Random Number Distribution for Multi-Party Computation Bandwidth
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Solution Overview
Problem
In secure multi-party computation (MPC) scenarios, the existing methods require a large number of random numbers to be sent across the network, leading to significant network bandwidth occupation, which is inefficient and costly.
Innovation Solution
A method where a random number server generates and sends specific random number sets based on seeds to different devices, reducing the overall number of random numbers sent and thereby minimizing network bandwidth usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a large number of random numbers are sent across the network in MPC scenarios, then the security and correctness of computation is ensured, but network bandwidth occupation increases significantly
Solution Approach 1:
The patent segments the random number distribution process by separating seed generation from random number generation. The random number server generates and sends only seeds to computing devices, while the computing devices locally generate the actual random numbers needed for MPC operations. This segmentation reduces network bandwidth occupation by transmitting only compact seed values rather than large volumes of random numbers.
Solution Approach 2:
The patent introduces seeds as an intermediary element between the random number server and the random numbers used in MPC computations. Instead of directly transmitting random numbers, the server transmits seeds that serve as compact representations, which are then expanded into full random numbers locally at the computing devices. This intermediary approach maintains computational security while reducing network bandwidth requirements.
2Reliability
If random numbers are generated and distributed to multiple devices for MPC, then the computation can proceed securely, but the complexity of random number management increases
Solution Approach 1:
The patent implements self-service by enabling computing devices to autonomously generate their own random numbers locally using received seeds and local random number generation algorithms. Each device independently manages its own random number generation without requiring centralized distribution or coordination, thereby reducing the complexity of random number management across the system while maintaining secure computation execution.
Data Source
AI summary
The present disclosure relates to exchanging data for multi-party computation. In some aspects, a server generates a first random number set, a second random number set, a third random number set, and a fourth random number set based on a first random seed, a second random seed, a third random seed, and a fourth random seed, respectively. The sever generates a fifth random number set and a sixth random number set, respectively, based on the first random number set, the second random number set, the third random number set, and the fourth random number set. The random numbers in the random number sets satisfy a predetermined condition. The server sends the first random seed, the second random seed, and the fifth random number set to a first device. The server sends the third random seed, the fourth random seed, and the sixth random number set to a second device.