on-chain. This mirrors the Solana philosophy but for arbitrary logic.
• Result: Achieves ~500ms finality for complex apps, reducing L1 congestion fees by -70% for bulk operations.

Self-custody is a single point of failure; centralized custodies reintroduce trust. MPC provides a superior trust model by distributing key shards.

• Blockchain Anchor: The on-chain state acts as the immutable, canonical settlement layer for the MPC network's outputs, preventing equivocation. This is the core innovation behind Fireblocks and Libra/Diems's original design.
• Result: Enables institutional-grade $1B+ wallet security with programmable, multi-sig-like policies without on-chain gas overhead.

Users express intents (e.g., 'get the best price for 100 ETH') but face fragmented liquidity and security risks across chains like Ethereum, Solana, Arbitrum.

• MPC as Solver: An MPC network can confidentially compute the optimal cross-chain route, leveraging UniswapX, Across, and LayerZero quotes without revealing the user's full strategy.
• Result: Delivers ~5% better execution on large trades by sourcing liquidity privately, moving beyond simple atomic swap bridges.

Traditional cloud compute (AWS) is fast but opaque. ZK-proofs are verifiable but computationally heavy for general-purpose logic.

• MPC + Blockchain Hybrid: MPC handles the heavy compute with inherent fraud detection (via secret-shared validation), while the blockchain provides a cheap, final fraud-proof challenge layer. This is the Espresso Systems model.
• Result: Enables 1000x more complex dApp logic (e.g., AI inference) with ~1s verification time, versus minutes for a ZK-VM.

Regulators (SEC, MiCA) are defining assets and custody rules. MPC's auditable, policy-driven control is more compliant than anonymous wallets.

• On-Chain Enforcement: Smart contracts can whitelist MPC nodes that meet regulatory standards (KYC/AML), creating a compliant gateway. This is critical for RWA tokenization and institutional DeFi.
• Result: Unlocks TradFi pipelines, allowing regulated entities to interact with DeFi protocols like Aave and Compound without legal ambiguity.

A central server must aggregate encrypted model updates from 100+ hospitals. How do you prove the aggregation was performed correctly without decrypting the data and breaking privacy? Pure MPC is computationally heavy for this scale, and pure blockchain can't compute on encrypted data.

• Verification Gap: Hospitals cannot trust the central coordinator's output.
• Performance Bottleneck: Homomorphic encryption for the entire model is computationally prohibitive, creating a ~100x latency overhead.

Use a lightweight MPC committee (e.g., using secret sharing) to perform the secure aggregation. Then, commit the cryptographic proofs of correct computation (e.g., zk-SNARKs or attestations) to an immutable ledger like Ethereum or a Celestia data availability layer.

• Auditable Trail: Every aggregation step is recorded on-chain, enabling slashing for malicious actors.
• Scalable Design: Offloads heavy computation to a small MPC network, maintaining sub-2 second finality for the consensus layer.

Blockchain enables a cryptoeconomic layer impossible with MPC alone. Hospitals earn tokens for contributing verified model updates, while MPC validators stake tokens and are slashed for provable malfeasance.

• Aligned Incentives: Replaces fragile legal agreements with automated, enforceable crypto-economics.
• Sybil Resistance: Protocols like EigenLayer can provide decentralized trust for the MPC committee selection, preventing collusion.

Real-world implementations show the blueprint works. Oasis Labs uses a trusted execution environment (TEE)-based confidential compute layer with a consensus blockchain. Phala Network combines TEEs with a Polkadot parachain for decentralized AI.

• Hybrid Trust Model: Leverages hardware security (TEE/MPC) for execution and blockchain for ordering and settlement.
• Composability: The on-chain record allows aggregated models to be used as assets in DeFi or data marketplaces.

Public ledgers expose all transaction logic and state. This kills institutional adoption for DeFi and confidential business logic. Zero-Knowledge proofs are computationally heavy for complex operations.

• MPC enables private computation on encrypted data before a single, minimal result is posted on-chain.
• Projects like Penumbra and Aztec use MPC-influenced designs for shielded pools and private DeFi.

Single points of failure in private key storage are the #1 cause of catastrophic hacks. MPC distributes signing authority across multiple parties.

• Threshold signatures (e.g., t-of-n) ensure no single entity holds a complete key, mitigating insider threats and external attacks.
• Adopted by major custodians (Fireblocks, Coinbase) and wallets (ZenGo) to secure >$1T in assets.

Bridges like Multichain and Wormhole have lost >$2B to exploits, often due to centralized multisig control over vast asset pools.

• MPC-based bridges (e.g., Chainlink CCIP) use decentralized oracle networks to run threshold signatures for attestations, removing single operator risk.
• Intent-based architectures (Across, Socket) use MPC for faster, cheaper verification before settling on a destination chain.

Blockchains are slow and expensive state machines. Complex computations (AI inference, game logic) are economically impossible on-chain.

• MPC networks act as verifiable co-processors, executing heavy logic off-chain and committing only cryptographic proofs (like zk-proofs).
• Enables decentralized AI (Bittensor), high-frequency DEX order matching, and verifiable randomness (Chainlink VRF).

On-chain voting exposes strategy and requires constant wallet connectivity for signers, creating security and operational bottlenecks for $30B+ in DAO Treasuries.

• MPC enables asynchronous, private voting where members compute the result off-chain. Only the final, authorized transaction is broadcast.
• Reduces attack surface and enables faster execution for protocols like Uniswap and Aave governance.

Chainlink demonstrates the blueprint: MPC secures oracle data feeds and cross-chain messages, while blockchains guarantee payment and settlement.

• Functions: Uses a decentralized oracle network (DON) running MPC to fetch & compute off-chain data, returning a single verified result.
• CCIP: Employs a Risk Management Network with independent nodes running threshold signatures to secure cross-chain token transfers and messaging.