Secure Computation System for Fisher's Exact Test
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Solution Overview
Problem
Existing methods for computing Fisher's exact test assume specific values for frequencies, making it difficult to keep input data secret during secure computation, particularly in genome-wide association studies.
Innovation Solution
A secure computation system with multiple devices computes secure texts of frequency combinations using reference frequencies and pattern computation, ensuring that only encrypted values are processed, allowing efficient computation of Fisher's exact test without disclosing input data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional secure computation methods are used to compute Fisher's exact test, then input data secrecy is maintained, but computational resources and processing time increase significantly
Solution Approach 1:
The patent segments the computation of Fisher's exact test by dividing the frequency combinations into two parts: (a+b, c+d) which are computed securely using encrypted values, and (a+c, b+d) which are pre-computed and stored in lookup tables. This segmentation allows the system to maintain input data secrecy while significantly reducing computational burden by eliminating the need to securely compute all four frequency values.
Solution Approach 2:
The patent applies preliminary action by pre-computing the marginal sums (a+c) and (b+d) and storing them in lookup tables before the actual secure computation takes place. This pre-computation step allows these values to be retrieved directly during the test execution, avoiding the need for time-consuming secure computation operations on these particular values.
2Measurement precision
If all frequency combinations are computed securely, then complete accuracy is achieved, but the number of computations becomes unmanageably large
Solution Approach 1:
The patent extracts the computationally intensive part of the calculation by isolating only (a+b) and (c+d) for secure computation, while taking out (a+c) and (b+d) and handling them through lookup tables. This extraction reduces the number of secure computations required while maintaining the accuracy of the Fisher's exact test through the use of pre-computed reference values.
3Reliability
If encrypted values are processed for all frequency components, then data secrecy is maintained, but processing time increases
Solution Approach 1:
The patent applies preliminary action by pre-computing the marginal sums (a+c) and (b+d) and storing them in lookup tables before the actual secure computation takes place. This pre-computation step allows these values to be retrieved directly during the test execution, avoiding the need for time-consuming secure computation operations on these particular values.
Solution Approach 2:
The patent segments the computation of Fisher's exact test by dividing the frequency combinations into two parts: (a+b, c+d) which are computed securely using encrypted values, and (a+c, b+d) which are pre-computed and stored in lookup tables. This segmentation allows the system to maintain input data secrecy while significantly reducing computational burden by eliminating the need to securely compute all four frequency values.
Data Source
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AI summary
Fisher's exact test is efficiently computed through secure computation. It is assumed that a, b, c and d are frequencies of a 2×2 contingency table, [a], [b], [c] and [d] are secure texts of the respective frequencies a, b, c and d, and N is an upper bound satisfying a+b+c+d≤N. A reference frequency computation part 12 computes a secure text ([a0], [b0], [c0], [d0]) of a combination of reference frequencies (a0, b0, c0, d0) which are integers satisfying a0+b0=a+b, c0+d0=c+d, a0+c0=a+c, and b0+d0=b+d. A number-of-patterns determination part 13 determines integers h0 and h1 satisfying h0≤h1. A pattern computation part 14 computes [ai]=[a0]+i, [bi]=[b0]-i, [ci]=[c0]-i and [di]=[d0]+i for i=h0,..., h1, and obtains a set S={([ai], [bi], [ci], [di])}i of secure texts of combinations of frequencies (ai, bi, ci, di).