CN112688779B

CN112688779B - Data processing method and device and data processing device

Info

Publication number: CN112688779B
Application number: CN202110255743.3A
Authority: CN
Inventors: 王天雨
Original assignee: Huakong Tsingjiao Information Technology Beijing Co Ltd
Current assignee: Huakong Tsingjiao Information Technology Beijing Co Ltd
Priority date: 2021-03-09
Filing date: 2021-03-09
Publication date: 2021-07-13
Anticipated expiration: 2041-03-09
Also published as: CN112688779A

Abstract

The embodiment of the invention provides a data processing method and device and a device for data processing. The method comprises the following steps: under the condition that the security computing task meets the preset conversion condition, performing type conversion on a secret sharing factor of computing data of the security computing task by using a relation random number held by each participant; and executing the safe computing task based on the secret sharing factor of the computing data after the type conversion. The embodiment of the invention can improve the efficiency of calculating the calculation data, and further improve the efficiency of executing the safe calculation task.

Description

Data processing method and device and data processing device

Technical Field

The present invention relates to the field of computer technologies, and in particular, to a data processing method and apparatus, and an apparatus for data processing.

Background

Secret Share (Secret Share) is a method for distributing, storing and recovering secrets, and is an important means for implementing Multi-party secure computing (MPC).

For a multi-party secure computing system adopting addition secret sharing, addition computation (such as x + y) can be completed by each participant based on the local secret sharing factor, and multiplication computation needs to consume more communication and computation; for multi-party secure computing systems that employ multiplicative secret sharing, multiplicative calculations (e.g., x y) may be performed by each party based on a locally held secret sharing factor, while additive calculations require more communication and computation.

In practical applications, a large number of addition calculations and multiplication calculations may be included in one calculation task, which greatly reduces the calculation efficiency of the multi-party secure computing system.

Disclosure of Invention

Embodiments of the present invention provide a data processing method and apparatus, and an apparatus for data processing, which can improve computation efficiency when a large number of addition computations and multiplication computations are simultaneously included in a computation task.

In order to solve the above problem, an embodiment of the present invention discloses a data processing method, where the method includes:

under the condition that the security computing task meets the preset conversion condition, performing type conversion on a secret sharing factor of computing data of the security computing task by using a relation random number held by each participant;

and executing the safe computing task based on the secret sharing factor of the computing data after the type conversion.

In another aspect, an embodiment of the present invention discloses a data processing apparatus, where the apparatus includes:

the conversion module is used for performing type conversion on a secret sharing factor of the computing data of the security computing task by using the relation random number held by each participant under the condition that the security computing task meets the preset conversion condition;

and the execution module is used for executing the safe computing task based on the secret sharing factor of the computing data after type conversion.

In yet another aspect, an embodiment of the present invention discloses an apparatus for data processing, comprising a memory, and one or more programs, wherein the one or more programs are stored in the memory, and configured to be executed by one or more processors comprises instructions for:

In yet another aspect, an embodiment of the invention discloses a machine-readable medium having stored thereon instructions, which, when executed by one or more processors, cause an apparatus to perform a data processing method as described in one or more of the preceding.

The embodiment of the invention has the following advantages:

in the embodiment of the invention, under the condition that the security computing task meets the preset conversion condition, the secret sharing factor of the computing data of the security computing task is subjected to type conversion by using the relation random number held by each participant, and the secret sharing factor of the computing data in the security computing task is converted into a type more suitable for the current computing environment (such as a secret sharing algorithm adopted by a multi-party security computing system), so that the type of the secret sharing factor of the computing data after conversion is more matched with the type of the secret sharing algorithm adopted by the multi-party security computing system, the efficiency of computing the computing data is improved, and the efficiency of executing the security computing task can be further improved.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments of the present invention will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive labor.

FIG. 1 is a flow chart of the steps of one data processing method embodiment of the present invention;

FIG. 2 is a schematic diagram showing the present invention showing two parties each holding a relational random number;

FIG. 3 is a schematic diagram of a process of two participants obtaining respective self-sustaining relational random numbers through cooperative computing according to the present invention;

FIG. 4 is a schematic diagram of a process for two parties to convert a secret sharing factor from an addition type to a multiplication type through a cooperative computing according to the present invention;

FIG. 5 is a schematic diagram of the present invention showing the holding of relational random numbers by participants in the case of more than two participants;

FIG. 6 is a schematic diagram of a process of obtaining the respective self-sustaining relational random numbers by two or more participants through cooperative computing according to the present invention;

FIG. 7 is a schematic diagram of a process for two or more parties to transform a secret sharing factor from an addition type to a multiplication type through a collaborative computation according to the present invention;

FIG. 8 is a block diagram of an embodiment of a data processing apparatus of the present invention;

FIG. 9 is a block diagram of an apparatus 800 for data processing of the present invention;

fig. 10 is a schematic diagram of a server in some embodiments of the invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The terms first, second and the like in the description and in the claims of the present invention are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that embodiments of the invention may be practiced other than those illustrated or described herein, and that the objects identified as "first," "second," etc. are generally a class of objects and do not limit the number of objects, e.g., a first object may be one or more. Furthermore, the term "and/or" in the specification and claims is used to describe an association relationship of associated objects, meaning that three relationships may exist, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. The term "plurality" in the embodiments of the present invention means two or more, and other terms are similar thereto.

Referring to fig. 1, a flowchart illustrating steps of an embodiment of a data processing method according to the present invention is shown, where the method may specifically include the following steps:

step 101, under the condition that the security computing task meets the preset conversion condition, performing type conversion on a secret sharing factor of computing data of the security computing task by using a relation random number held by each participant;

and 102, executing the safe computing task based on the secret sharing factor of the computing data after type conversion.

The data processing method of the embodiment of the invention can be applied to a multi-party safe computing system, and the multi-party safe computing system is a computing system for protecting data privacy and safety. Under the premise of not leaking self data, a plurality of participants can use the multi-party safety computing technology to carry out collaborative computing to obtain computing results, and the data participating in computing, intermediate results and final results can be guaranteed not to be leaked. The participants can comprise task control nodes and computing nodes, and the task control nodes are used for scheduling the computing nodes to execute safe computing tasks; and the computing nodes perform cooperative computing based on the secret sharing factors held by the computing nodes respectively so as to complete the safe computing task.

It should be noted that, in the embodiment of the present invention, the number of the computing nodes participating in executing one secure computing task is not limited, and preferably, the number of the computing nodes participating in executing one secure computing task is greater than or equal to 2. Further, the participants may further include a data node for providing services such as data storage, data provision, calculation result storage, and the like. The multi-party security computing system may further include a result acquirer, configured to acquire a computation result from the computing node, where the result acquirer may be a specified certain data node or certain data nodes.

It will be appreciated that the private data may be any data that is not convenient to disclose, and may include, but is not limited to, data representing personal information of the user, or trade secrets or the like. In the embodiment of the present invention, the private data may be a ciphertext.

In the embodiment of the present invention, the secure computing task may be a computer program code implemented by a preset programming language, and the multi-party secure computing system may implement a corresponding computing function by executing the computer program code. The secure computing task includes, but is not limited to: and data related operations such as calculation, cleaning, analysis, model training, storage, database query and the like of the data are realized based on the ciphertext. It is to be understood that embodiments of the present invention do not impose limitations on the specific types of secure computing tasks.

A secure computation task may include any type of mathematical computation, such as four arithmetic computations (e.g., addition, subtraction, multiplication, division), logical computations (e.g., and, or, xor), etc.

The multi-party secure computing system may employ an additive secret sharing algorithm, which refers to slicing a secret S into additive-type secret sharing factors: a1, a2, …, an such that S = a1+ a2+ … + an. For n participants to a secure computing task, a first participant holds the secret sharing factor a1, a second participant holds the secret sharing factor a2, and so on, the nth participant holds the secret sharing factor an.

Alternatively, the multi-party secure computing system may employ a multiplicative secret sharing algorithm, which refers to slicing the secret S into secret sharing factors of the multiplicative type: b1, b2, …, bn, such that S = b1 × b2 × … × bn. For n participants of the secure computing task, a first participant holds the secret sharing factor b1, a second participant holds the secret sharing factors b2, …, and an nth participant holds the secret sharing factor bn.

If the addition secret sharing algorithm is adopted, the calculation addition operation is simple and convenient, but the calculation multiplication operation is complex, and the calculation efficiency is low. On the contrary, if the secret sharing algorithm is used, the operation is simpler and more convenient when the multiplication operation is calculated, but the operation is more complicated when the addition operation is calculated, and the calculation efficiency is lower.

In order to improve the calculation efficiency of a security calculation task when the security calculation task simultaneously comprises addition calculation and multiplication calculation, the embodiment of the invention performs type conversion on a secret sharing factor of calculation data of the security calculation task by using a relation random number held by each participant under the condition that the security calculation task meets a preset conversion condition. The safety calculation task meeting the preset conversion condition means that calculation influencing the execution efficiency of the safety calculation task exists in the safety calculation task. For example, for a multi-party secure computing system adopting an additive secret sharing algorithm, if multiplication occurs in a secure computing task, the execution efficiency of the secure computing task may be affected, and at this time, the secure computing task may be considered to satisfy a preset conversion condition. For another example, for a multi-party secure computing system adopting a multiplicative secret sharing algorithm, if additive computation occurs in a secure computing task, the execution efficiency of the secure computing task may be affected, and at this time, the secure computing task may be considered to meet a preset conversion condition.

In an alternative embodiment of the present invention, the preset transition condition includes, but is not limited to: the safety calculation task comprises continuous multiplication calculation, or the safety calculation task comprises continuous addition calculation.

For a multi-party secure computing system adopting an addition secret sharing algorithm, if continuous multiplication calculation occurs in a secure computing task, a large amount of communication and calculation cost needs to be consumed, and the execution efficiency of the secure computing task is greatly influenced. Similarly, for a multi-party secure computing system adopting a multiplicative secret sharing algorithm, if continuous addition computation occurs in a secure computing task, a large amount of communication and computation cost needs to be consumed, and the execution efficiency of the secure computing task is greatly influenced.

Therefore, in the embodiment of the present invention, under the condition that it is determined that the secure computation task satisfies the preset conversion condition, the secret sharing factor of the computation data of the secure computation task is subjected to type conversion by using the relationship random number held by each participant. The relation random number held by each participant can be used for converting the secret sharing factor of the calculation data from the addition type to the multiplication type or converting the secret sharing factor of the calculation data from the multiplication type to the addition type. In the embodiment of the present invention, the relationship random number is a random number having a certain calculation relationship, that is, the relationship random number held by each participant satisfies a preset relationship. According to the embodiment of the invention, based on the relation random number held by each participant, the secret sharing factor of the computing data in the security computing task is converted into the type more suitable for the current computing environment (the secret sharing algorithm adopted by the current multi-party security computing system), so that the type of the secret sharing factor of the computing data after conversion is more matched with the type of the secret sharing algorithm adopted by the multi-party security computing system, and the execution efficiency of the security computing task is improved.

In an optional embodiment of the present invention, the type converting the secret sharing factor of the computing data of the secure computing task includes:

under the condition that continuous multiplication calculation is included in the safety calculation task, converting a secret sharing factor of calculation data participating in the continuous multiplication calculation from an addition type to a multiplication type; alternatively, the first and second electrodes may be,

in the case that the secure computation task includes a successive addition computation, a secret sharing factor of computation data participating in the successive addition computation is converted from a multiplication type to an addition type.

For example, for a multi-party secure computing system adopting an addition secret sharing algorithm, if the secure computing task includes continuous multiplication, the secret sharing factor of the computing data participating in the continuous multiplication can be converted from an addition type to a multiplication type by using the relational random numbers held by each participant, and the continuous multiplication is executed based on the secret sharing factor of the computing data after the type conversion, so that the multiplication efficiency can be improved, and the execution efficiency of the secure computing task can be further improved. For another example, for a multi-party secure computing system using a multiplicative secret sharing algorithm, if the secure computing task includes continuous addition computation, the secret sharing factor of the computing data participating in the continuous addition computation may be converted from a multiplication type to an addition type by using a relational random number held by each participant, and the continuous addition computation may be executed based on the secret sharing factor of the computing data after type conversion, so that the efficiency of the addition computation may be improved, and the efficiency of executing the secure computing task may be further improved.

In an optional embodiment of the invention, the secure computing task comprises n participants, the method further comprising: the n participants respectively obtain the relationship random numbers held by the n participants, and the relationship random numbers held by the n participants respectively meet the preset relationship;

the performing type conversion on the secret sharing factor of the computing data of the secure computing task by using the relationship random number held by each participant comprises: and the n participants perform type conversion on the secret sharing factor of the computing data of the secure computing task based on the respective held relationship random numbers.

In one example, assuming that the participants of a certain secure computing task include participant P1 and participant P2, for computing data x, participant P1 holds an addition-type secret sharing factor x1, participant P2 holds an addition-type secret sharing factor x2, x = x1+ x 2. Assuming that the calculation data x needs to participate in the successive multiplication calculation, in order to improve the efficiency of the successive multiplication calculation, the secret sharing factor of x may be converted from an addition type to a multiplication type. For example, the party P1 holds relationship random numbers r1 and r3, the party P2 holds relationship random numbers r2 and r4, and r1, r2, r3, r4 satisfy the following preset relationships: r1/r2= r3/r4, i.e. r1 × r4= r2 × r 3. The participant P1 performs type conversion on the secret sharing factor of the computation data held by the participant P1 based on the relationship random number held by the participant P1, and converts the secret sharing factor x1 of the addition type held by the participant P1 into the secret sharing factor x 1' = (r1 r4 x)/r3 of the multiplication type; the participant P2 type-converts the secret sharing factor of the calculation data it holds based on the relationship random number it holds, and converts the addition type secret sharing factor x2 it holds into the multiplication type secret sharing factor x 2' =1/r 2. The secret sharing factor of the calculation data x is converted from the addition type to the multiplication type, continuous multiplication calculation is carried out based on the secret sharing factor of the multiplication type, the continuous multiplication calculation efficiency can be greatly improved, and the efficiency of executing a safe calculation task is further improved.

It is to be understood that the manner of setting the relational random numbers in the above example is only an application example of the present invention, and the specific manner of generating the relational random numbers and the generated relational random numbers are not limited by the embodiment of the present invention. In addition, for convenience of description, a scenario in which the secret sharing factor is converted from the addition type to the multiplication type is mainly used as an example in the embodiment of the present invention, and for a scenario in which the secret sharing factor is converted from the multiplication type to the addition type, the generated relational random number may be different from the conversion from the addition type to the multiplication type.

In an optional embodiment of the invention, the method may further comprise: and generating the relation random number in advance before executing the safety calculation task, wherein the relation random number is obtained by the cooperative calculation of the participants of the safety calculation task, or the relation random number is obtained by the calculation of a trusted third party.

In practical application, because certain computing time is required for performing type conversion on the secret sharing factor of the computing data on line, in order to reduce the time for performing the online conversion and avoid the online conversion from influencing the execution efficiency of the security computing task, the embodiment of the invention divides the process of performing the type conversion on the secret sharing factor of the computing data into an offline preprocessing stage and an online conversion stage. The off-line preprocessing stage is irrelevant to the actual secret sharing factor and only takes charge of generating the relation random number required by the on-line conversion stage. The online conversion stage is to perform type conversion on the secret sharing factor of the computing data of the security computing task by using the relation random number generated in the offline preprocessing stage held by each participant before or in the process of executing the security computing task. The on-line conversion stage needs to consume the relational random numbers generated by the off-line preprocessing stage.

The method and the device have the advantages that the process of carrying out type conversion on the secret sharing factors of the calculated data is divided into the offline preprocessing stage and the online conversion stage, so that the offline preprocessing stage is decoupled from the actual secret sharing factors to be converted, a large amount of preprocessing data (namely, relation random numbers) are generated in advance in the offline preprocessing stage, and a part of communication and calculation processes of the conversion process are transferred to the offline preprocessing stage, so that the communication and calculation amount required by the online conversion stage is reduced, the actual conversion can be more efficiently completed in the online conversion stage, and the efficiency of the whole conversion process is improved.

It should be noted that, the number of the participants of the secure computing task is not limited in the embodiment of the present invention. The number of participants may be greater than or equal to 2. The embodiment of the present invention is mainly described by taking an example that two or more participants convert the secret sharing factor of the calculation data from an addition type to a multiplication type. The process of converting the secret sharing factor of the calculation data from the multiplication type to the addition type is similar for two or more participants, and the two or more participants can refer to each other.

In an optional embodiment of the present invention, n is 2, the n participants include a participant P1 and a participant P2, and the n participants respectively obtain relationship random numbers held by the participants respectively, including:

the participating parties P1 and P2 respectively acquire the relationship random numbers respectively held by the participating parties P1 and P3538 based on the first secure computing protocol, wherein the participating parties P1 hold the relationship random numbers r1 and r3, the participating parties P2 hold the relationship random numbers r2 and r4, and the relationship random numbers respectively held by the participating parties P1 and P2 satisfy the following preset relationships: r1 × r4= r2 × r 3.

In the case that there are two parties (such as the party P1 and the party P2) to the security computing task, in the offline preprocessing stage, the party P1 and the party P2 respectively obtain the respective held relationship random numbers based on the first security computing protocol, wherein the party P1 holds the relationship random numbers r1 and r3, the party P2 holds the relationship random numbers r2 and r4, and the relationship random numbers held by the party P1 and the party P2 respectively satisfy the following preset relationships: r1 × r4= r2 × r 3. Referring to fig. 2, a schematic diagram is shown in which each participant holds a relational random number in the case of two participants.

It is understood that, in the offline preprocessing stage, the relationship random numbers held by the participants may be obtained through collaborative calculation by the participants of the security calculation task, or may also be obtained through calculation by a trusted third party.

In the case where there is a trusted third party, in the above example, the relationship random numbers r1, r2, r3, r4 may be generated offline by the trusted third party, and r1, r2, r3, r4 satisfy the following preset relationships: r1/r2= r3/r4, i.e. r1 × r4= r2 × r 3. The trusted third party sends the generated relationship random numbers r1 and r3 to the participant P1 and the relationship random numbers r2 and r4 to the participant P2.

Referring to fig. 3, a schematic diagram of a process for two participants to obtain respective held relational random numbers through cooperative computing is shown. As shown in fig. 3, in the case that n =2, the participant P1 and the participant P2 respectively obtain the relationship random numbers held by the participants based on the first secure computing protocol, and the method includes the following steps:

step A1, participant P1 locally generates relation random number r1, and participant P2 locally generates relation random numbers r2 and r 4;

step A2, participant P2 calculates r4/r2 locally;

step a3, participant P1 and participant P2 calculate r1 (r4/r2) based on the first secure calculation protocol, and output the calculation result of r1 (r4/r2) to participant P1;

step a4, participant P1 locally calculates the relational random number r3= r1 (r4/r 2).

As shown in fig. 3, two parties may obtain respective relationship random numbers that satisfy a preset relationship on the basis of not revealing respective generated random number original texts.

In an alternative embodiment of the present invention, the first secure computing protocol described in step a3 includes, but is not limited to, any one of the following: a multiparty secure computing protocol, a homomorphic encryption protocol, an oblivious transfer protocol.

For example, in the case where the first secure computing protocol is a multi-party secure computing protocol, step a3 calculates r1 × (r4/r2) for party P1 and party P2 based on the multi-party secure computing protocol.

As another example, in the case where the first secure computing protocol is a homomorphic cryptographic protocol, step a3 computes r1 (r4/r2) for party P1 and party P2 based on the homomorphic cryptographic protocol. Specifically, the participant P1 encrypts r1 by using the public key of P1 to obtain a homomorphic ciphertext Cr1, and then sends Cr1 to the participant P2; the participant P2 encrypts r4/r2 using the public key of the participant P1 to obtain a homomorphic ciphertext Cr42, and then calculates a ciphertext product C = Cr1 × Cr 42; participant P2 sends C to participant P1, and participant P1 decrypts to obtain the relational random number r3= r1 (r4/r 2).

In an alternative embodiment of the invention, the party P1 and the party P2 hold secret sharing factors x1 and x2, respectively, of the type of addition of the calculation data x; the n participants perform type conversion on a secret sharing factor of the computing data of the secure computing task based on the respective held relationship random numbers, and the type conversion includes:

step S11, participant P1 calculates r1 x1 locally, participant P2 calculates r4 x2 locally, and participant P1 and participant P2 exchange the calculation results of r1 x1 and r4 x 2;

step S12, participant P1 calculates r1 (r4 × 2) locally, and participant P2 calculates r4 (r1 × 1) locally;

step S13, participant P1 and participant P2 calculate r1 (r4 × x2) + r4 (r1 × x1) based on the second secure calculation protocol, obtain calculation result r1 × r4 × x, and output calculation result r1 × r4 × x to participant P1;

step S14, the participant P1 converts the addition-type secret sharing factor x1 that it holds to the multiplication-type secret sharing factor x1 '= (r1 × r4 ×)/r3, and the participant P2 converts the addition-type secret sharing factor x2 that it holds to the multiplication-type secret sharing factor x 2' =1/r 2.

After the offline pre-processing stage generates the secret sharing factors that each participant individually holds, the online conversion stage may perform the operations of steps S11-S14. Referring to fig. 4, a schematic diagram of a process for two parties to convert a secret sharing factor from an addition type to a multiplication type through a collaborative computation is shown. Note that, in step S13, participant P1 and participant P2 calculate r1 × (r4 × 2) + r4 × (r1 × 1) based on the second secure computation protocol, and may obtain r1 × (r4 × 2) + r4 × (r1 × 1) = r1 × r4 (x1+ x2), and since x = x1+ x2, a calculation result r1 × r4 x may be obtained, and a calculation result r1 × r4 × x may be output to participant P1. The second secure computing protocol may be a multi-party secure computing protocol.

As shown in fig. 4, the party P1 and the party P2 convert the addition-type secret sharing factors x1, x2 into multiplication-type secret sharing factors x1 ', x 2' based on the relationship random numbers held by the respective secrets. That is, prior to conversion, x = x1+ x 2; after the conversion, x = x1 '× 2'. In the whole conversion process, the participator P1 and the participator P2 do not reveal the respective secret sharing factor original text and the respective relationship random number original text to each other, so that the privacy and the safety of the data information can be ensured.

For a multi-party secure computing system employing an additive secret sharing algorithm, it is assumed that the secure computing task includes multiplicative computations x y, where the computed data x is sliced into additive type secret sharing factors x1 and x2 such that x = x1+ x 2. The calculation data y is sliced into addition-type secret sharing factors y1 and y2 such that y = y1+ y 2. Assume that party P1 holds secret sharing factors x1 and y1 and party P2 holds secret sharing factors x2 and y 2. When calculating x × y = (x1+ x2) (y1+ y2), the calculation protocol is complicated, and the calculation efficiency is affected. By the embodiment of the invention, the addition type secret sharing factors x1 and x2 can be converted into multiplication type secret sharing factors x1 'and x 2', so that x = x1 '× 2'; the addition type of secret sharing factors y1 and y2 are converted into multiplication type of secret sharing factors y1 'and y 2', so that y = y1 '. times. 2'. After the conversion, party P1 holds the secret sharing factors x1 'and y 1', and party P2 holds the secret sharing factors x2 'and y 2'. In this way, the process of participant P1 and participant P2 cooperatively computing x = (x1+ x2) = (y1+ y2) may be converted to the process of participant P1 and participant P2 cooperatively computing x = (x1 '× x 2') (y1 '× y 2'). Therefore, the participants P1 and P2 can locally calculate x1 '. times. 1 and x2 '. times. 2 ', respectively, so as to complete the calculation process of the multiplication x.times.y, and the efficiency of calculating the multiplication x.times.y can be improved. Particularly, under the condition that the safety calculation task comprises continuous multiplication calculation, the calculation efficiency of the continuous multiplication can be greatly improved through the embodiment of the invention, and further, the efficiency of executing the safety calculation task can be improved.

Alternatively, steps S11 to S13 in the online conversion phase may be executed during the calculation interval of the safety calculation task along with the execution of the safety calculation task before the actual conversion, and only step S14 needs to be executed when the actual conversion is required, whereby the efficiency of the online conversion may be further improved. The computing gap of the secure computing task is such as idle time when the computing nodes of the multi-party secure computing system are not executing the computing task.

In an alternative embodiment of the invention, n is greater than 2, and the n participants comprise a participant P₁To party P_nThe n participants respectively obtain the relationship random numbers held by the n participants, and the method comprises the following steps:

participant P₁To party P_nRespectively acquiring the relationship random numbers held by the participants P based on a first secure computing protocol₁To party P_n-1Respectively hold relational random numbers r₁~r_n-1Participant P₁To party P_nHolding a relational random number r, participant P₁To party P_nRespectively hold relational random numbers R₁~R_nAnd party P₁To party P_nThe random numbers of the respective held relations satisfy the following preset relations: r is₁To r_n-1Is r, i.e. r = r₁*r₂*…*r_n-1；R₁To R_nIs 0, i.e. 0= R₁+R₂+…+R_n。

There are more than two participants in a secure computing task (e.g., participant P)₁To party P_nN is greater than 2), in the offline preprocessing phase, the participant P₁To party P_nRespectively acquiring the relationship random numbers held by the participants P based on a first secure computing protocol₁To party P_n-1Respectively hold relational random numbers r₁~r_n-1Participant P₁To party P_nHolding a relational random number r, participant P₁To party P_nRespectively hold relational random numbers R₁~R_nAnd party P₁To party P_nThe random numbers of the respective held relations satisfy the following preset relations: r is₁To r_n-1Is r (r = r)₁*r₂*…*r_n-1），R₁To R_nIs 0 (0 = R)₁+R₂+…+R_n）。

Referring to fig. 5, a schematic diagram is shown in which each participant holds a relational random number in the case of two or more participants. As shown in FIG. 5, the secure computing task includes a participant P₁To party P_nN participants, n being greater than 2. Participant P₁Holding relation random number r₁、r、R₁(ii) a Participant P₂Holding relation random number r₂、r、R₂(ii) a By analogy, party P_n-1Holding relation random number r_n-1、r、R_n-1(ii) a And a participant P_nHold relationship withNumber of machines R, R_n. The random number of relationships held by each of the n participants shown in fig. 5 satisfies the following preset relationships: r = r₁*r₂*…*r_n-1，0=R₁+R₂+…+R_n。

Referring to fig. 6, a schematic diagram of a process for two or more participants to obtain respective held relational random numbers through collaborative computation is shown. In case n is greater than 2, the participant P, as shown in fig. 6₁To party P_nBased on a first secure computing protocol, respectively acquiring the relationship random numbers held by the first secure computing protocol, comprising the following steps:

step B1, Party P₁To party P_n-1Respectively locally generating relational random numbers r₁~r_n-1；

Step B2, Party P₁To party P_nCalculating r = r based on a first secure computing protocol₁*r₂*…*r_n-1And respectively outputting the calculation results r to the participants P₁To party P_n；

Step B3, Party P₁To party P_nRespectively locally generating random numbers U₁~U_nParticipant P_iRandom number U generated by the same_iTo the participant P_i+1I takes values from 1 to n-1, participant P_nRandom number U generated by the same_nTo the participant P₁；

In particular, party P₁Locally generated random number U₁Participant P₂Locally generated random number U₂By analogy, party P_nLocally generated random number U_nAnd party P is involved₁Random number U generated locally₁To the participant P₂Participant P₂Random number U generated locally₂To the participant P₃By analogy, party P_n-1Random number U generated locally_n-1To the participant P_nParticipant P_nRandom number U generated locally_nTo the participant P₁。

Step (ii) ofB4 participant P₁To party P_nRespectively locally generating random numbers V₁~V_n；

Step B5, Party P₁To party P_nSeparately calculating relational random numbers R₁~ R_nWherein the participant P₁Calculating a relational random number R₁=V₁-U_nParticipant P_iCalculating a relational random number R_i=V_i-U_i-1And i takes the value of 2 to n.

In particular, party P₁Calculating a relational random number R₁=V₁-U_nParticipant P₂Calculating a relational random number R₂=V₂-U₁Participant P₃Calculating a relational random number R₃=V₃-U₂By analogy, party P_n-1Calculating a relational random number R_n-1=V_n-1-U_n-2And a party P_nCalculating a relational random number R_n=V_n-U_n-1。

As shown in fig. 6, two or more participants can obtain the relationship random numbers that satisfy the preset relationship and are held by themselves on the basis of not revealing the random number original texts that are generated by themselves.

In an alternative embodiment of the present invention, the first secure computing protocol in step B2 includes any one of the following: a multiparty secure computing protocol, a homomorphic encryption protocol, an oblivious transfer protocol.

For example, in the case that the first secure computing protocol is a multi-party secure computing protocol, step B2 is participant P₁To party P_nComputing r = r based on a multi-party secure computing protocol₁*r₂*…*r_n-1。

As another example, in the case where the first secure computing protocol is a homomorphic encryption protocol, step B2 is participant P₁To party P_nR = r calculation based on homomorphic cryptographic protocol₁*r₂*…*r_n-1. In particular, party P₁Using P₁Is a public key pair V₁The encryption is carried out to obtain homomorphic ciphertext Cv1, and then Cv1 is sent to the participant P_n(ii) a Participant P_nUsing Party P₁Public key pair U₂Encrypting to obtain homomorphic ciphertext Cu2, and then calculating a ciphertext difference C = Cv 1-Cun; participant P_nSending C to participant P₁Participant P₁Decrypting to obtain the relation random number R₂=V₁-U_n。

It should be noted that, in the case of existence of a trusted third party, the participant P may be generated offline by the trusted third party₁To party P_nAnd respectively sent to the participants P₁To party P_n。

In an alternative embodiment of the invention, the participant P₁To party P_nSecret sharing factors x each holding an addition type of calculation data x₁~x_n(ii) a The n participants perform type conversion on a secret sharing factor of the computing data of the secure computing task based on the respective held relationship random numbers, and the type conversion includes:

step S21, participant P₁To party P_nRespectively locally calculating r (x)_i-R_i) I takes the value from 1 to n;

step S22, participant P_nObtaining r (x) of all participants_i-R_i) Calculating the result, and calculating r (x) of each participant locally_i-R_i) Calculating the sum of the results to obtain S_n；

Step S23, participant P₁To party P_n-1Respectively converting the secret sharing factors of the addition type held by the secret sharing device into the secret sharing factor x of the multiplication type_i’=1/r_iI takes the value from 1 to n-1;

step S24, participant P_nConverting the addition type secret sharing factor held by the secret sharing factor into the multiplication type secret sharing factor x_n’=S_n。

After the offline pre-processing stage generates the secret sharing factors that each participant individually holds, the online conversion stage may perform the operations of steps S21-S24. Referring to fig. 7, a schematic diagram of a process for two or more parties to convert a secret sharing factor from an addition type to a multiplication type through a collaborative computation is shown.

As shown in FIG. 7, participant P₁To party P_nRespectively locally calculating r (x)_i-R_i) Thereafter, party P₁To party P_n-1Respectively calculating r (x) obtained by each calculation_i-R_i) The calculation result is sent to the participant P_nE.g. party P₁Calculated r (x) of it₁-R₁) The calculation result is sent to the participant P_nParticipant P₂Calculated r (x) of it₂-R₂) The calculation result is sent to the participant P_nBy analogy, party P_n-1Calculated r (x) of it_n-1-R_n-1) The calculation result is sent to the participant P_nTo enable the participant P_nR (x) of all participants can be obtained_i-R_i) Calculating the result, and calculating r (x) of each participant locally_i-R_i) The sum of the results of the calculations, i.e. S_n=r*(x₁-R₁)+r*(x₂-R₂)+…+r*(x_n-1-R_n-1)+r*(x_n-R_n) To obtain S_n. Note that, the participant P_nWhich may be any one of the n participants.

Prior to conversion, suppose participant P₁Secret sharing factor x holding calculation data x₁Participant P₂Holding secret sharing factor x₂By analogy, party P_nHolding secret sharing factor x_nAnd x = x₁+x₁+…+x_n. As shown in FIG. 7, participant P₁To party P_nBased on the relation random number held by each secret, the secret sharing factor x of the addition type is divided₁~x_nSecret sharing factor x converted to multiplication type₁’~x_n'. After conversion, participant P₁Holding secret sharing factor x₁', party P₂Holding secret sharing factor x₂', by analogy, participant P_nHolding secret sharing factor x_n', and x =x₁’*x₂’*…*x_n'. During the whole conversion process, the participant P₁To party P_nThe secret sharing factor original texts held by the users and the relation random number original texts held by the users cannot be disclosed to the other party, and the privacy and the safety of the data information can be guaranteed.

Alternatively, the steps S21 to S23 of the online conversion phase may be executed during the calculation interval of the safety calculation task along with the execution of the safety calculation task before the actual conversion, and only the step S24 needs to be executed when the actual conversion is required, thereby further improving the efficiency of the online conversion.

It should be noted that, in the embodiment of the present invention, the calculated data x and y are related to the random numbers r1, r2, r3, r4, and r₁~r_n-1，r，R₁~R_nRandom number U₁~U_n、V₁~V_nThe like are illustrative symbols and do not represent specific values, which may be substituted for specific values in actual practice.

In summary, in the embodiment of the present invention, under the condition that it is determined that the secure computation task satisfies the preset conversion condition, the type conversion is performed on the secret sharing factor of the computation data of the secure computation task by using the relational random numbers held by each participant, and the secret sharing factor of the computation data in the secure computation task is converted into a type more suitable for the current computation environment (for example, a secret sharing algorithm adopted by the current multi-party secure computation system), so that the type of the secret sharing factor of the computation data after conversion is more matched with the type of the secret sharing algorithm adopted by the multi-party secure computation system, thereby improving the efficiency of computing the computation data and further improving the efficiency of executing the secure computation task.

It should be noted that, for simplicity of description, the method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present invention is not limited by the illustrated order of acts, as some steps may occur in other orders or concurrently in accordance with the embodiments of the present invention. Further, those skilled in the art will appreciate that the embodiments described in the specification are presently preferred and that no particular act is required to implement the invention.

Device embodiment

Referring to fig. 8, a block diagram of a data processing apparatus according to an embodiment of the present invention is shown, where the apparatus may specifically include:

the conversion module 201 is configured to, under a condition that it is determined that the security computation task satisfies a preset conversion condition, perform type conversion on a secret sharing factor of computation data of the security computation task by using a relationship random number held by each participant;

an executing module 202, configured to execute the secure computing task based on the secret sharing factor of the type-converted computing data.

Optionally, the preset conversion condition includes: the safety calculation task comprises continuous multiplication calculation, or the safety calculation task comprises continuous addition calculation.

Optionally, the conversion module includes:

the first conversion sub-module is used for converting the secret sharing factor of the calculation data participating in the continuous multiplication calculation from an addition type to a multiplication type under the condition that the secure calculation task comprises the continuous multiplication calculation; alternatively, the first and second electrodes may be,

and the second conversion sub-module is used for converting the secret sharing factor of the calculation data participating in the continuous addition calculation from a multiplication type to an addition type under the condition that the secure calculation task comprises the continuous addition calculation.

Optionally, the secure computing task includes n participants, and the apparatus further includes:

a random number obtaining module, configured to obtain, through the n participants, relationship random numbers held by the n participants respectively, where the relationship random numbers held by the n participants respectively satisfy a preset relationship;

the conversion module is specifically configured to perform type conversion on a secret sharing factor of the calculation data of the secure calculation task based on the respective relationship random numbers held by the n participants.

Optionally, n is 2, the n participants include a participant P1 and a participant P2, and the random number obtaining module is specifically configured to obtain, based on a first secure computing protocol, relationship random numbers held by the participants P1 and P2 respectively, where the participant P1 holds the relationship random numbers r1 and r3, the participant P2 holds the relationship random numbers r2 and r4, and the relationship random numbers held by the participants P1 and P2 respectively satisfy the following preset relationships: r1 × r4= r2 × r 3.

Optionally, the random number obtaining module includes:

a first generation submodule for locally generating a relational random number r1 by the participant P1, and locally generating relational random numbers r2 and r4 by the participant P2;

a first computation submodule for locally computing r4/r2 by a participant P2;

a second calculation submodule for calculating r1 (r4/r2) based on the first secure calculation protocol by the participant P1 and the participant P2, and outputting a calculation result of r1 (r4/r2) to the participant P1;

a third computation submodule for locally computing a relational random number r3= r1 (r4/r2) by the participant P1.

Optionally, the party P1 and party P2 hold secret sharing factors x1 and x2, respectively, of the type of addition of the calculation data x; the conversion module comprises:

a fourth computation submodule for locally computing r1 x1 by participant P1, locally computing r4 x2 by participant P2, and exchanging the computation results of r1 x1 and r4 x2 by participant P1 and participant P2;

a fifth computation submodule for locally computing r1 (r4 x2) by participant P1, and r4 (r1 x1) by participant P2;

a sixth calculation submodule, configured to calculate r1 (r4 × 2) + r4 (r1 × 1) based on the second secure calculation protocol through the participant P1 and the participant P2, obtain a calculation result r1 × r4 × x, and output the calculation result r1 × r4 × x to the participant P1;

a first conversion submodule for converting the addition type secret sharing factor x1 that it holds into a multiplication type secret sharing factor x1 '= (r1 × r4 × x)/r3 through the participant P1, and the participant P2 converts the addition type secret sharing factor x2 that it holds into a multiplication type secret sharing factor x 2' =1/r 2.

Optionally, n is greater than 2, the n participants including participant P₁To party P_nThe random number obtaining module is specifically used for obtaining the random number by the participant P₁To party P_nRespectively acquiring the relationship random numbers held by the participants P based on a first secure computing protocol₁To party P_n-1Respectively hold relational random numbers r₁~r_n-1Participant P₁To party P_nHolding a relational random number r, participant P₁To party P_nRespectively hold relational random numbers R₁~R_nAnd party P₁To party P_nThe random numbers of the respective held relations satisfy the following preset relations: r is₁To r_n-1The product of (A) and (B) is R, R₁To R_nThe sum of (1) is 0.

Optionally, the random number obtaining module includes:

a second generation submodule for passing through the participant P₁To party P_n-1Respectively locally generating relational random numbers r₁~r_n-1；

A seventh computation submodule for passing through the participant P₁To party P_nCalculating r = r based on a first secure computing protocol₁*r₂*…*r_n-1And respectively outputting the calculation results r to the participants P₁To party P_n；

A third generation submodule for passing through the participant P₁To party P_nRespectively locally generating random numbers U₁~U_nParticipant P_iRandom number U generated by the same_iTo the participant P_i+1I takes values from 1 to n-1, participant P_nRandom number U generated by the same_nTo the participant P₁；

A fourth generation submodule for passing through the participant P₁To party P_nRespectively locally generating random numbers V₁~V_n；

An eighth computation submodule for passing through the participant P₁To party P_nSeparately calculating relational random numbers R₁~ R_nWherein the participant P₁Calculating a relational random number R₁=V₁-U_nParticipant P_iCalculating a relational random number R_i=V_i-U_i-1And i takes the value of 2 to n.

Optionally, the participant P₁To party P_nSecret sharing factors x each holding an addition type of calculation data x₁~x_n(ii) a The conversion module comprises:

a ninth computation submodule for passing through the participant P₁To party P_nRespectively locally calculating r (x)_i-R_i) I takes the value from 1 to n;

a tenth computation submodule for passing through the participant P_nObtaining r (x) of all participants_i-R_i) Calculating the result, and calculating r (x) of each participant locally_i-R_i) Calculating the sum of the results to obtain S_n；

A second conversion submodule for passing through the participant P₁To party P_n-1Respectively converting the secret sharing factors of the addition type held by the secret sharing device into the secret sharing factor x of the multiplication type_i’=1/r_iI takes the value from 1 to n-1;

a third conversion submodule for passing through the participant P_nConverting the addition type secret sharing factor held by the secret sharing factor into the multiplication type secret sharing factor x_n’=S_n。

Optionally, the first secure computing protocol includes any one of: a multiparty secure computing protocol, a homomorphic encryption protocol, an oblivious transfer protocol.

Optionally, the apparatus further comprises:

and the preprocessing module is used for generating the relation random number in advance before the safety calculation task is executed, wherein the relation random number is obtained by the cooperative calculation of the participants of the safety calculation task, or the relation random number is obtained by the calculation of a trusted third party.

For the device embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, refer to the partial description of the method embodiment.

The embodiments in the present specification are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.

With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.

An embodiment of the present invention provides an apparatus for data processing, comprising a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs comprising instructions for: under the condition that the security computing task meets the preset conversion condition, performing type conversion on a secret sharing factor of computing data of the security computing task by using a relation random number held by each participant; and executing the safe computing task based on the secret sharing factor of the computing data after the type conversion.

Fig. 9 is a block diagram illustrating an apparatus 800 for data processing in accordance with an example embodiment. For example, the apparatus 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, an exercise device, a personal digital assistant, and the like.

Referring to fig. 9, the apparatus 800 may include one or more of the following components: processing component 802, memory 804, power component 806, multimedia component 808, audio component 810, input/output (I/O) interface 812, sensor component 814, and communication component 816.

The processing component 802 generally controls overall operation of the device 800, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing elements 802 may include one or more processors 820 to execute instructions to perform all or a portion of the steps of the methods described above. Further, the processing component 802 can include one or more modules that facilitate interaction between the processing component 802 and other components. For example, the processing component 802 can include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 802.

The memory 804 is configured to store various types of data to support operation at the device 800. Examples of such data include instructions for any application or method operating on device 800, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 804 may be implemented by any type or combination of volatile or non-volatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.

Power components 806 provide power to the various components of device 800. The power components 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the apparatus 800.

The multimedia component 808 includes a screen that provides an output interface between the device 800 and a user. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front facing camera and/or a rear facing camera. The front-facing camera and/or the rear-facing camera may receive external multimedia data when the device 800 is in an operating mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

The audio component 810 is configured to output and/or input audio signals. For example, the audio component 810 includes a Microphone (MIC) configured to receive external audio signals when the apparatus 800 is in an operational mode, such as a call mode, a recording mode, and a voice information processing mode. The received audio signals may further be stored in the memory 804 or transmitted via the communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.

The I/O interface 812 provides an interface between the processing component 802 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.

The sensor assembly 814 includes one or more sensors for providing various aspects of state assessment for the device 800. For example, the sensor assembly 814 may detect the open/closed state of the device 800, the relative positioning of the components, such as a display and keypad of the apparatus 800, the sensor assembly 814 may also detect a change in position of the apparatus 800 or a component of the apparatus 800, the presence or absence of user contact with the apparatus 800, orientation or acceleration/deceleration of the apparatus 800, and a change in temperature of the apparatus 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

The communication component 816 is configured to facilitate communications between the apparatus 800 and other devices in a wired or wireless manner. The device 800 may access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on radio frequency information processing (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

In an exemplary embodiment, the apparatus 800 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors or other electronic components for performing the above-described methods.

In an exemplary embodiment, a non-transitory computer-readable storage medium comprising instructions, such as the memory 804 comprising instructions, executable by the processor 820 of the device 800 to perform the above-described method is also provided. For example, the non-transitory computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

Fig. 10 is a schematic diagram of a server in some embodiments of the invention. The server 1900 may vary widely by configuration or performance and may include one or more Central Processing Units (CPUs) 1922 (e.g., one or more processors) and memory 1932, one or more storage media 1930 (e.g., one or more mass storage devices) storing applications 1942 or data 1944. Memory 1932 and storage medium 1930 can be, among other things, transient or persistent storage. The program stored in the storage medium 1930 may include one or more modules (not shown), each of which may include a series of instructions operating on a server. Still further, a central processor 1922 may be provided in communication with the storage medium 1930 to execute a series of instruction operations in the storage medium 1930 on the server 1900.

The server 1900 may also include one or more power supplies 1926, one or more wired or wireless network interfaces 1950, one or more input-output interfaces 1958, one or more keyboards 1956, and/or one or more operating systems 1941, such as Windows Server, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, etc.

A non-transitory computer-readable storage medium in which instructions, when executed by a processor of an apparatus (server or terminal), enable the apparatus to perform the data processing method shown in fig. 1.

A non-transitory computer readable storage medium in which instructions, when executed by a processor of an apparatus (server or terminal), enable the apparatus to perform a data processing method, the method comprising: under the condition that the security computing task meets the preset conversion condition, performing type conversion on a secret sharing factor of computing data of the security computing task by using a relation random number held by each participant; and executing the safe computing task based on the secret sharing factor of the computing data after the type conversion.

Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.

It will be understood that the invention is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the invention is limited only by the appended claims.

The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.

The data processing method, the data processing apparatus and the apparatus for data processing provided by the present invention are described in detail above, and specific examples are applied herein to illustrate the principles and embodiments of the present invention, and the description of the above embodiments is only used to help understand the method and the core idea of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.

Claims

1. A method of data processing, the method comprising:

under the condition that the security computing task meets the preset conversion condition, performing type conversion on a secret sharing factor of computing data of the security computing task by using a relation random number held by each participant; the preset conversion conditions include: for a multi-party secure computing system adopting an addition secret sharing algorithm, multiplication calculation occurs in a secure computing task, or for a multi-party secure computing system adopting a multiplication secret sharing algorithm, addition calculation occurs in a secure computing task; the relation random number is a random number with a calculation relation, and the relation random numbers held by all the participants meet a preset relation;

executing the secure computing task based on the secret sharing factor of the computing data after type conversion;

wherein the secure computing task comprises n participants, in the case that n is 2, the n participants comprise a participant P1 and a participant P2, and the random numbers of the relationships held by the participants P1 and P2 satisfy the following preset relationships: r1 r4= r2 r3, participant P1 holds relational random numbers r1 and r3, participant P2 holds relational random numbers r2 and r 4; in the case where n is greater than 2, the n participants include a participant P₁To party P_nAnd party P₁To party P_nThe random numbers of the respective held relations satisfy the following preset relations: r is₁To r_n-1The product of (A) and (B) is R, R₁To R_nIs 0, participant P₁To party P_n-1Respectively hold relational random numbers r₁~r_n-1Participant P₁To party P_nHolding a relational random number r, participant P₁To party P_nRespectively hold relational random numbers R₁~R_n。

2. The method of claim 1, wherein the preset transition condition comprises: the safety calculation task comprises continuous multiplication calculation, or the safety calculation task comprises continuous addition calculation.

3. The method according to claim 1 or 2, wherein the type conversion of the secret sharing factor of the computing data of the secure computing task comprises:

4. The method of claim 1, further comprising:

the n participants respectively obtain the relationship random numbers held by the n participants, and the relationship random numbers held by the n participants respectively meet the preset relationship;

the performing type conversion on the secret sharing factor of the computing data of the secure computing task by using the relationship random number held by each participant comprises:

and the n participants perform type conversion on the secret sharing factor of the computing data of the secure computing task based on the respective held relationship random numbers.

5. The method of claim 4, wherein n is 2, and the n participants respectively obtain the relationship random numbers held by them, including:

the participant P1 and the participant P2 respectively acquire the relationship random numbers held by them based on the first secure computing protocol.

6. The method of claim 5, wherein the P1 and P2 respectively obtain the respective relational random numbers based on the first secure computing protocol, and comprise:

participant P1 locally generates relationship random numbers r1, and participant P2 locally generates relationship random numbers r2 and r 4;

the participant P2 locally calculates r4/r 2;

participant P1 and participant P2 calculate r1 (r4/r2) based on the first secure calculation protocol, and output the calculation result of r1 (r4/r2) to participant P1;

participant P1 locally calculates the relational random number r3= r1 (r4/r 2).

7. The method according to claim 5, characterized in that the parties P1 and P2 hold secret sharing factors x1 and x2, respectively, of the type of addition of the calculation data x; the n participants perform type conversion on a secret sharing factor of the computing data of the secure computing task based on the respective held relationship random numbers, and the type conversion includes:

participant P1 calculated r1 x1 locally, participant P2 calculated r4 x2 locally, and participant P1 and participant P2 exchanged the calculation results of r1 x1 and r4 x 2;

participant P1 calculated locally r1 (r4 x2), and participant P2 calculated locally r4 (r1 x 1);

participant P1 and participant P2 calculate r1 (r4 × 2) + r4 (r1 × 1) based on the second secure calculation protocol, obtain calculation result r1 × r4 × x, and output calculation result r1 × r4 × x to participant P1;

the participant P1 converts the addition-type secret sharing factor x1 that it holds into a multiplication-type secret sharing factor x1 '= (r1 × r4 × x)/r3, and the participant P2 converts the addition-type secret sharing factor x2 that it holds into a multiplication-type secret sharing factor x 2' =1/r 2.

8. The method of claim 4, wherein n is greater than 2, and the n participants respectively obtain the relationship random numbers held by the participants respectively, including:

participant P₁To party P_nBased on the first secure computing protocol, the relationship random numbers held by the first secure computing protocol are respectively obtained.

9. Method according to claim 8, characterized in that the party P₁To party P_nRespectively acquiring the relationship random numbers held by the first security computing protocol, wherein the method comprises the following steps:

participant P₁To party P_n-1Respectively locally generating relational random numbers r₁~r_n-1；

Participant P₁To party P_nCalculating r = r based on a first secure computing protocol₁*r₂*…*r_n-1And respectively outputting the calculation results r to the participants P₁To party P_n；

Participant P₁To party P_nAre respectively provided withLocally generated random number U₁~U_nParticipant P_iRandom number U generated by the same_iTo the participant P_i+1I takes values from 1 to n-1, participant P_nRandom number U generated by the same_nTo the participant P₁；

Participant P₁To party P_nRespectively locally generating random numbers V₁~V_n；

Participant P₁To party P_nSeparately calculating relational random numbers R₁~ R_nWherein the participant P₁Calculating a relational random number R₁=V₁-U_nParticipant P_iCalculating a relational random number R_i=V_i-U_i-1And i takes the value of 2 to n.

10. Method according to claim 8, characterized in that the party P₁To party P_nSecret sharing factors x each holding an addition type of calculation data x₁~x_n(ii) a The n participants perform type conversion on a secret sharing factor of the computing data of the secure computing task based on the respective held relationship random numbers, and the type conversion includes:

participant P₁To party P_nRespectively locally calculating r (x)_i-R_i) I takes the value from 1 to n;

participant P_nObtaining r (x) of all participants_i-R_i) Calculating the result, and calculating r (x) of each participant locally_i-R_i) Calculating the sum of the results to obtain S_n；

Participant P₁To party P_n-1Respectively converting the secret sharing factors of the addition type held by the secret sharing device into the secret sharing factor x of the multiplication type_i’=1/r_iI takes the value from 1 to n-1;

participant P_nConverting the addition type secret sharing factor held by the secret sharing factor into the multiplication type secret sharing factor x_n’=S_n。

11. The method according to any one of claims 5 to 10, wherein the first secure computing protocol comprises any one of: a multiparty secure computing protocol, a homomorphic encryption protocol, an oblivious transfer protocol.

12. The method of claim 1, further comprising:

and generating the relation random number in advance before executing the safety calculation task, wherein the relation random number is obtained by the cooperative calculation of the participants of the safety calculation task, or the relation random number is obtained by the calculation of a trusted third party.

13. A data processing apparatus, characterized in that the apparatus further comprises:

the conversion module is used for performing type conversion on a secret sharing factor of the computing data of the security computing task by using the relation random number held by each participant under the condition that the security computing task meets the preset conversion condition; the preset conversion conditions include: for a multi-party secure computing system adopting an addition secret sharing algorithm, multiplication calculation occurs in a secure computing task, or for a multi-party secure computing system adopting a multiplication secret sharing algorithm, addition calculation occurs in a secure computing task; the relation random number is a random number with a calculation relation, and the relation random numbers held by all the participants meet a preset relation;

the execution module is used for executing the safe computing task based on the secret sharing factor of the computing data after type conversion;

wherein the secure computing task comprises n participants, in the case that n is 2, the n participants comprise a participant P1 and a participant P2, and the random numbers of the relationships held by the participants P1 and P2 satisfy the following preset relationships: r1 r4= r2 r3, participant P1 holds relational random numbers r1 and r3, participant P2 holds relational random numbers r2 and r 4; in the case where n is greater than 2, the n participants include a participant P₁To party P_nAnd party P₁Radix GinsengAnd party P_nThe random numbers of the respective held relations satisfy the following preset relations: r is₁To r_n-1The product of (A) and (B) is R, R₁To R_nIs 0, participant P₁To party P_n-1Respectively hold relational random numbers r₁~r_n-1Participant P₁To party P_nHolding a relational random number r, participant P₁To party P_nRespectively hold relational random numbers R₁~R_n。

14. The apparatus of claim 13, wherein the preset transition condition comprises: the safety calculation task comprises continuous multiplication calculation, or the safety calculation task comprises continuous addition calculation.

15. The apparatus of claim 13 or 14, wherein the conversion module comprises:

16. The apparatus of claim 13, further comprising:

17. The apparatus of claim 16, wherein n is 2, and the random number obtaining module is specifically configured to obtain the relationship random numbers held by the parties based on the first secure computing protocol through the parties P1 and P2.

18. The apparatus of claim 17, wherein the random number obtaining module comprises:

a first computation submodule for locally computing r4/r2 by a participant P2;

19. The apparatus according to claim 17, wherein the party P1 and party P2 hold secret sharing factors x1 and x2, respectively, of the type of addition of the calculation data x; the conversion module comprises:

20. The apparatus of claim 16, wherein n is greater than 2, and wherein the random number obtaining module is specifically configured to obtain the random number by the participant P₁To party P_nBased on the first secure computing protocol, the relationship random numbers held by the first secure computing protocol are respectively obtained.

21. The apparatus of claim 20, wherein the random number obtaining module comprises:

22. The apparatus of claim 20, wherein the party P is a party P₁To party P_nSecret sharing factors x each holding an addition type of calculation data x₁~x_n(ii) a The conversion module comprises:

23. The apparatus of any of claims 17 to 22, wherein the first secure computing protocol comprises any of: a multiparty secure computing protocol, a homomorphic encryption protocol, an oblivious transfer protocol.

24. The apparatus of claim 13, further comprising:

25. An apparatus for data processing, the apparatus comprising a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs comprising instructions for:

26. The apparatus of claim 25, wherein the preset transition condition comprises: the safety calculation task comprises continuous multiplication calculation, or the safety calculation task comprises continuous addition calculation.

27. The apparatus according to claim 25 or 26, wherein the type conversion of the secret sharing factor of the computing data of the secure computing task comprises:

28. The device of claim 25, wherein the device is also configured to execute the one or more programs by one or more processors includes instructions for:

29. The apparatus of claim 28, wherein n is 2, and wherein the n participants respectively obtain the respective relational random numbers held by them, comprises:

30. The apparatus of claim 29, wherein the participating parties P1 and P2 respectively obtain the respective relational random numbers based on a first secure computing protocol, comprising:

the participant P2 locally calculates r4/r 2;

participant P1 locally calculates the relational random number r3= r1 (r4/r 2).

31. The apparatus according to claim 29, wherein the party P1 and party P2 hold secret sharing factors x1 and x2, respectively, of the type of addition of the calculation data x; the n participants perform type conversion on a secret sharing factor of the computing data of the secure computing task based on the respective held relationship random numbers, and the type conversion includes:

32. The apparatus of claim 28, wherein n is greater than 2, and wherein the n participants respectively obtain the respective relational random numbers, comprising:

33. The apparatus of claim 32, wherein the party P is a party P₁To party P_nRespectively acquiring the relationship random numbers held by the first security computing protocol, wherein the method comprises the following steps:

Participant P₁To party P_nRespectively locally generating random numbers U₁~U_nParticipant P_iRandom number U generated by the same_iTo the participant P_i+1I takes values from 1 to n-1, participant P_nRandom number U generated by the same_nTo the participant P₁；

34. The apparatus of claim 32, wherein the party P is a party P₁To party P_nSecret sharing factors x each holding an addition type of calculation data x₁~x_n(ii) a The n participants perform type conversion on a secret sharing factor of the computing data of the secure computing task based on the respective held relationship random numbers, and the type conversion includes:

35. The apparatus of any one of claims 29 to 34, wherein the first secure computing protocol comprises any one of: a multiparty secure computing protocol, a homomorphic encryption protocol, an oblivious transfer protocol.

36. The device of claim 25, wherein the device is also configured to execute the one or more programs by one or more processors includes instructions for:

37. A machine-readable medium having stored thereon instructions which, when executed by one or more processors, cause an apparatus to perform the data processing method of any of claims 1 to 12.