Why Multi-Party Computation Alone Isn't Enough for Data Markets

MPC is a narrow solution that only addresses computation on encrypted data. It assumes the existence of clean, structured, and trustworthy input data, which is the primary bottleneck in analytics. The data sourcing problem remains unsolved, as MPC provides no mechanism to incentivize or guarantee the quality of raw data feeds from external sources like IoT sensors or private databases.

Trust shifts, but doesn't vanish. While MPC eliminates the need for a single trusted compute node, it creates a new dependency on the honest majority assumption among key-share holders. This model, similar to the security of many Proof-of-Stake networks, fails if a quorum colludes, leaving the computation's integrity unverifiable by the data consumer or buyer.

Verifiable computation is non-negotiable. A true data market requires cryptographic proof of correct execution, like a zk-SNARK, that any party can verify. MPC's private computation offers opacity, not proof. Protocols like Arbitrum's BOLD for fraud proofs or RISC Zero's zkVM demonstrate that verifiability is a prerequisite for scalable, trust-minimized commerce.

Evidence: The failure of early data marketplaces like Ocean Protocol v2, which relied heavily on MPC-like compute-to-data, showed that without guaranteed data provenance and verifiable outputs, commercial adoption stalls. Successful models now integrate zero-knowledge proofs and oracle networks like Chainlink to anchor data authenticity before computation even begins.

MPC is a coordination protocol. It orchestrates computation across multiple parties, ensuring no single entity sees the raw input data. This enables services like threshold signature schemes for wallet security and privacy-preserving analytics.

ZKPs are a verifiable property. They generate a cryptographic receipt that proves a computation's correctness without revealing its inputs. This transforms an MPC's output from a claim into a cryptographically assured fact.

MPC without ZKPs lacks verifiability. A data consumer must trust the MPC node operators executed the function correctly. This reintroduces a trusted execution layer, negating the decentralized trust model required for scalable data markets.

The combination is non-optional. For a data marketplace like Space and Time or Ocean Protocol, ZKPs provide the auditable truth of computed results, while MPC enables the raw computation on private datasets. One handles process, the other provides proof.

MPC creates data silos. Each computation enclave is a black box. Data from a Chainlink oracle or a Pyth feed is processed in isolation, preventing direct integration with on-chain smart contracts like Uniswap or Aave. This kills the composable liquidity that defines DeFi.

Silos fragment liquidity. A prediction market using MPC cannot natively use collateral from a lending protocol. This is the opposite of the composability that made Ethereum's DeFi summer possible, where protocols like MakerDAO and Compound became interoperable money legos.

The market demands on-chain state. Protocols like EigenLayer and Celestia succeed because they provide verifiable, shared state. MPC's private outputs are useless for building a shared financial layer. The value is in the verifiable public ledger, not the private computation.

Evidence: Look at adoption. The largest data markets, like DIA Oracle or API3's Airnode, prioritize on-chain verifiability. Niche MPC use cases exist, but they are exceptions that prove the rule for scalable, liquid markets.

MPC's speed advantage is a red herring. Multi-party computation protocols like Threshold Signature Schemes achieve fast signature aggregation by sacrificing decentralization and finality. This trade-off is acceptable for wallet signing but catastrophic for data attestation.

The finality problem is fatal. MPC committees provide probabilistic, not deterministic, security. A market like Ocean Protocol or a verifiable compute network like Ritual requires on-chain, universally verifiable proofs, not a quorum's promise.

Compare to ZK proofs. A zk-SNARK from a RISC Zero prover is slower to generate but provides a cryptographic guarantee of correctness. The data consumer verifies this proof in milliseconds, achieving both speed and trustlessness.

Evidence: In a data market, the bottleneck is not computation speed but settlement finality. An MPC-attested data feed requires a separate, slower blockchain transaction to be useful, negating its initial speed benefit entirely.