Secure Computation Output Distribution via Random Masking
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Solution Overview
Problem
Existing multiparty computation protocols for 1-out-of-3 secure scenarios lack fairness in distributing computation outputs, where one party can send incorrect results without being detected, and there is no guarantee that all parties receive the correct computation result.
Innovation Solution
A method involving random masking of computation outputs and Message Authentication Codes (MACs) is introduced, where evaluators share masked computation outputs and MACs with a dealer node, allowing verification and ensuring that either all parties receive the correct result or none do, thus ensuring fairness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a straightforward method is used where evaluators send computation outputs to the dealer, then the dealer can obtain the computation result, but the dealer cannot verify which evaluator sent the correct result and fairness is not guaranteed
Solution Approach 1:
The patent introduces random masks as an intermediary mechanism. Each evaluator adds a random mask to the computation output before sending it to the dealer. The dealer receives multiple masked outputs and can verify correctness by checking if the masked outputs are consistent with each other and with the original computation inputs, without needing to trust any single evaluator. This intermediary masking layer enables verification while maintaining protocol simplicity.
Solution Approach 2:
The patent transforms the computation output parameter by adding random masks to it. Instead of sending raw computation outputs, evaluators send masked outputs where the mask is a randomly generated value. This parameter transformation allows the dealer to verify correctness by checking consistency of masked outputs while preventing any single evaluator from unilaterally determining the final result, thus ensuring fairness.
2Reliability
If one evaluator sends a wrong computation result, then the dealer receives incorrect information, but the dealer has no way of detecting the error
Solution Approach 1:
The patent implements a feedback mechanism where the dealer sends the computed result back to the evaluators for verification. The evaluators can then check if the dealer's computed result (derived from their masked outputs) matches their own expectations. This feedback loop enables error detection because if one evaluator sent a wrong result, the inconsistency will be detected when the dealer computes the result and returns it to the evaluators for verification.
3Loss of time
If the dealer accepts the first received computation output, then the protocol terminates quickly, but fairness is compromised as later evaluators cannot verify correctness
Solution Approach 1:
The patent applies preliminary action by having all evaluators send their masked computation outputs to the dealer before the dealer computes and returns the final result. This preliminary exchange of masked outputs from all evaluators ensures that no single evaluator can unilaterally determine the outcome, as the dealer needs to aggregate and process all masked outputs before computing the final result. This preliminary action from all parties ensures fairness while maintaining reasonable protocol termination time.
Data Source
AI summary
According to an aspect, there is provided a method of operating a first computing node to distribute a computation output, the method comprising: determining a first random mask; providing the first random mask as a private input to a computation by a first evaluator node and a second evaluator node; receiving, from each of the first evaluator node and the second evaluator node, a respective masked computation output, wherein each masked computation output is a function of an output of the computation and the first random mask; if the received respective masked computation outputs match, determining the output of the computation from the received masked computation output and the first random mask; and sending information to the first evaluator node and the second evaluator node to enable the first evaluator node and the second evaluator node to determine the output of the computation from the respective masked computation output.