Trusted Random Source for Secure Multi-Party Computation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing secure multi-party computation algorithms are vulnerable to data breaches due to the risk of malicious implementations constructing pseudo-random numbers based on private data, which can lead to privacy leakage when used as computing parameters.
Innovation Solution
The use of a trusted random number from a trusted random source as a computing parameter in secure multi-party computation, preventing the need for locally generated random numbers and thereby mitigating the risk of data breaches caused by malicious algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a trusted random number from a trusted random source is used as a computing parameter, then data security and privacy protection are improved, but system complexity increases due to the need for trusted random sources and audit mechanisms
Solution Approach 1:
A trusted random source is introduced as an intermediary component that provides cryptographically secure random numbers to the secure multi-party computation system. This mediator ensures that random numbers cannot be predicted or manipulated by malicious parties, thereby enhancing data security without requiring changes to the core computation logic
Solution Approach 2:
An audit mechanism is implemented that verifies the security properties of random numbers used in computations. The system performs audits on random number generation processes and maintains audit logs that provide feedback on the security status of the computation system, allowing detection and correction of potential security issues
2Reliability
If audit mechanisms are implemented to verify random number security, then privacy leakage risk is reduced, but computational overhead and processing time increase
Solution Approach 1:
The system performs security audits on random number generation processes in advance before actual secure multi-party computations are executed. By pre-verifying the security properties of random numbers and pre-establishing audit trails, the system minimizes the time penalty during actual computation operations
Solution Approach 2:
The audit mechanism uses lightweight verification methods that do not require complex computational resources. Audit logs are maintained as simple records that can be efficiently generated and verified, minimizing the computational overhead while still providing robust security verification
Data Source
AI summary
Embodiments of a multi-party secure computation method applicable to any one computing node deployed in a distributed network are provided. A plurality of computing nodes are deployed in the distributed network, the plurality of computing nodes jointly participate in a secure multi-party computation based on respectively held private data, and the computing node that performs the method is connected to a trusted random source. The method includes: obtaining a trusted random number from the trusted random source; performing an operation on the held private data based on the obtained trusted random number to obtain an operation result; and transmitting a computing parameter comprising at least the trusted random number to other computing nodes participating in secure multi-party computation, so that the other computing nodes perform the secure multi-party computation based on collected computing parameters transmitted by the computing nodes participating in the secure multi-party computation.