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Confidential product-sum computation method, confidential product-sum computation system, computation apparatus, and program for same

Technology of a computing device and computing method, applied in the fields of hidden product sum computing systems, computing devices and their programs

Active Publication Date: 2013-09-25
NIPPON TELEGRAPH & TELEPHONE CORP
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Since the multiplication operation requires communication and random number generation, it becomes the bottleneck of the hidden function calculation of the three sub-devices

Method used

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  • Confidential product-sum computation method, confidential product-sum computation system, computation apparatus, and program for same
  • Confidential product-sum computation method, confidential product-sum computation system, computation apparatus, and program for same
  • Confidential product-sum computation method, confidential product-sum computation system, computation apparatus, and program for same

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0073] figure 1 shows a configuration example of the hidden product sum computing system 100, figure 2 Indicates an example of its processing flow. The hidden product sum computing system 100 includes a sub-device (party) X, a sub-device (party) Y, and a sub-device (party) Z as computing devices that respectively perform symmetrical calculation processing.

[0074] The hidden product sum calculation of the present invention is carried out through the coordinated calculation of the three calculation devices of sub-device X, sub-device Y, and sub-device Z to perform data sequence A 0 =(a0 0 ,...,a0 na0－1 ), A 1 =(a1 0 ,...,a1 na1 －1 ) and A 2 =(a2 0 ,...,a2 na2－1 ) with data column B 0 =(b0 0 ,...,b0 nb0－1 ), B 1 =(b1 0 ,...,b1 nb1－1 ) and B 2 =(b2 0 ,...,b2 nb2－1 ) product and calculation. na0, na1, na2, nb0, nb1, and nb2 are natural numbers respectively.

[0075] Such as image 3 As shown, each sub-device includes a random number generation unit 101 , a ...

Embodiment 2

[0112] Embodiment 2 is a specific example of Embodiment 1, and is na0=na1=na2=nb0=nb1=nb2=n (n is an integer greater than 1), e00=e01=e10=e11=e12=e21=e22=e20= The case of e02=1. Figure 4 A configuration example of the hidden product sum computing system 200 of this embodiment is shown, Figure 5 Indicates an example of its processing flow. The hidden product sum calculation system 200 includes a sub-device X, a sub-device Y, a sub-device Z, a data sequence decomposition supply unit 210 , and an output unit 220 . Same as Example 1, such as image 3 As shown, each sub-device includes a random number generation unit 101 , a first calculation unit 102 , and a second calculation unit 103 .

[0113] The hidden product sum calculation system 200, through the coordinated calculation of the three calculation devices of sub-device X, sub-device Y, and sub-device Z, calculates the element a of a natural number smaller than the prime number p i , b i (i=0,...,n-1) two data columns A...

Embodiment 3

[0154] Embodiment 3 is a structure in which a fraud detection function is added to Embodiments 1 and 2 which perform product sum calculation. Figure 6 shows a configuration example of the hidden product sum computing system 300, Figure 7 Indicates an example of its processing flow. The hidden product sum calculation system 300 includes a sub-device X, a sub-device Y, and a sub-device Z as computing devices that perform respective symmetrical calculation processing.

[0155] The hidden product sum calculation of the present invention is performed for a total of m groups of q=0,...,m-1 (m is an integer greater than 1) through the coordinated calculation of the three computing devices of sub-device X, sub-device Y, and sub-device Z (Parallel when m is 2 or more) Perform data column A q_0 =(a0 q_0 ,...,a0 q_na0－1 ), A q_1 =(a1 q_0 ,...,a1 q_na1－1 ) and A q_2 =(a2 q_0 ,...,a2 q_na2－1 ) with data column B q_0 =(b0 q_0 ,...,b0 q_nb0 －1 ), B q_1 =(b1 q_0 ,...,b1 q_nb1...

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Abstract

Provided is a fast and easy-to-implement method for performing confidential product-sum computation based on coordinated computations by three parties (computation apparatuses). In a confidential computation method in which: a party X performs a party X random number generation step, a party X first computation step, and a party X second computation step; a party Y performs a party Y random number generation step, a party Y first computation step, and a party Y second computation step; and a party Z performs a party Z random number generation step, a party Z first computation step, and a party Z second computation step, the computation processes of the respective parties are symmetrically configured.

Description

technical field [0001] The present invention relates to a hidden product-sum computing method, a hidden product-sum computing system, a computing device, and their programs for performing data processing, especially multiplication and product-sum operations, while concealing data through secret distribution. Background technique [0002] In the management and application of so-called sensitive information such as customer information and business information, security measures and personal privacy considerations have become more important issues due to the diversification of management information and changes in the information processing infrastructure such as cloud computing. Among them, recently, information leakage is prevented by distributing information in multiple places, and the popularization of secret distribution technology is being promoted. Furthermore, regarding the hidden function calculation (party protocol) that derives a specified calculation result without...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G09C1/00H04L9/08
CPCH04L9/085H04L2209/46G06F7/5443G06F7/57
Inventor 五十岚大滨田浩气千田浩司
Owner NIPPON TELEGRAPH & TELEPHONE CORP
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