Distributed Biometric Metric Calculation via Segmented Data Shares
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Solution Overview
Problem
Existing biometric data comparison methods lack secure and efficient mechanisms for calculating metrics representative of differences between data pieces, particularly in secure and distributed environments, where confidentiality and authorization are critical.
Innovation Solution
A distributed calculation method for a metric f(X, Y) is proposed, where f(X, Y) is calculated across multiple devices using predefined functions and intermediate data, allowing for secure and efficient comparison of biometric data by summing results from each device to determine the difference between two data sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If biometric data is stored in a centralized database for comparison, then the calculation of metrics can be performed efficiently, but the confidentiality and security of the data are compromised
Solution Approach 1:
The patent divides the biometric data into multiple shares and distributes them across several devices. Each device holds only a portion of the data, and the complete metric calculation requires combining results from multiple devices. This segmentation prevents any single device from accessing the full biometric data, thereby maintaining confidentiality while enabling efficient comparison operations.
Solution Approach 2:
The patent introduces an intermediary mechanism where devices compute partial metrics based on their data shares and transmit these partial results to a central collector. The collector aggregates these partial results to obtain the final metric. This intermediary approach allows efficient calculation without requiring centralized storage of complete biometric data, thus resolving the contradiction between calculation efficiency and data confidentiality.
2Reliability
If distributed calculation is used to secure biometric data, then confidentiality is improved, but the calculation complexity and processing time increase
Solution Approach 1:
The patent segments the complex metric calculation into simpler partial calculations that can be performed independently on each device. Each device computes a partial metric based on its data share using simplified operations, and the final result is obtained by aggregating these partial results. This segmentation reduces the computational complexity at each individual device while maintaining overall calculation accuracy and data confidentiality.
3Reliability
If multiple devices are involved in the calculation process, then data security is enhanced, but the processing time and system complexity increase
Solution Approach 1:
The patent performs preliminary actions by pre-processing and distributing data shares to multiple devices before the actual metric calculation. Each device is pre-configured with its data share and the necessary computation instructions. During the calculation phase, devices can independently compute their partial metrics in parallel without requiring sequential coordination, thereby reducing processing time while maintaining enhanced security through multi-device involvement.
Data Source
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AI summary
A distributed calculation method for a metric f(X,Y) representing a difference between a data point X comprising n bits (x1, ..., xn) and a data point Y, the metric f(X,Y) being of the form fXY=fXX+∑i=1nfixiY+fYY, the method being implemented by a system comprising m + 1 devices, the method comprising: - for any j from 1 to m, calculation of at least one intermediate data point by the device of index j depending on the data point X and the data point Y, and transmission to the device of index m + 1 of at least one result comprising or depending on each intermediate data point, - determination, by the device of index m + 1, of the metric f(X, Y), the determination comprising a summation of each result to obtain a value equal to ∑i=1nfixiY or a value equal to ∑i=1nfixiY+fYY.