Confidential Multi-Party Computation - Terminal 3 Documentation

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Currently, multiple parties that wish to collaborate or compute on joint datasets (e.g., analyzing overlapping customer bases) must either share their sensitive data with each other or rely on a centralized, trusted third party, both of which risk exposing private information. For instance, two competing banks attempting to identify shared fraudulent activity cannot legally share their customers’ Personally Identifiable Information (PII) with one another to run a joint analysis.A typical confidential multiparty computation flow on T3N can look like this:

1. Multiple data owners (e.g., Bank A and Bank B) store their private data in T3N or allow T3N to access their private data.
2. The parties authorize a mutually agreed-upon TEE contract that defines the exact computation to run on the combined dataset.
3. When the computation executes, T3N securely processes the combined data inside a hardware Trusted Execution Environment (TEE), ensuring the raw inputs remain hidden from all parties.
4. The TEE contract outputs only the final computed results to the authorized parties, keeping the underlying data completely private.

Examples of confidential multiparty computation:

• Collaborative fraud detection among financial institutions.
• Joint medical research across multiple healthcare providers.
• Secure supply chain optimization between competing enterprises.
• Privacy-preserving advertising attribution and audience matching.
• Benchmarking and market analysis on aggregated proprietary datasets.