Privacy set intersection method, device, equipment and system

Abstract

The embodiment of the invention provides a privacy set intersection method, device, equipment and system, and relates to the field of information security. The method comprises the following steps: generating at least one subscript data, and sending the ith subscript data to a second computing device; wherein the ith subscript data is used for obtaining the ith confusion data; the ith confusion data is a selection result based on an obligate transmission (OT) operation on the ith blinded data; receiving the ith confusion data sent by the second computing device; determining a first hash value of each piece of second privacy data in a second privacy set according to the ith confusion data and the second privacy set of the first computing equipment; receiving a second hash value of the ith first privacy data sent by the second computing device; and determining an intersection according to the second hash value and each first hash value. The method is used for achieving the effects of reducing the overall data interaction frequency and improving the operation and communication efficiency.

Description

Technical Field

[0001] The present application relates to the field of information security, and in particular to a privacy set intersection method, device, equipment and system. Background Art

[0002] Privacy computing technology is a key technology to achieve "available but invisible" data. Among them, privacy set intersection is an important branch of secure multi-party computing. It allows data holding participants to obtain the intersection data between the privacy sets of each participant through calculation without leaking any data information other than the intersection data, such as user data or device data and other privacy data that needs to be protected.

[0003] In the prior art, based on the Oblivious Transfer (OT) design framework, the classic OT protocol is used to randomly blindly transmit the private data in the privacy set to be intersected, and perform intersection processing to achieve the effect of privacy protection.

[0004] However, in the above method, the oblivious transmission method is adopted, and the number of times the OT protocol is performed is related to the data format. For each privacy set with a longer data format, the more times the OT protocol needs to be operated, resulting in an increase in the communication overhead required for the calculation process, affecting the overall calculation efficiency. Summary of the invention

[0005] The embodiments of the present application provide a privacy set intersection method, apparatus, device and system to solve the technical problem that the longer the data format of each privacy set is, the more times the OT protocol needs to be operated, resulting in an increase in the communication overhead required for the calculation process and affecting the overall calculation efficiency.

[0006] In a first aspect, an embodiment of the present application provides a privacy set intersection method, the method being applied to a first computing device in a secure computing system; the secure computing system also includes a second computing device; the method comprising:

[0007] Generate at least one subscript data, and send the i-th subscript data to the second computing device; wherein the i-th subscript data is used to obtain the i-th obfuscated data; the i-th obfuscated data is a selection result based on the oblivious transmission (OT) operation on the i-th blinded data; the i-th blinded data is obtained by processing the i-th first private data in the first privacy set of the second computing device;

[0008] receiving the i-th obfuscated data sent by the second computing device; and determining, according to the i-th obfuscated data and the second privacy set of the first computing device, a first hash value of each second privacy data in the second privacy set;

[0009] Receive the second hash value of the i-th first privacy data sent by the second computing device; and determine an intersection according to the second hash value and each of the first hash values; wherein the intersection includes the privacy data common to the first privacy set and the second privacy set.

[0010] In a possible implementation, determining, according to the i-th obfuscated data and the second privacy set of the first computing device, a first hash value of each second privacy data in the second privacy set includes:

[0011] Determining a target encryption algorithm; and generating a target pseudo-random function according to the target encryption algorithm;

[0012] Determine a first hash value of each second private data according to the i-th obfuscated data, the target pseudo-random function and each second private data.

[0013] In a possible implementation, generating a target pseudo-random function according to the target encryption algorithm includes:

[0014] Determine a public key parameter and a private key parameter; and send the public key parameter to the second computing device; wherein the public key parameter is used to generate encryption information, and the encryption information includes obfuscation parameter information and key information of the target encryption algorithm;

[0015] receiving the encrypted information sent by the second computing device; and decrypting the encrypted information according to the private key parameter to obtain obfuscation parameter information and key information of the target encryption algorithm;

[0016] The target pseudo-random function is generated according to the key information, the obfuscation parameter information and the target encryption algorithm.

[0017] In a possible implementation, generating the target pseudo-random function according to the key information, the obfuscation parameter information, and the target encryption algorithm includes:

[0018] The target pseudo-random function is generated according to the key information, the obfuscation parameter information, the target encryption algorithm and the encryption parameter information of the target encryption algorithm; wherein the encryption parameter information represents the parameter form of the target encryption algorithm.

[0019] In a possible implementation, determining the first hash value of each second private data according to the i-th obfuscated data, the target pseudo-random function, and each second private data includes:

[0020] Determining, according to the i-th obfuscated data, the target pseudo-random function and the second private data, comparison data corresponding to the second private data;

[0021] A hash operation is performed on the comparison data to obtain a first hash value of the second private data.

[0022] In a possible implementation, determining, according to the i-th obfuscated data, the target pseudo-random function, and the second private data, comparison data corresponding to the second private data includes:

[0023] Performing calculation processing on the j-th second private data according to the target pseudo-random function to obtain a calculation result corresponding to the j-th second private data;

[0024] Determine the comparison data corresponding to the j-th second privacy data according to the calculation result corresponding to the j-th second privacy data, the i-th obfuscation data and the target obfuscation parameter; wherein the target obfuscation parameter is the obfuscation parameter corresponding to the i-th obfuscation data in the obfuscation parameter information sent by the second computing device.

[0025] In a possible implementation manner, the comparison data corresponding to the j-th second private data is in, is the i-th obfuscated data, is the target confusion parameter, F k (x j ) is the calculation result corresponding to the j-th second privacy data.

[0026] In a possible implementation, determining a target encryption algorithm includes:

[0027] The target encryption algorithm is determined according to data features corresponding to the first privacy set and the second privacy set; wherein the target encryption algorithm has encryption parameter information, and the encryption parameter information represents the parameter form of the target encryption algorithm.

[0028] In a possible implementation, determining an intersection according to the second Hash value and each of the first Hash values ​​includes:

[0029] If it is determined that among the first hash values ​​there is a first hash value corresponding to the j-th second private data which is equal to the second hash value, then the j-th second private data is determined to be the public private data in the intersection.

[0030] In a second aspect, an embodiment of the present application provides a privacy set intersection method, the method being applied to a second computing device in a secure computing system; the secure computing system also includes a first computing device; the method comprising:

[0031] Determine a random private key corresponding to each first private data in the first privacy set of the second computing device; and hide the i-th first private data according to the i-th random private key to obtain the i-th blinded data;

[0032] Receive the i-th subscript data sent by the first computing device; at the same time, send the i-th blinded data to the first computing device; wherein the i-th blinded data is used to obtain the i-th obfuscated data based on the oblivious transmission (OT) operation; the i-th obfuscated data is used to generate a first hash value of each second private data in the second private set of the first computing device;

[0033] Determine a second hash value of the i-th first privacy data; and send the second hash value to the first computing device; wherein the first hash value and each of the second hash values ​​are used to generate an intersection; and the intersection includes the privacy data common to the first privacy set and the second privacy set.

[0034] In a possible implementation, the i-th first private data is hidden according to the i-th random private key to obtain the i-th blinded data, including:

[0035] Determining a target encryption algorithm, and generating a target pseudo-random function according to the target encryption algorithm;

[0036] The i-th first private data is hidden according to the i-th random private key and the target pseudo-random function to obtain the i-th blinded data.

[0037] In a possible implementation, generating a target pseudo-random function according to the target encryption algorithm includes:

[0038] The target pseudo-random function is generated according to the target encryption algorithm and the key information of the target encryption algorithm; at the same time, obfuscation parameter information is generated; wherein the obfuscation parameter information includes a first obfuscation parameter and a second obfuscation parameter.

[0039] In a possible implementation, the method further includes:

[0040] receiving the public key parameters sent by the first computing device; and encrypting the key information and the obfuscation parameter information according to the public key parameters to obtain encrypted information;

[0041] The encrypted information is sent to the first computing device.

[0042] In a possible implementation, performing hiding processing on the i-th first private data according to the i-th random private key and the target pseudo-random function to obtain the i-th blinded data includes:

[0043] Performing calculation processing on the i-th first private data according to the target pseudo-random function to obtain a calculation result of the i-th first private data;

[0044] Generate obfuscation parameter information; and obtain the i-th blinded data according to the obfuscation parameter information, the i-th random private key and the calculation result of the i-th first privacy data.

[0045] In a possible implementation, obtaining the i-th blinded data according to the obfuscation parameter information, the i-th random private key, and a calculation result of the i-th first private data includes:

[0046] Obtaining a first blinding value in the i-th blinded data according to a calculation result of the first obfuscation parameter in the obfuscation parameter information, the i-th random private key, and the i-th first private data;

[0047] A second blinding value in the i-th blinded data is obtained according to a calculation result of a second obfuscation parameter in the obfuscation parameter information, the i-th random private key, and the i-th first privacy data.

[0048] In a possible implementation manner, the first blinding value in the i-th blinding data Among them, k i is the i-th random private key, α 0 is the first confusion parameter, F k (y i ) is the calculation result of the i-th first privacy data;

[0049] The second blinding value in the i-th blinding data Among them, α 1 is the second obfuscation parameter.

[0050] In a possible implementation, determining a target encryption algorithm includes:

[0051] The target encryption algorithm is determined according to data features corresponding to the first privacy set and the second privacy set; wherein the target encryption algorithm has encryption parameter information, and the encryption parameter information represents the parameter form of the target encryption algorithm.

[0052] In a third aspect, an embodiment of the present application provides a privacy set intersection device, the device is applied to a first computing device in a secure computing system; the secure computing system also includes a second computing device; the device includes:

[0053] A sending module, configured to generate at least one subscript data, and send the i-th subscript data to the second computing device; wherein the i-th subscript data is used to obtain the i-th obfuscated data; the i-th obfuscated data is a selection result based on the oblivious transmission (OT) operation performed on the i-th blinded data; the i-th blinded data is obtained by processing the i-th first private data in the first privacy set of the second computing device;

[0054] A first determination module, configured to receive the i-th obfuscated data sent by the second computing device; and determine a first hash value of each second private data in the second private set according to the i-th obfuscated data and the second private set of the first computing device;

[0055] The second determination module is used to receive the second hash value of the i-th first privacy data sent by the second computing device; and determine the intersection according to the second hash value and each of the first hash values; wherein the intersection includes the privacy data common between the first privacy set and the second privacy set.

[0056] In a possible implementation, the first determination module is specifically used to: determine a target encryption algorithm; and generate a target pseudo-random function based on the target encryption algorithm; and determine a first hash value of each second privacy data based on the i-th obfuscated data, the target pseudo-random function and each second privacy data.

[0057] In one possible implementation, the first determination module is specifically used to: determine public key parameters and private key parameters; and send the public key parameters to the second computing device; wherein the public key parameters are used to generate encrypted information, and the encrypted information includes obfuscation parameter information and key information of the target encryption algorithm; receive the encrypted information sent by the second computing device; and decrypt the encrypted information according to the private key parameters to obtain obfuscation parameter information and key information of the target encryption algorithm; generate the target pseudo-random function according to the key information, the obfuscation parameter information and the target encryption algorithm.

[0058] In a possible implementation, the first determination module is further specifically used to generate the target pseudo-random function based on the key information, the obfuscation parameter information, the target encryption algorithm and the encryption parameter information of the target encryption algorithm; wherein the encryption parameter information represents the parameter form of the target encryption algorithm.

[0059] In a possible implementation, the first determination module is further specifically used to: determine the comparison data corresponding to the second private data according to the i-th obfuscated data, the target pseudo-random function and the second private data; and perform a hash operation on the comparison data to obtain a first hash value of the second private data.

[0060] In a possible implementation, the first determination module is further specifically used to: perform calculation processing on the j-th second private data according to the target pseudo-random function to obtain a calculation result corresponding to the j-th second private data; determine the comparison data corresponding to the j-th second private data according to the calculation result corresponding to the j-th second private data, the ith obfuscation data and a target obfuscation parameter; wherein the target obfuscation parameter is an obfuscation parameter corresponding to the ith obfuscated data in the obfuscation parameter information sent by the second computing device.

[0061] In a possible implementation manner, the comparison data corresponding to the j-th second private data is in, is the i-th obfuscated data, is the target confusion parameter, F k (x j ) is the calculation result corresponding to the j-th second privacy data.

[0062] In a possible implementation, the first determination module is further specifically used to: determine the target encryption algorithm according to data features corresponding to the first privacy set and the second privacy set; wherein the target encryption algorithm has encryption parameter information, and the encryption parameter information represents the parameter form of the target encryption algorithm.

[0063] In a possible implementation manner, the second determination module is specifically configured to: if it is determined that among the first hash values, the first hash value corresponding to the j-th second private data is equal to the second hash value, determine that the j-th second private data is the public private data in the intersection.

[0064] In a fourth aspect, an embodiment of the present application provides a privacy set intersection device, the device is applied to a second computing device in a secure computing system; the secure computing system also includes a first computing device; the device includes:

[0065] a determination module, configured to determine a random private key corresponding to each first private data in the first privacy set of the second computing device; and to hide the i-th first private data according to the i-th random private key to obtain the i-th blinded data;

[0066] A first sending module, configured to receive the i-th subscript data sent by the first computing device; and at the same time, send the i-th blinded data to the first computing device; wherein the i-th blinded data is used to obtain the i-th obfuscated data based on the oblivious transmission (OT) operation; and the i-th obfuscated data is used to generate a first hash value of each second private data in the second private set of the first computing device;

[0067] A second sending module is used to determine the second hash value of the i-th first privacy data; and send the second hash value to the first computing device; wherein each of the first hash value and the second hash value is used to generate an intersection; and the intersection includes the common privacy data between the first privacy set and the second privacy set.

[0068] In a possible implementation, the determination module is specifically used to: determine a target encryption algorithm, and generate a target pseudo-random function based on the target encryption algorithm; hide the i-th first privacy data according to the i-th random private key and the target pseudo-random function to obtain the i-th blinded data.

[0069] In a possible implementation, the determination module is specifically used to: generate the target pseudo-random function according to the target encryption algorithm and the key information of the target encryption algorithm; and at the same time, generate obfuscation parameter information; wherein the obfuscation parameter information includes a first obfuscation parameter and a second obfuscation parameter.

[0070] In a possible implementation, the determination module is further specifically used to: receive the public key parameters sent by the first computing device; and encrypt the key information and the obfuscation parameter information according to the public key parameters to obtain encrypted information; and send the encrypted information to the first computing device.

[0071] In a possible implementation, the determination module is further specifically used to: perform calculation processing on the i-th first privacy data according to the target pseudo-random function to obtain a calculation result of the i-th first privacy data; generate obfuscation parameter information; and obtain the i-th blinded data according to the obfuscation parameter information, the i-th random private key and the calculation result of the i-th first privacy data.

[0072] In a possible implementation, the determination module is further specifically used to: obtain a first blinded value in the i-th blinded data based on a first obfuscation parameter in the obfuscation parameter information, the i-th random private key, and a calculation result of the i-th first privacy data; and obtain a second blinded value in the i-th blinded data based on a second obfuscation parameter in the obfuscation parameter information, the i-th random private key, and a calculation result of the i-th first privacy data.

[0073] In a possible implementation manner, the first blinding value in the i-th blinding data Among them, k i is the i-th random private key, α 0 is the first confusion parameter, F k (y i ) is the calculation result of the i-th first privacy data; the second blinding value in the i-th blinding data Among them, α 1 is the second obfuscation parameter.

[0074] In a possible implementation, the determination module is further specifically used to: determine the target encryption algorithm based on data features corresponding to the first privacy set and the second privacy set; wherein the target encryption algorithm has encryption parameter information, and the encryption parameter information represents the parameter form of the target encryption algorithm.

[0075] In a fifth aspect, an embodiment of the present application provides a first computing device, including: a memory, a processor;

[0076] The memory stores computer-executable instructions;

[0077] The processor executes the computer-executable instructions stored in the memory, so that the processor performs the method described in the first aspect above.

[0078] In a sixth aspect, an embodiment of the present application provides a second computing device, including: a memory, a processor;

[0079] The memory stores computer-executable instructions;

[0080] The processor executes the computer-executable instructions stored in the memory, so that the processor performs the method described in the second aspect above.

[0081] In a seventh aspect, an embodiment of the present application provides a secure computing system, which includes a first computing device and a second computing device; the first computing device is used to implement the method described in the first aspect above; the second computing device is used to implement the method described in the second aspect.

[0082] In an eighth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer execution instructions, and when the computer execution instructions are executed by a processor, they are used to implement the method described in the first aspect and / or the second aspect above.

[0083] In a ninth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the method described in the first aspect and / or the second aspect above.

[0084] The privacy set intersection method, apparatus, device and system provided by the embodiments of the present application, through an oblivious transfer protocol, a first computing device sends the i-th subscript data to a second computing device, and the second computing device sends the i-th blinded data corresponding to the i-th first privacy data in the first privacy set of the second computing device to the first computing device, and through the oblivious transfer (OT) operation, the first computing device receives the i-th obfuscated data in the i-th blinded data for calculating the first hash value corresponding to each second privacy data in the second privacy set of the first computing device, and performs an intersection operation on each first hash value and the second hash value corresponding to the i-th first privacy data sent by the second computing device to obtain the common privacy data between the first privacy set and the second privacy set; further, the first computing device obtains the obfuscated data of the OT operation based on the subscript data sent by the second computing device through the subscript data, so as to operate on its own privacy data, so that the number of data transmissions is only related to the number of data in the privacy set, and is no longer related to the data form of the privacy data, thereby reducing the number of data interactions of the overall oblivious transfer protocol and improving communication efficiency and computing efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0085] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0086] Figure 1 A schematic diagram of an application scenario provided for this application;

[0087] Figure 2 A flowchart of a privacy set intersection method provided in an embodiment of the present application;

[0088] Figure 3 A flowchart of an OT operation process provided in an embodiment of the present application;

[0089] Figure 4 A flowchart of another privacy set intersection method provided in an embodiment of the present application;

[0090] Figure 5A flowchart of another privacy set intersection method provided in an embodiment of the present application;

[0091] Figure 6 A schematic diagram of a process for generating a pseudo-random function provided in an embodiment of the present application;

[0092] Figure 7 A schematic diagram of a nonlinear layer arrangement based on a symmetric cryptographic algorithm instantiation provided in an embodiment of the present application;

[0093] Figure 8 A flowchart of another privacy set intersection method provided in an embodiment of the present application;

[0094] Fig. 9 A schematic diagram of the structure of a privacy set intersection device provided in an embodiment of the present application;

[0095] Fig.10 A schematic diagram of the structure of a privacy set intersection device provided in an embodiment of the present application;

[0096] Fig.11 A schematic diagram of the structure of a first computing device provided in an embodiment of the present application;

[0097] Fig.12 A schematic diagram of the structure of a second computing device provided in an embodiment of the present application.

[0098] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0099] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0100] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, processing, transmission, provision, disclosure and application of the relevant data comply with relevant laws, regulations and standards, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0101] It should be noted that the privacy set intersection method, device, equipment and system of the present application can be used in the field of information security, and can also be used in any field other than information security. The application field of the privacy set intersection method, device, equipment and system of the present application is not limited.

[0102] Figure 1 A schematic diagram of an application scenario provided by this application. Figure 1 As shown, the specific application scenario of the present application includes a first computing device 101 and a second computing device 102. The first computing device 101 and the second computing device 102 perform intersection operations on each privacy data in the privacy sets of both parties through data interaction between the two parties to obtain the common privacy data in the privacy sets of both parties.

[0103] Privacy computing technology is a key technology to achieve "available but invisible" data. Among them, privacy set intersection is an important branch of secure multi-party computing. It allows data holding participants to obtain the intersection data between the privacy sets of each participant through calculation without leaking any data information other than the intersection data, such as user data or device data and other privacy data that needs to be protected.

[0104] In one example, a framework based on the public key cryptography system is designed, such as homomorphic encryption, which encrypts the elements and performs corresponding comparison operations on the ciphertext, and finally obtains the intersection of the two sets through private key decryption.

[0105] However, in the above method, the protocol based on the public key cryptography system has high computational overhead.

[0106] In another example, a framework based on public key cryptography is designed, such as homomorphic encryption, which encrypts elements and performs corresponding comparison operations on the ciphertext, and finally obtains the intersection of the two sets through private key decryption.

[0107] However, among the above methods, the protocol based on the confusion circuit has good versatility but low efficiency.

[0108] In another example, based on the oblivious transfer (OT) design framework, the classic OT protocol and pseudorandom function (PRF) are used to blind the elements of the set with random values ​​to achieve the effect of privacy protection, which requires a large number of OT operations.

[0109] However, in the above method, the number of OT operations in the privacy intersection protocol based on the OT protocol is related to the data bit length. The longer the data format is, the more OT protocols are performed and the communication overhead is very large, which affects the overall efficiency. Since the Advanced Encryption Standard (AES) algorithm is used for instantiation, the data format is relatively fixed. For other data type formats on the prime field that may appear in actual scenarios, preliminary processing is required to convert them into a format that conforms to the AES algorithm input, resulting in low computational efficiency.

[0110] In response to the above technical problems, the present application proposes the following technical concept: through the oblivious transmission protocol, the first computing device sends the i-th subscript data to the second computing device, and the second computing device sends the i-th blinded data corresponding to the i-th first privacy data in the first privacy set of the second computing device to the first computing device, and through the oblivious transmission OT operation, the first computing device receives the i-th obfuscated data in the i-th blinded data, which is used to calculate the first hash value corresponding to each second privacy data in the second privacy set of the first computing device, and performs an intersection operation on each first hash value and the second hash value corresponding to the i-th first privacy data sent by the second computing device, so as to obtain the common privacy data between the first privacy set and the second privacy set. In this way, it is possible to solve the problem in the prior art that the number of OT protocols performed is related to the data form by using the oblivious transmission method, and the longer the data form of each privacy set, the more times the OT protocol needs to be operated, resulting in an increase in the communication overhead required for the calculation process, affecting the overall calculation efficiency.

[0111] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0112] Figure 2 A flowchart of a privacy set intersection method provided in an embodiment of the present application is shown as follows: Figure 2 As shown, the method is applied to a first computing device in a secure computing system; the secure computing system also includes a second computing device, and the method includes:

[0113] 201. A first computing device generates at least one subscript data and sends the i-th subscript data to a second computing device; wherein the i-th subscript data is used to obtain the i-th obfuscated data; the i-th obfuscated data is a selection result based on an inadvertent transmission (OT) operation on the i-th blinded data; the i-th blinded data is obtained by processing the i-th first privacy data in the first privacy set of the second computing device.

[0114] For example, in a secure computing system, for a first computing device having a set X={x 1 ,…,x m}, the second computing device has a set Y = {y 1 ,…y n}, both parties perform privacy set intersection processing, and the first computing device generates a random subscript sequence, which includes at least one subscript data, such as W = {w 1 ,…,w n},w i ∈{0,1}, for each subscript data, in order, replace the i-th subscript data w i The first computing device sends the i-th subscript data to the second computing device. After the second computing device receives the i-th subscript data, it determines the i-th first private data from the privacy set of the second computing device, that is, the first privacy set, according to the sequence number i of the subscript data, and blinds the i-th first private data to obtain the i-th blinded data. The first computing device and the second computing device can perform an inadvertent transmission OT operation, that is, the first computing device sends the i-th subscript data to the second computing device based on the preset OT protocol, and the second computing device sends the i-th blinded data to the first computing device based on the preset OT protocol. Based on the OT operation of the OT protocol, the i-th obfuscated data is randomly selected from the i-th blinded data, and the first computing device receives the i-th obfuscated data.

[0115] For example, Figure 3 A flowchart of an OT operation process provided in an embodiment of the present application is shown in FIG. Figure 3 As shown, for each i, the first computing device and the second computing device complete an OT operation, such as a 2-choose-1-OT operation, where the input of the first computing device is the subscript data w i , the input of the second computing device is the blinded data After this OT operation, the first computing device obtains the selection result of the OT operation in the blinded data and the first computing device is unaware of the input of the second computing device The second computing device does not know which of the two data is obtained by the first computing device.

[0116] 202. The first computing device receives the i-th obfuscated data sent by the second computing device; and determines the first hash value of each second private data in the second privacy set according to the i-th obfuscated data and the second privacy set of the first computing device.

[0117] For example, in combination Figure 3 , based on the OT operation of the OT protocol, randomly select from the i-th blinded data to obtain the i-th obfuscated data, and the first computing device receives the i-th obfuscated data. The first computing device calculates and processes the i-th obfuscated data and each second private data based on the preset hash algorithm for its own privacy set, that is, each second private data in the second privacy set, to obtain the first hash value corresponding to each second private data in the second privacy set.

[0118] 203. The first computing device receives the second hash value of the i-th first private data sent by the second computing device, and determines an intersection according to the second hash value and each first hash value, wherein the intersection includes the private data common to the first privacy set and the second privacy set.

[0119] Exemplarily, the second computing device generates and sends the second hash value corresponding to its own i-th first private data to the first computing device based on the i-th obfuscated data. The first computing device receives the second hash value corresponding to the i-th first private data sent by the second computing device, and performs an intersection operation on the second hash value and all the first hash values ​​based on the intersection operation algorithm, so as to obtain the common private data between the first privacy set and the second privacy set, that is, the intersection.

[0120] In this embodiment, a privacy set intersection method is provided, in which a first computing device obtains obfuscated data of an OT operation based on the subscript data sent by a second computing device through subscript data, so as to perform operations on its own privacy data, so that the number of data transmissions is only related to the number of data in the privacy set and is no longer related to the data form of the privacy data, thereby reducing the number of data interactions of the overall oblivious transfer protocol and improving communication efficiency and computing efficiency.

[0121] Figure 4 A flowchart of another privacy set intersection method provided in an embodiment of the present application is shown as follows: Figure 4 As shown, the secure computing system includes a first computing device and a second computing device, and the method includes:

[0122] 301. The second computing device determines a random private key corresponding to each first privacy data in a first privacy set of the second computing device; and hides the i-th first privacy data according to the i-th random private key to obtain the i-th blinded data.

[0123] Exemplarily, the second computing device generates a random private key corresponding to each first privacy data for its own privacy set, that is, each first privacy data in the first privacy set, and blinds the i-th random private key and the i-th first privacy data based on a preset hiding algorithm or a blinding processing algorithm according to the order of each random private key to obtain the i-th blinded first privacy data, that is, the i-th blinded data.

[0124] For example, combined with Figure 3 , the second computing device constructs a random private key set K for intersection operation = {k 1 …k n}, in, is the finite field parameter of the operation algorithm, and the privacy set Y of the second computing device itself is 1 ,…y n}, each first private data has a corresponding random private key; for each first private data y i , through the blind processing algorithm, the i-th blind data is calculated To complete the y i of hiding.

[0125] 302. The first computing device generates at least one subscript data and sends the i-th subscript data to the second computing device; wherein the i-th subscript data is used to obtain the i-th obfuscated data; the i-th obfuscated data is a selection result based on the inadvertent transmission (OT) operation on the i-th blinded data; the i-th blinded data is obtained by processing the i-th first privacy data in the first privacy set of the second computing device.

[0126] Exemplarily, this step may refer to step 201 and will not be described in detail here.

[0127] 303. The second computing device receives the i-th subscript data sent by the first computing device; at the same time, sends the i-th blinded data to the first computing device; wherein the i-th blinded data is used to obtain the i-th obfuscated data based on the oblivious transmission (OT) operation; the i-th obfuscated data is used to generate the first hash value of each second privacy data in the second privacy set of the first computing device.

[0128] For example, in combination Figure 3 For each i, the first computing device and the second computing device complete an OT operation, where the input of the first computing device is the i-th index data w i , that is, the i-th subscript data w i Send to the second computing device, the input of the second computing device is the i-th blinded data The i-th blinded data Sent to the first computing device. After this OT operation, the first computing device obtains the selection result of the OT operation in the blinded data. and the first computing device is unaware of the input of the second computing device The second computing device does not know which of the two data the first computing device has obtained. After receiving the i-th obfuscated data, the first computing device calculates each second private data in the second privacy set of the first computing device according to the i-th obfuscated data to obtain a first hash value of each second private data.

[0129] 304. The first computing device receives the i-th obfuscated data sent by the second computing device; and determines the first hash value of each second privacy data in the second privacy set according to the i-th obfuscated data and the second privacy set of the first computing device.

[0130] Exemplarily, this step may refer to step 202 and will not be described in detail here.

[0131] 305. The second computing device determines a second hash value of the i-th first privacy data; and sends the second hash value to the first computing device; wherein each first hash value and the second hash value are used to generate an intersection; and the intersection includes the privacy data common to the first privacy set and the second privacy set.

[0132] For example, in combination Figure 3 The second computing device calculates each first privacy data based on a preset hash algorithm to obtain a second hash value of each first privacy data, and sends the second hash value of the i-th first privacy data to the first computing device, so that the first computing device can perform an intersection operation on the second hash value and the first hash value of each second privacy data in the first computing device to obtain the common privacy data between the first privacy set in the second computing device and the second privacy set in the first computing device.

[0133] 306. The first computing device receives the second hash value of the i-th first private data sent by the second computing device, and determines an intersection according to the second hash value and each first hash value; wherein the intersection includes the private data common to the first privacy set and the second privacy set.

[0134] Exemplarily, this step may refer to step 203 and will not be described in detail here.

[0135] In this embodiment, based on the above embodiment, after the i-th random index is sent to the second computing device through the first device, the second computing device generates the i-th blinded data according to the random private key corresponding to the i-th privacy data in its own privacy set and transmits it to the first computing device. The first computing device operates on its own privacy data according to the i-th obfuscated data obtained by performing an OT operation on the i-th blinded data, and further performs an intersection operation to obtain the intersection; the number of times data is transmitted is only related to the number of data in the privacy set, and is no longer related to the data form, thereby reducing the number of interactions between the two parties in the overall transmission protocol and improving communication efficiency and computing efficiency.

[0136] Figure 5 A flowchart of another privacy set intersection method provided in an embodiment of the present application is shown as follows: Figure 5 As shown, the secure computing system includes a first computing device and a second computing device, and the method includes:

[0137] 401. The second computing device determines a random private key corresponding to each first privacy data in a first privacy set of the second computing device; and hides the i-th first privacy data according to the i-th random private key to obtain the i-th blinded data.

[0138] Exemplarily, this step may refer to step 301 and will not be described in detail here.

[0139] 402. The first computing device generates at least one subscript data and sends the i-th subscript data to the second computing device; wherein the i-th subscript data is used to obtain the i-th obfuscated data; the i-th obfuscated data is a selection result based on the inadvertent transmission (OT) operation on the i-th blinded data; the i-th blinded data is obtained by processing the i-th first privacy data in the first privacy set of the second computing device.

[0140] Exemplarily, this step may refer to step 201 and will not be described in detail here.

[0141] 403. The second computing device receives the i-th subscript data sent by the first computing device; at the same time, sends the i-th blinded data to the first computing device; wherein the i-th blinded data is used to obtain the i-th obfuscated data based on the oblivious transmission (OT) operation; the i-th obfuscated data is used to generate the first hash value of each second privacy data in the second privacy set of the first computing device.

[0142] Exemplarily, this step may refer to step 303 and will not be described in detail here.

[0143] 404. The first computing device receives the i-th obfuscated data sent by the second computing device.

[0144] Exemplarily, this step may refer to step 202 and will not be described in detail here.

[0145] 405. The first computing device determines a target encryption algorithm.

[0146] For example, Figure 6 A schematic diagram of a pseudo-random function generation process provided in an embodiment of the present application is shown in FIG. Figure 6 As shown, the first computing device calls a preset encryption algorithm, such as a symmetric encryption algorithm, and determines the preset encryption algorithm as a target encryption algorithm.

[0147] In one example, step 405 includes: determining a target encryption algorithm according to data features corresponding to the first privacy set and the second privacy set; wherein the target encryption algorithm has encryption parameter information, and the encryption parameter information represents the parameter form of the target encryption algorithm.

[0148] Exemplarily, the first computing device or the second computing device or other third-party device can determine the data characteristics of each privacy data in the two privacy sets in advance based on the second privacy set of the first computing device and the first privacy set of the second computing device, such as data characteristics or data form. The first computing device can determine the target encryption algorithm corresponding to the data characteristic from multiple preset encryption algorithms based on the data characteristics; wherein the target encryption algorithm has encryption parameter information, and the encryption parameter information represents the parameter form of the target encryption algorithm. In order to obtain a PRF based on arithmetic operations, more emphasis is placed on arithmetic operations, such as operations on rings, finite fields, etc. and The calculation of the algorithm function is completed directly through the corresponding algebraic operation, and at the same time, the overall efficiency of the PRF operation is improved by reducing the number of multiplication operations in the algorithm. The symmetric cryptographic primitives designed based on this concept mainly include Low Multiplicative Complexity (LowMC), Minimal Multiplicative Complexity* (MiMC), Generalized Minimal Multiplicative Complexity (GMiMC), Hashing by Advanced Designs for Efficient and Secure Multiplicative Inverse Mixing Circuits (HADESMiMC), etc.

[0149] For example, combining Figure 6The first computing device selects the symmetric cryptographic MiMC algorithm according to the data characteristics of the privacy sets of the first computing device and the second computing device, and determines the parameter form of the MiMC algorithm, that is, determines the finite field q = p or 2 n , round number r, round constant c i etc., where the MiMC algorithm is based on a finite field Design, q is p or 2 n , gcd(3,p-1)=1, and its nonlinear operation is F(x)=x 3 , the round function of each round is F i (x) = (x + k + c i ) 3 The entire encryption algorithm is k is the key, r is the number of rounds, c i is the wheel constant.

[0150] 406. The first computing device generates a target pseudo-random function according to a target encryption algorithm.

[0151] Exemplarily, the first computing device can generate the currently required target pseudo-random function (Pseudorandom Function, PRF for short) for data blinding or obfuscation processing by instantiating the determined target encryption algorithm in combination with a preset pseudo-random function form.

[0152] In one example, step 406 includes the following steps:

[0153] The first step of step 406 is to determine the public key parameters and the private key parameters; and send the public key parameters to the second computing device; wherein the public key parameters are used to generate encryption information, and the encryption information includes obfuscation parameter information and key information of the target encryption algorithm.

[0154] The second step of step 406 is to receive the encrypted information sent by the second computing device; and decrypt the encrypted information according to the private key parameters to obtain the obfuscation parameter information and the key information of the target encryption algorithm.

[0155] The third step of step 406 is to generate a target pseudo-random function according to the key information, the obfuscation parameter information and the target encryption algorithm.

[0156] For example, in combination Figure 6 The first computing device generates a public key parameter and a private key parameter (Pk, Sk) based on a preset public key cryptographic algorithm, and sends the public key parameter Pk to the second computing device; the second computing device encrypts the key information and obfuscation parameter information generated by itself according to the public key parameter Pk to obtain encrypted information, which includes the obfuscation parameter information α0 ,α 1 and the key information k of the target encryption algorithm MiMC The first computing device receives the encrypted information sent by the second computing device, and decrypts the encrypted information according to the private key parameters and the decryption algorithm to obtain the obfuscation parameter information α. 0 ,α 1 and the key information k of the target encryption algorithm MiMC The first computing device calculates the target encryption algorithm according to the determined target encryption algorithm and combines the preset pseudo-random function form and the key information k MiMC , obfuscated parameter information α 0 ,α 1 By instantiating it, the target pseudo-random function currently required can be generated for data blinding or obfuscation.

[0157] In one example, the third step of step 406 includes: generating a target pseudo-random function based on key information, obfuscation parameter information, a target encryption algorithm, and encryption parameter information of the target encryption algorithm; wherein the encryption parameter information represents the parameter form of the target encryption algorithm.

[0158] Specifically, the first computing device obtains encryption parameter information of the target encryption algorithm according to the determined target encryption algorithm, that is, the parameter form characterizing the target encryption algorithm, and calculates the encryption parameter information of the target encryption algorithm according to the determined target encryption algorithm and the encryption parameter information of the target encryption algorithm, and in combination with the preset pseudo-random function form and the key information k MiMC , obfuscated parameter information α 0 ,α 1 By instantiating it, the target pseudo-random function currently required can be generated for data blinding or obfuscation.

[0159] For example, for the target encryption algorithm, the symmetric encryption algorithm MiMC algorithm, determine the finite field q = p or 2 n , round number r, round constant c i Etc., according to the key information k MiMC , obfuscated parameter information α 0 ,α 1 , the pseudo-random function PRF can be expressed as where f i (x) = (x + k MiMC +c i ) 3 .

[0160] For example, Figure 7 A schematic diagram of a nonlinear layer arrangement based on a symmetric cryptographic algorithm instantiation provided in an embodiment of the present application, such as Figure 7 As shown, taking the instantiation process of HADESMiMC as an example, it is designed based on the finite field Fp; the overall algorithm can be expressed as: The round function of each round can be expressed as: Fk(·) = k + M × S(·); k is the key, M is the linear layer (linear transformation); S is the non - linear layer (non - linear operation), and it is set as S(x) = x 3 More generally, it can be set as S(x) = x α , where α satisfies gcd(p - 1, α) = 1, and α is adjusted to adapt to different data situations; the algorithm structure feature is: by improving the classical non - linear layer structure, applying full S - boxes in some function rounds, only applying 1 S - box in some function rounds, and not applying S - boxes in the remaining parts. That is, when not applying S - boxes in some function rounds, the non - linear part of the corresponding part of the data remains unchanged, reducing the number of non - linear operations in the overall algorithm. In the <PRF generation link> of both parties, the implementation steps of PRF generation are general, and mainly differ in the content of the PRF parameters to be secretly negotiated.

[0161] 407. The first computing device determines the first hash value of each second privacy data according to the i - th obfuscated data, the target pseudo - random function, and each second privacy data.

[0162] Exemplarily, in order to further enhance data security, the first computing device performs a hash calculation on the obtained i - th obfuscated data, the target pseudo - random function, and each second privacy data among each second privacy data to obtain the first hash value of each second privacy data.

[0163] In one example, step 407 includes the following steps:

[0164] The first step of step 407, according to the i - th obfuscated data, the target pseudo - random function, and the second privacy data, determines the comparison data corresponding to the second privacy data.

[0165] The second step of step 407, performs a hash operation on the comparison data to obtain the first hash value of the second privacy data.

[0166] Exemplarily, the first computing device calculates the obtained i - th obfuscated data, the target pseudo - random function, and each second privacy data based on a preset algorithm to obtain the comparison data corresponding to each second privacy data and then obtains the comparison set corresponding to all second privacy data and performs a hash operation on the comparison data corresponding to each second privacy data based on a preset hash algorithm to obtain the first hash value of each second privacy data

[0167] In one example, the first step of step 407 includes:

[0168] Step 1: Calculate and process the j-th second private data according to the target pseudo-random function to obtain a calculation result corresponding to the j-th second private data.

[0169] Step 2: Determine the comparison data corresponding to the j-th second private data based on the calculation result corresponding to the j-th second private data, the i-th obfuscated data and the target obfuscation parameter; wherein the target obfuscation parameter is the obfuscation parameter corresponding to the i-th obfuscated data in the obfuscation parameter information sent by the second computing device.

[0170] Among them, the comparison data corresponding to the j-th second private data in, is the i-th obfuscated data, is the target confusion parameter, F k (x j ) is the calculation result corresponding to the j-th second privacy data.

[0171] Specifically, combined Figure 3 The first computing device performs computational processing on each second private data, i.e., the j-th second private data, according to the computational form of the target pseudo-random function, and obtains a computational result F corresponding to the j-th second private data. k (x j ), according to the obtained i-th obfuscated data, determine the obfuscation parameter corresponding to the i-th obfuscated data in the obfuscation parameter information sent by the second computing device, that is, the target obfuscation parameter, and calculate the calculation result F corresponding to the j-th second private data based on the preset algorithm. k (x j ), the i-th obfuscated data and the target obfuscation parameter are calculated to obtain the comparison data corresponding to the j-th second private data Among them, the formula For the i-th obfuscated data Target obfuscation parameters And the calculation result F corresponding to the j-th second private data k (x j ) is calculated and processed to obtain the comparison data corresponding to the j-th second privacy data

[0172] 408. The second computing device determines a second hash value of the i-th first private data; and sends the second hash value to the first computing device; wherein each first hash value and the second hash value are used to generate an intersection; and the intersection includes the private data common to the first privacy set and the second privacy set.

[0173] Exemplarily, this step may refer to step 305 and will not be described in detail here.

[0174] 409. The first computing device receives the second hash value of the i-th first private data sent by the second computing device; and if it is determined that the first hash value corresponding to the j-th second private data among the first hash values ​​is equal to the second hash value, then the j-th second private data is determined to be the public private data in the intersection.

[0175] For example, in combination Figure 3 The first computing device receives the second hash value of the i-th first private data sent by the second computing device, and for each first hash value and the second hash value H(k i ),Compare With H(k i ), if there exists j such that Then there is x j =y i , which is the common element of sets X and Y. After completing the above comparison for all elements in Y, we can get the common elements of both sets, that is, the intersection of the two sets. It is worth noting that if x j =y i , then F k (x j )=F k (y i ), corresponding to With k i Equal, then If x j ≠y i , according to the PRF property F k (x j )≠F k (y i ), At this time, non-intersection elements will be excluded. Since the first computing device does not know the random private key k i , when y i If it is not in the set X, it cannot be obtained through And the hash value H(k i ) to infer the element y i The original value of the first computing device is used to ensure that information other than the intersection element is not leaked to the other party. The second computing device cannot know the additional information of the non-intersection in set X, which meets the requirement of privacy intersection.

[0176] For example, taking user data as an example, 18-bit data is converted into 2 60Traditionally, information hiding for a single bit through OT requires about 60 OT interactions, which has a very large communication overhead. Algebraic operations are performed in the form of its own data. Only a pair of blinding parameters needs to be introduced, and information hiding can be completed through one OT, which reduces the number of communication interactions and the online computing overhead. On the other hand, since the blinding operation is also performed on the finite field Fp, it will increase some local computing overhead.

[0177] In this embodiment, on the basis of the above-mentioned embodiments, a PRF is formed by deriving from a symmetric cryptographic algorithm designed based on parameters such as finite fields. The advantage of this type of algorithm is that it can adapt to richer data formats and reduce data processing costs. At the same time, its design has fewer multiplication operations and can achieve higher computing efficiency than the existing PRF instantiated based on AES.

[0178] Figure 8 A flowchart of another privacy set intersection method provided in an embodiment of the present application is shown as follows: Figure 8 As shown, the secure computing system includes a first computing device and a second computing device, and the method includes:

[0179] 501. A second computing device determines a random private key corresponding to each first privacy data in a first privacy set of the second computing device.

[0180] Exemplarily, this step may refer to step 301 and will not be described in detail here.

[0181] 502. The second computing device determines a target encryption algorithm.

[0182] For example, in combination Figure 6 , the second computing device calls a preset encryption algorithm, such as a symmetric encryption algorithm, and determines the preset encryption algorithm as a target encryption algorithm.

[0183] In one example, step 502 includes the following steps: determining a target encryption algorithm based on data features corresponding to the first privacy set and the second privacy set; wherein the target encryption algorithm has encryption parameter information, and the encryption parameter information represents the parameter form of the target encryption algorithm.

[0184] For example, in combination Figure 6 The first computing device or the second computing device or other third-party device can determine the data characteristics of each privacy data in the two privacy sets in advance based on the second privacy set of the first computing device and the first privacy set of the second computing device, such as data characteristics or data form. The second computing device can determine the target encryption algorithm corresponding to the data characteristic from multiple preset encryption algorithms based on the data characteristic; wherein the target encryption algorithm has encryption parameter information, and the encryption parameter information represents the parameter form of the target encryption algorithm.

[0185] 503. The second computing device generates a target pseudo-random function according to a target encryption algorithm.

[0186] Exemplarily, the first computing device can generate the currently required target pseudo-random function PRF for data blinding or obfuscation processing by instantiating the determined target encryption algorithm in combination with a preset pseudo-random function form.

[0187] In one example, step 503 includes the following steps: generating a target pseudo-random function according to a target encryption algorithm and key information of the target encryption algorithm; and generating obfuscation parameter information at the same time; wherein the obfuscation parameter information includes a first obfuscation parameter and a second obfuscation parameter.

[0188] Exemplarily, the second computing device generates key information k of the target encryption algorithm according to the determined target encryption algorithm. MiMC , and based on the determined target encryption algorithm, combined with the preset pseudo-random function form and key information k MiMC By instantiating, the target pseudo-random function currently required can be generated for data blinding or obfuscation processing; at the same time, based on the determined target pseudo-random function, the obfuscation parameter information is determined; wherein; the obfuscation parameter information includes the first obfuscation parameter α 0 and the second confusion parameter α 1 .

[0189] In one example, step 503 further includes:

[0190] Step 1: Receive the public key parameters sent by the first computing device; and encrypt the key information and the obfuscation parameter information according to the public key parameters to obtain encrypted information.

[0191] Step 2: Send the encrypted information to the first computing device.

[0192] Specifically, combined Figure 6 , the first computing device generates a public key parameter and a private key parameter of a preset public key cryptographic algorithm, and sends the public key parameter Pk to the second computing device, the second computing device receives the public key parameter sent by the first computing device, and according to the public key parameter, generates the generated obfuscated parameter information α 0 ,α 1 And the key information k MiMC The encrypted information is encrypted and transmitted to the first computing device, so that the first computing device uses the private key parameter to decrypt and obtain the key information k MiMC And confusion parameter information α 0 ,α 1 , to complete the generation of the PRF of the first computing device.

[0193] 504. The second computing device performs hiding processing on the i-th first private data according to the i-th random private key and the target pseudo-random function to obtain the i-th blinded data.

[0194] Exemplarily, the second computing device performs hiding processing on the i-th first privacy data based on a preset hiding algorithm and in combination with the generated i-th random private key and the determined target pseudo-random function to obtain the i-th blinded data.

[0195] In one example, step 504 includes the following steps:

[0196] The first step of step 504 is to perform calculation processing on the i-th first private data according to the target pseudo-random function to obtain the calculation result of the i-th first private data.

[0197] The second step of step 504 is to generate obfuscation parameter information; and obtain the i-th blinded data according to the obfuscation parameter information, the i-th random private key and the calculation result of the i-th first privacy data.

[0198] Exemplarily, the first computing device performs PRF calculation processing on the i-th first privacy data according to the determined target pseudo-random function to obtain the calculation result of the i-th first privacy data; and determines the obfuscation parameter information according to the target pseudo-random function, and based on the preset hiding algorithm, performs calculation processing on the obtained obfuscation parameter information, the i-th random private key, and the calculation result of the i-th first privacy data to obtain the i-th blinded data.

[0199] In one example, the second step of step 504 includes:

[0200] Step 1: Obtain a first blinding value in the i-th blinded data according to the calculation result of the first obfuscation parameter in the obfuscation parameter information, the i-th random private key, and the i-th first privacy data.

[0201] Step 2: Obtain a second blinding value in the i-th blinded data according to the calculation result of the second obfuscation parameter in the obfuscation parameter information, the i-th random private key, and the i-th first privacy data.

[0202] Among them, the first blinding value in the i-th blinding data Among them, k i is the i-th random private key, α 0 is the first confusion parameter, F k (y i ) is the calculation result of the i-th first private data; the second blinding value in the i-th blinding data Among them, α 1 is the second obfuscation parameter.

[0203] Specifically, combined Figure 3 , the obfuscation parameter information generated in the second computing device includes the first obfuscation parameter and the second obfuscation parameter. Based on the preset hiding algorithm, the calculation results of the first obfuscation parameter, the i-th random private key and the i-th first privacy data are calculated and processed to obtain the first blinded value in the i-th blinded data; wherein, the formula Calculate the first blind value in the i-th blind data Among them, k i is the i-th random private key, α 0 is the first confusion parameter, F k (y i ) is the calculation result of the i-th first private data; at the same time, the second computing device calculates and processes the second obfuscation parameter, the i-th random private key and the calculation result of the i-th first private data based on the preset hiding algorithm to obtain the second blinding value in the i-th blinding data; wherein, the formula Calculate the second blind value in the i-th blind data Among them, α 1 is the second obfuscation parameter.

[0204] 505. The first computing device generates at least one subscript data and sends the i-th subscript data to the second computing device; wherein the i-th subscript data is used to obtain the i-th obfuscated data; the i-th obfuscated data is a selection result based on the oblivious transmission (OT) operation on the i-th blinded data; the i-th blinded data is obtained by processing the i-th first privacy data in the first privacy set of the second computing device.

[0205] Exemplarily, this step may refer to step 201 and will not be described in detail here.

[0206] 506. The second computing device receives the i-th subscript data sent by the first computing device; at the same time, sends the i-th blinded data to the first computing device; wherein the i-th blinded data is used to obtain the i-th obfuscated data based on the oblivious transmission (OT) operation; the i-th obfuscated data is used to generate the first hash value of each second privacy data in the second privacy set of the first computing device.

[0207] Exemplarily, this step may refer to step 303 and will not be described in detail here.

[0208] 507. The second computing device determines the second hash value of the i-th first privacy data; and sends the second hash value to the first computing device; wherein each first hash value and the second hash value are used to generate an intersection; and the intersection includes the common privacy data between the first privacy set and the second privacy set.

[0209] Exemplarily, this step may refer to step 303 and will not be described in detail here.

[0210] 508. The first computing device receives the i-th obfuscated data sent by the second computing device; and determines a first hash value of each second private data in the second privacy set according to the i-th obfuscated data and the second privacy set of the first computing device.

[0211] Exemplarily, this step may refer to step 202 and will not be described in detail here.

[0212] 509. The first computing device receives the second hash value of the i-th first privacy data sent by the second computing device, and determines an intersection according to the second hash value and each first hash value; wherein the intersection includes the privacy data common to the first privacy set and the second privacy set.

[0213] Exemplarily, this step may refer to step 203 and will not be described in detail here.

[0214] In this embodiment, based on the above embodiment, the second computing device constructs a new data random blinding method based on the PRF characteristics, so that for each blinded data to be transmitted, the first computing device only needs to use 2-to-1-OT once to obtain the corresponding value, thereby constructing a new matching data calculation method, which can assist in completing the comparison of the corresponding privacy data, thereby reducing the number of interactions between the two parties in the overall protocol and improving the efficiency of calculation and communication.

[0215] Fig. 9 A schematic diagram of a privacy set intersection device provided in an embodiment of the present application is shown in FIG. Fig. 9 As shown, the apparatus is applied to a first computing device in a secure computing system; the secure computing system also includes a second computing device; the apparatus includes:

[0216] The sending module 601 is used to generate at least one subscript data and send the i-th subscript data to the second computing device; wherein the i-th subscript data is used to obtain the i-th obfuscated data; the i-th obfuscated data is a selection result based on the inadvertent transmission (OT) operation on the i-th blinded data; the i-th blinded data is obtained by processing the i-th first private data in the first privacy set of the second computing device;

[0217] A first determination module 602 is configured to receive the i-th obfuscated data sent by the second computing device; and determine a first hash value of each second private data in the second private set according to the i-th obfuscated data and the second private set of the first computing device;

[0218] The second determination module 603 is used to receive the second hash value of the i-th first privacy data sent by the second computing device; and determine the intersection according to the second hash value and each first hash value; wherein the intersection includes the common privacy data between the first privacy set and the second privacy set.

[0219] In one possible implementation, the first determination module 602 is specifically used to: determine a target encryption algorithm; and generate a target pseudo-random function based on the target encryption algorithm; and determine a first hash value of each second privacy data based on the i-th obfuscated data, the target pseudo-random function and each second privacy data.

[0220] In one possible implementation, the first determination module 602 is specifically used to: determine public key parameters and private key parameters; and send the public key parameters to a second computing device; wherein the public key parameters are used to generate encrypted information, the encrypted information including obfuscation parameter information and key information of a target encryption algorithm; receive the encrypted information sent by the second computing device; and decrypt the encrypted information according to the private key parameters to obtain obfuscation parameter information and key information of the target encryption algorithm; generate a target pseudo-random function according to the key information, obfuscation parameter information and the target encryption algorithm.

[0221] In a possible implementation, the first determination module 602 is further specifically used to generate a target pseudo-random function based on key information, obfuscation parameter information, a target encryption algorithm, and encryption parameter information of the target encryption algorithm; wherein the encryption parameter information represents the parameter form of the target encryption algorithm.

[0222] In a possible implementation, the first determination module 602 is further specifically used to: determine the comparison data corresponding to the second private data based on the i-th obfuscated data, the target pseudo-random function and the second private data; and perform a hash operation on the comparison data to obtain a first hash value of the second private data.

[0223] In a possible implementation, the first determination module 602 is further specifically used to: perform calculation processing on the j-th second privacy data according to a target pseudo-random function to obtain a calculation result corresponding to the j-th second privacy data; determine the comparison data corresponding to the j-th second privacy data according to the calculation result corresponding to the j-th second privacy data, the ith obfuscation data and a target obfuscation parameter; wherein the target obfuscation parameter is an obfuscation parameter corresponding to the ith obfuscated data in the obfuscation parameter information sent by the second computing device.

[0224] In a possible implementation manner, the comparison data corresponding to the j-th second private data in, is the i-th obfuscated data, is the target confusion parameter, Fk (x j ) is the calculation result corresponding to the j-th second privacy data.

[0225] In a possible implementation, the first determination module 602 is further specifically used to: determine a target encryption algorithm based on data features corresponding to the first privacy set and the second privacy set; wherein the target encryption algorithm has encryption parameter information, and the encryption parameter information represents the parameter form of the target encryption algorithm.

[0226] In a possible implementation, the second determination module 603 is specifically configured to: if it is determined that among the first hash values, the first hash value corresponding to the j-th second private data is equal to the second hash value, determine that the j-th second private data is the public private data in the intersection.

[0227] The device of this embodiment can execute the technical solution in the above method. Its specific implementation process and technical principles are the same and will not be repeated here.

[0228] Fig.10 A schematic diagram of a privacy set intersection device provided in an embodiment of the present application is shown in FIG. Fig.10 As shown, the apparatus is applied to a second computing device in a secure computing system; the secure computing system also includes a first computing device; the apparatus includes:

[0229] The determination module 701 is used to determine the random private key corresponding to each first private data in the first private set of the second computing device; and hide the i-th first private data according to the i-th random private key to obtain the i-th blinded data;

[0230] The first sending module 702 is used to receive the i-th subscript data sent by the first computing device; at the same time, send the i-th blinded data to the first computing device; wherein the i-th blinded data is used to obtain the i-th obfuscated data based on the oblivious transmission (OT) operation; the i-th obfuscated data is used to generate a first hash value of each second private data in the second private set of the first computing device;

[0231] The second sending module 703 is used to determine the second hash value of the i-th first privacy data; and send the second hash value to the first computing device; wherein the first hash value and each second hash value are used to generate an intersection; and the intersection includes the common privacy data between the first privacy set and the second privacy set.

[0232] In a possible implementation, the determination module 701 is specifically used to: determine a target encryption algorithm, and generate a target pseudo-random function based on the target encryption algorithm; hide the i-th first privacy data according to the i-th random private key and the target pseudo-random function to obtain the i-th blinded data.

[0233] In a possible implementation, the determination module 701 is specifically used to: generate a target pseudo-random function according to a target encryption algorithm and key information of the target encryption algorithm; and at the same time, generate obfuscation parameter information; wherein the obfuscation parameter information includes a first obfuscation parameter and a second obfuscation parameter.

[0234] In a possible implementation, the determination module 701 is further specifically used to: receive a public key parameter sent by the first computing device; and encrypt the key information and the obfuscation parameter information according to the public key parameter to obtain encrypted information; and send the encrypted information to the first computing device.

[0235] In a possible implementation, the determination module 701 is further specifically used to: perform calculation processing on the i-th first privacy data according to the target pseudo-random function to obtain the calculation result of the i-th first privacy data; generate obfuscation parameter information; and obtain the i-th blinded data according to the obfuscation parameter information, the i-th random private key and the calculation result of the i-th first privacy data.

[0236] In a possible implementation, the determination module 701 is further specifically used to: obtain a first blinded value in the i-th blinded data based on the calculation result of the first obfuscation parameter in the obfuscation parameter information, the i-th random private key, and the i-th first privacy data; obtain a second blinded value in the i-th blinded data based on the calculation result of the second obfuscation parameter in the obfuscation parameter information, the i-th random private key, and the i-th first privacy data.

[0237] In a possible implementation, the first blinding value in the i-th blinding data Among them, k i is the i-th random private key, α 0 is the first confusion parameter, F k (y i ) is the calculation result of the i-th first private data; the second blinding value in the i-th blinding data Among them, α 1 is the second obfuscation parameter.

[0238] In a possible implementation, the determination module 701 is further specifically used to: determine a target encryption algorithm based on data features corresponding to the first privacy set and the second privacy set; wherein the target encryption algorithm has encryption parameter information, and the encryption parameter information represents the parameter form of the target encryption algorithm.

[0239] The device of this embodiment can execute the technical solution in the above method. Its specific implementation process and technical principles are the same and will not be repeated here.

[0240] Fig.11A schematic diagram of the structure of a first computing device provided in an embodiment of the present application is shown in FIG. Fig.11 As shown, the first computing device includes: a memory 801 and a processor 802; the memory 801 is a memory for storing instructions executable by the processor 802.

[0241] The processor 802 is configured to execute the method provided in the above embodiment.

[0242] The first computing device further includes a receiver 803 and a transmitter 804. The receiver 803 is used to receive instructions and data sent by other devices, and the transmitter 804 is used to send instructions and data to external devices.

[0243] The specific implementation process of the processor can be found in the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be repeated here.

[0244] Fig.12 A schematic diagram of the structure of a second computing device provided in an embodiment of the present application is shown in FIG. Fig.12 As shown, the second computing device includes: a memory 901 and a processor 902; the memory 901 is a memory for storing instructions executable by the processor 902.

[0245] The processor 902 is configured to execute the method provided in the above embodiment.

[0246] The second computing device further includes a receiver 903 and a transmitter 904. The receiver 903 is used to receive instructions and data sent by other devices, and the transmitter 904 is used to send instructions and data to external devices.

[0247] The specific implementation process of the processor can be found in the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be repeated here.

[0248] In the above embodiments, it should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the invention may be directly implemented as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.

[0249] The memory may include a high-speed memory (Random Access Memory, referred to as RAM), and may also include a non-volatile memory (Non-volatile Memory, referred to as NVM), such as at least one disk memory.

[0250] An embodiment of the present application provides a secure computing system, which includes a first computing device and a second computing device; the first computing device and the second computing device are both used to execute the technical solution of the processing method in the above embodiment.

[0251] An embodiment of the present application also provides a chip for executing instructions, which is used to execute the technical solution of the processing method in the above embodiment.

[0252] The embodiment of the present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed on a computer, the computer executes the technical solution of the processing method of the above embodiment.

[0253] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory, electrically erasable programmable read-only memory, erasable programmable read-only memory, programmable read-only memory, read-only memory, magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special-purpose computer.

[0254] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be an integral part of the processor. The processor and the readable storage medium can be located in a dedicated integrated circuit. Of course, the processor and the readable storage medium can also exist in a device as discrete components.

[0255] An embodiment of the present application also provides a computer program product, which includes a computer program stored in a computer-readable storage medium. At least one processor can read the computer program from the computer-readable storage medium. When at least one processor executes the computer program, the technical solution of the processing method in the above embodiment can be implemented.

[0256] Those skilled in the art will appreciate that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware associated with program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed.

[0257] Finally, it should be noted that those skilled in the art will readily conceive of other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention, which follow the general principles of the present invention and include common knowledge or customary technical means in the art not disclosed by the present invention, are not limited to the precise structure described above and shown in the drawings, and may be modified and changed in various ways without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A method for finding the intersection of private sets, characterized in that: The method is applied to a first computing device in a secure computing system; The secure computing system further includes a second computing device; and the method includes: Generate at least one subscript data, and send the i-th subscript data to the second computing device; wherein the i-th subscript data is used to obtain the i-th obfuscated data; the i-th obfuscated data is a selection result based on the oblivious transmission (OT) operation on the i-th blinded data; the i-th blinded data is obtained by processing the i-th first private data in the first privacy set of the second computing device; receiving the i-th obfuscated data sent by the second computing device; and determining, according to the i-th obfuscated data and the second privacy set of the first computing device, a first hash value of each second privacy data in the second privacy set; Receive the second hash value of the i-th first privacy data sent by the second computing device; and determine an intersection according to the second hash value and each of the first hash values; wherein the intersection includes the privacy data common to the first privacy set and the second privacy set.

2. The method according to claim 1, characterized in that Determining, according to the i-th obfuscated data and the second privacy set of the first computing device, a first hash value of each second privacy data in the second privacy set, comprising: Determining a target encryption algorithm; and generating a target pseudo-random function according to the target encryption algorithm; Determine a first hash value of each second private data according to the i-th obfuscated data, the target pseudo-random function and each second private data.

3. The method according to claim 2, characterized in that Generating a target pseudo-random function according to the target encryption algorithm includes: Determine a public key parameter and a private key parameter; and send the public key parameter to the second computing device; wherein the public key parameter is used to generate encryption information, and the encryption information includes obfuscation parameter information and key information of the target encryption algorithm; receiving the encrypted information sent by the second computing device; and decrypting the encrypted information according to the private key parameter to obtain obfuscation parameter information and key information of the target encryption algorithm; The target pseudo-random function is generated according to the key information, the obfuscation parameter information and the target encryption algorithm.

4. The method according to claim 3, characterized in that Generating the target pseudo-random function according to the key information, the obfuscation parameter information and the target encryption algorithm includes: The target pseudo-random function is generated according to the key information, the obfuscation parameter information, the target encryption algorithm and the encryption parameter information of the target encryption algorithm; wherein the encryption parameter information represents the parameter form of the target encryption algorithm.

5. The method according to claim 2, characterized in that: Determining a first hash value of each second private data according to the i-th obfuscated data, the target pseudo-random function, and each second private data includes: Determining, according to the i-th obfuscated data, the target pseudo-random function and the second private data, comparison data corresponding to the second private data; A hash operation is performed on the comparison data to obtain a first hash value of the second private data.

6. The method according to claim 5, characterized in that Determining, according to the i-th obfuscated data, the target pseudo-random function, and the second private data, comparison data corresponding to the second private data, comprising: Performing calculation processing on the j-th second private data according to the target pseudo-random function to obtain a calculation result corresponding to the j-th second private data; Determine the comparison data corresponding to the j-th second privacy data according to the calculation result corresponding to the j-th second privacy data, the i-th obfuscation data and the target obfuscation parameter; wherein the target obfuscation parameter is the obfuscation parameter corresponding to the i-th obfuscation data in the obfuscation parameter information sent by the second computing device.

7. The method according to claim 6, characterized in that The comparison data corresponding to the j-th second private data in, is the i-th obfuscated data, is the target confusion parameter, F k (x j ) is the calculation result corresponding to the j-th second privacy data.

8. The method according to claim 2, characterized in that: Determine the target encryption algorithm, including: The target encryption algorithm is determined according to data features corresponding to the first privacy set and the second privacy set; wherein the target encryption algorithm has encryption parameter information, and the encryption parameter information represents the parameter form of the target encryption algorithm.

9. The method according to any one of claims 1 to 8, characterized in that Determining an intersection according to the second Hash value and each of the first Hash values ​​includes: If it is determined that among the first hash values ​​there is a first hash value corresponding to the j-th second private data which is equal to the second hash value, then the j-th second private data is determined to be the public private data in the intersection.

10. A method for finding intersection of private sets, characterized in that: The method is applied to a second computing device in a secure computing system; the secure computing system also includes a first computing device; the method includes: Determine a random private key corresponding to each first private data in the first privacy set of the second computing device; and hide the i-th first private data according to the i-th random private key to obtain the i-th blinded data; Receive the i-th subscript data sent by the first computing device; at the same time, send the i-th blinded data to the first computing device; wherein the i-th blinded data is used to obtain the i-th obfuscated data based on the oblivious transmission (OT) operation; the i-th obfuscated data is used to generate a first hash value of each second private data in the second private set of the first computing device; Determine a second hash value of the i-th first privacy data; and send the second hash value to the first computing device; wherein each of the first hash value and the second hash value is used to generate an intersection; and the intersection includes the privacy data common to the first privacy set and the second privacy set.

11. The method according to claim 10, characterized in that According to the i-th random private key, the i-th first private data is hidden to obtain the i-th blinded data, including: Determining a target encryption algorithm, and generating a target pseudo-random function according to the target encryption algorithm; The i-th first private data is hidden according to the i-th random private key and the target pseudo-random function to obtain the i-th blinded data.

12. The method according to claim 11, characterized in that Generating a target pseudo-random function according to the target encryption algorithm includes: The target pseudo-random function is generated according to the target encryption algorithm and the key information of the target encryption algorithm; at the same time, obfuscation parameter information is generated; wherein the obfuscation parameter information includes a first obfuscation parameter and a second obfuscation parameter.

13. The method according to claim 12, characterized in that The method further comprises: receiving the public key parameters sent by the first computing device; and encrypting the key information and the obfuscation parameter information according to the public key parameters to obtain encrypted information; The encrypted information is sent to the first computing device.

14. The method according to claim 11, characterized in that According to the i-th random private key and the target pseudo-random function, the i-th first private data is hidden to obtain the i-th blinded data, including: Performing calculation processing on the i-th first private data according to the target pseudo-random function to obtain a calculation result of the i-th first private data; Generate obfuscation parameter information; and obtain the i-th blinded data according to the obfuscation parameter information, the i-th random private key and the calculation result of the i-th first privacy data.

15. The method according to claim 14, characterized in that Obtaining the i-th blinded data according to the obfuscation parameter information, the i-th random private key, and the calculation result of the i-th first private data, including: Obtaining a first blinding value in the i-th blinded data according to a calculation result of the first obfuscation parameter in the obfuscation parameter information, the i-th random private key, and the i-th first private data; A second blinding value in the i-th blinded data is obtained according to a calculation result of a second obfuscation parameter in the obfuscation parameter information, the i-th random private key, and the i-th first privacy data.

16. The method according to claim 15, characterized in that The first blinding value in the i-th blinding data Among them, k i is the i-th random private key, α0 is the first obfuscation parameter, F k (y i ) is the calculation result of the i-th first privacy data; The second blinding value in the i-th blinding data Wherein, α1 is the second confusion parameter.

17. The method according to claim 11, characterized in that Determine the target encryption algorithm, including: The target encryption algorithm is determined according to data features corresponding to the first privacy set and the second privacy set; wherein the target encryption algorithm has encryption parameter information, and the encryption parameter information represents the parameter form of the target encryption algorithm.

18. A privacy set intersection device, characterized in that: The apparatus is applied to a first computing device in a secure computing system; The secure computing system further includes a second computing device; the apparatus includes: A sending module, configured to generate at least one subscript data, and send the i-th subscript data to the second computing device; wherein the i-th subscript data is used to obtain the i-th obfuscated data; the i-th obfuscated data is a selection result based on the oblivious transmission (OT) operation performed on the i-th blinded data; the i-th blinded data is obtained by processing the i-th first private data in the first privacy set of the second computing device; A first determination module, configured to receive the i-th obfuscated data sent by the second computing device; and determine a first hash value of each second private data in the second private set according to the i-th obfuscated data and the second private set of the first computing device; The second determination module is used to receive the second hash value of the i-th first privacy data sent by the second computing device; and determine the intersection according to the second hash value and each of the first hash values; wherein the intersection includes the privacy data common between the first privacy set and the second privacy set.

19. A privacy set intersection device, characterized in that: The apparatus is applied to a second computing device in a secure computing system; the secure computing system also includes a first computing device; the apparatus includes: a determination module, configured to determine a random private key corresponding to each first private data in the first privacy set of the second computing device; and to hide the i-th first private data according to the i-th random private key to obtain the i-th blinded data; A first sending module, configured to receive the i-th subscript data sent by the first computing device; and at the same time, send the i-th blinded data to the first computing device; wherein the i-th blinded data is used to obtain the i-th obfuscated data based on the oblivious transmission (OT) operation; and the i-th obfuscated data is used to generate a first hash value of each second private data in the second private set of the first computing device; A second sending module is used to determine the second hash value of the i-th first privacy data; and send the second hash value to the first computing device; wherein each of the first hash value and the second hash value is used to generate an intersection; and the intersection includes the common privacy data between the first privacy set and the second privacy set.

20. A first computing device, characterized in that: include: Memory, processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor performs the method according to any one of claims 1 to 9.

21. A second computing device, characterized in that: include: Memory, processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor performs the method according to any one of claims 10 to 17.

22. A secure computing system, characterized in that: The secure computing system includes a first computing device and a second computing device; the first computing device is used to implement the method according to any one of claims 1 to 9; and the second computing device is used to implement the method according to any one of claims 10 to 17.

23. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method according to any one of claims 1 to 9 or the method according to any one of claims 10 to 17.

24. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the method according to any one of claims 1 to 9 or the method according to any one of claims 10 to 17.

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