Multiparty Queue Synchronization for Secure Computation
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Solution Overview
Problem
Conventional secure multiparty computation (SMPC) frameworks face challenges in synchronizing anonymized linked data across multiple queues, leading to computational overhead and concurrency issues, such as deadlocks and corruption due to misaligned data inputs.
Innovation Solution
The method involves a system and method for synchronizing anonymized linked data across multiple queues by using push and pop requests with digital signatures to ensure data integrity and synchronization, utilizing a Multiparty Queue (MPQ) system that distributes trust evenly among parties without a master node, allowing for instant synchronization and error detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional SMPC frameworks generate offline data for key operations, then secure computation can be performed, but computational overhead increases significantly
Solution Approach 1:
The system generates offline data (Beaver triples, comparison data) in advance and stores them in pre-synchronized queues before the actual secure computation is needed. This preliminary preparation eliminates the need for intensive computation during the online phase, resolving the contradiction between having secure computation capability available and maintaining computational efficiency.
2Productivity
If functions are started across multiple parties concurrently, then processing speed improves, but concurrency issues cause deadlocks or corruption
Solution Approach 1:
The system uses push tags and digital signatures as feedback mechanisms to track and verify the state of data across all parties. Each party sends push tags to others, and digital signatures provide cryptographic verification that all parties have received and processed the same data in the same order, enabling concurrent processing while maintaining synchronization and preventing deadlocks.
Solution Approach 2:
Push tags act as intermediaries that coordinate the concurrent operations across multiple parties. By exchanging and verifying push tags with digital signatures, the system mediates the concurrent data operations to ensure they proceed in a synchronized manner without causing deadlocks or corruption.
3Loss of information
If data is split into secret shares across parties, then privacy is protected, but data synchronization becomes complex
Solution Approach 1:
Instead of directly synchronizing the actual secret shares across parties, the system synchronizes push tags that are cryptographic copies or representations of the data operations. The digital signatures on these tags verify that all parties have the corresponding secret shares in the correct state, simplifying synchronization while maintaining privacy.
Data Source
AI summary
Disclosed herein are systems and methods for synchronizing anonymized linked data across multiple queues for SMPC. The systems and methods guarantee that data is kept private from a plurality of nodes, yet can still be synced within a local queue, across the plurality of local queues. In conventional SMPC frameworks, specialised data known as offline data is required to perform key operations, such as multiplication or comparisons. The generation of this offline data is computationally intensive, and thus adds significant overhead to any secure function. The disclosed system and methods aid in the operation of generating and storing offline data before it is required. Furthermore, the disclosed system and methods can help start functions across multi-parties, preventing concurrency issues, and align secure input data to prevent corruption.