Trusted Execution Environment for Secure Sample Alignment
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Solution Overview
Problem
Existing hardware encryption machines are not flexible enough for various application scenarios, limiting their versatility in sample alignment operations, particularly in multi-participant data processing where data privacy is a concern.
Innovation Solution
The implementation of trusted execution environments (TEEs) in participant systems to securely obtain, intersect, and shuffle sample identifiers, ensuring alignment without revealing original identifiers, and allowing for customization to meet different application needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a hardware encryption machine is used to encrypt sample IDs, then data privacy is protected, but versatility for different application scenarios is reduced
Solution Approach 1:
The patent uses homomorphic encryption to create cryptographic copies of sample IDs that can be processed in encrypted form. These cryptographic representations allow intersection operations to be performed without decrypting the original data, thereby protecting privacy while enabling versatile application across different scenarios through standardized cryptographic protocols
Solution Approach 2:
The patent changes the state of data from plaintext to encrypted form using homomorphic encryption, allowing mathematical operations to be performed on the encrypted parameters. This parameter transformation enables the same encryption mechanism to serve multiple application scenarios with different privacy requirements, improving versatility while maintaining security
2Adaptability or versatility
If hardware encryption machines are customized for different application scenarios, then specific needs are met, but device complexity and implementation difficulty increase
Solution Approach 1:
The patent implements a universal homomorphic encryption framework that can handle multiple application scenarios through a single standardized interface. The same encryption library and protocol can be applied across different industries and use cases (medical, financial, marketing), eliminating the need for custom hardware encryption machines for each scenario and reducing overall system complexity
Data Source
AI summary
A method for sample alignment is applied to a first participant system, where a first trusted execution environment is deployed at the first participant system. The method includes, in the first trusted execution environment, obtaining at least one first sample identifier of the first participant system; through the first trusted execution environment, obtaining at least one second sample identifier of the second participant system from the second trusted execution environment, where the second trusted execution environment is deployed at the second participant system; in the first trusted execution environment, determining the first initial intersection of the at least one first sample identifier and the at least one second sample identifier and performing the shuffle processing on all first target sample identifiers in the first initial intersection to obtain the first target intersection; and based on the first target intersection, determining the first sample alignment result.