MPC

Multi-Party Computing is a secure distributed computating paradigm whereby the participating nodes are given data that lacks the knowledge necessary to reveal any confidential information. At the same time, these nodes can use this insufficient data to collectively perform a group computation that relies on confidential information. This model allows programs to leverage untrusted computational resources and confidential data to compute an outcome securely without exposing any secrets.

One use case for this technology is performing big data analysis on private patient data to achieve a sort of impromtu clinical trail in order to diagnose diseases.

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