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Multi-Party Computation (MPC)

Traditional data handling follows a decrypt-compute-reencrypt cycle: data has to be decrypted in order to run a computation, and then re-encrypted for storage or transmission. Decrypted data is vulnerable to unauthorized access and potential security breaches, exposing sensitive information during the computation phase.

MPC enables computation over inputs from multiple parties while keeping the actual data hidden. The data remains confidential throughout the entire process — not only when it's stored or in transit, but also during the actual computation. With MPC, you can collaborate to compute on hidden secrets without ever revealing the actual secrets.

Applied MPC​

Classic Scenario: The Millionaire Problem​

The "Millionaires Problem" is a classic MPC scenario, first introduced by Andrew Yao in 1982. In the "Millionaires Problem" problem, two millionaires want to find out who is richer without disclosing their actual net worth. Using MPC, the millionaires can jointly compute who has more money without revealing their individual net worths to each other or anyone else. This is achieved through a series of cryptographic operations that allow each party to input their net worth into a shared computation. The computation is structured in a way that it only outputs the comparison result (i.e., which millionaire is richer) without leaking any specifics about their respective net worths. This problem showcases the power of MPC - it can preserve privacy while enabling collaborative computation.

Real World Application: The 2008 Danish Sugar Beet Auction​

In the early 2000s, Denmark's sugar industry faced a critical challenge: how to conduct auctions for sugar beet contracts securely while maintaining confidentiality. Traditional auction methods required bidders to openly reveal their bids, leading to concerns about fairness and the potential for bid manipulation. To address these issues, the industry sought a solution that would enable secure bidding without compromising the privacy of individual bids.

Enter secure MPC. By leveraging MPC, farmers could submit encrypted bids to processors, ensuring that bid information remained confidential throughout the auction. This innovative approach not only safeguarded the integrity of the bidding process but also promoted fairness and transparency, setting a new standard for auction security and confidentiality in the sugar industry. The adoption of MPC led to a notable increase in beet farmer satisfaction. 80% of farmers surveyed emphasized the significance of maintaining bid confidentiality during the bidding. Responses indicated high levels of confidence in the fairness and confidentiality of the auction process, further solidifying the benefits of MPC in real-world applications. Read more about the Danish Sugar Beet Auction implementation in Secure Multiparty Computation Goes Live.

Additional MPC Resources​