Homomorphic keyword privacy information retrieval method and system based on polynomial link

Abstract

The invention provides a homomorphic keyword privacy information retrieval method and system based on polynomial linking.The homomorphic keyword privacy information retrieval method and system based on polynomial linking.The homomorphic keyword privacy information retrieval method comprises the steps that data items in a database are segmented; the method comprises the following steps: processing keywords in a database by using cuckoo Hash, and publishing a used Hash function; creating a zero-value polynomial by using the processed elements in the table, and creating an interpolation polynomial on the segmented data items by using a polynomial linking technology and taking a hash value as a root; respectively calculating hash values of keywords expected to be queried by utilizing the published hash function; the method comprises the following steps: encrypting a hash value of a keyword expected to be queried by using a fully homomorphic encryption technology, and respectively calculating a value of each polynomial; and decrypting the value of the first zero-value polynomial, if 0 exists, indicating that the keyword is matched with the query, decrypting the value of the interpolation polynomial, and outputting a result obtained by the query. According to the method, the practicability of private information retrieval is expanded.

Description

Technical Field

[0001] The present invention belongs to the technical field of information retrieval, and in particular relates to a polynomial link-based homomorphic keyword privacy information retrieval method and system. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] Due to the rapid development of the Internet and the comprehensive digitization of personal information, personal privacy and security issues have become increasingly prominent. In the traditional database query process, when users search for information on the Internet, their queries may be recorded by search engines or third parties. This not only involves the leakage of user privacy, but may also lead to more serious information security issues. In addition, in some scenarios, such as healthcare, financial transactions, etc., it is particularly important to protect the privacy of user queries because these queries often involve very sensitive information. Private Information Retrieval (PIR) technology was developed in this context, aiming to provide a mechanism for users to access remote databases without exposing the content of their queries.

[0004] The current PIR can be divided into multi-server PIR and single-server PIR according to the number of servers. Multi-server PIR needs to be based on the assumption that there is no collusion between servers to achieve security defined in information theory, which is difficult to achieve in actual deployment. Single-server PIR is based on computationally indistinguishable security, which does not require additional assumptions and is easier to deploy in reality.

[0005] The current single-server PIR technology only supports a certain size of plaintext space, and most single-server PIRs are queried based on indexes, which requires users to know the index of the target data item when querying. Considering that this assumption is difficult to meet in actual applications, and the client may not be sure that the queried data item is in this database, a keyword-based query technology is needed. Usually, the domain where the keyword is located is a large range, and the keywords of a database are sparsely distributed in it. This sparsity will bring high computing and storage costs when processing the database, and may also cause the problem of reduced precision in interpolation operations. Therefore, it is necessary to compress the domain where the keyword is located into a smaller domain so that the keyword is densely distributed in the compressed domain. Summary of the invention In order to overcome the shortcomings of the above-mentioned prior art, the present invention provides a private information retrieval scheme based on polynomial links, cuckoo hashing and homomorphic encryption of keywords, which can resist the private information retrieval framework of semi-honest adversaries and effectively protect the client's privacy information when the server follows the protocol execution.

[0006] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions: A first aspect of the present invention provides a homomorphic keyword privacy information retrieval method based on polynomial links.

[0007] A homomorphic keyword privacy information retrieval method based on polynomial links, comprising: Segment the data items in the database to obtain segmented data items; Use cuckoo hashing to process keywords in the database, obtain the processed elements in the table, and publish the hash function used; Using the processed elements in the table to create a zero-value polynomial, and using the polynomial chaining technique to create an interpolation polynomial on the split data items with the hash value as the root; Calculate the hash values ​​of the keywords to be queried respectively using the published hash function; Encrypt the hash value of the keyword of the expected query using fully homomorphic encryption technology; Use the encrypted hash value to calculate the value of each polynomial respectively; First, decrypt the value of the first zero-valued polynomial. If there is no 0, it means that no keyword is matched, then output that the query does not exist and end the protocol; if there is 0, it means that the keyword matches the query, then decrypt the value of the interpolation polynomial and output the result of the query.

[0008] A second aspect of the present invention provides a homomorphic keyword privacy information retrieval system based on polynomial links.

[0009] A homomorphic keyword privacy information retrieval system based on polynomial links, comprising: Server and client side; The server side segments the data items in the database to obtain segmented data items; The server uses cuckoo hashing to process keywords in the database, obtains processed table elements, and publishes the hash function used; The server creates a zero-value polynomial using the processed elements in the table, and creates an interpolation polynomial on the segmented data items using a polynomial chaining technique with the hash value as the root; The client uses the hash function published by the server to calculate the hash value of the keyword that the client wants to query; The client encrypts the hash value of the keyword to be queried using fully homomorphic encryption technology and sends the encrypted value to the server. The server calculates the value of each polynomial using the encrypted hash value sent by the client and sends the value to the client; The client first decrypts the value of the first zero-valued polynomial. If there is no 0, it means that no keyword is matched, then the query does not exist and the protocol ends; if there is 0, it means that the keyword matches the query, then the value of the interpolation polynomial is decrypted and the query result is output.

[0010] The third aspect of the present invention provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps in a method as described in the first aspect of the present invention are implemented.

[0011] A fourth aspect of the present invention provides a computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps in a method as described in the first aspect of the present invention.

[0012] A fifth aspect of the present invention provides a computer program product comprising instructions, which, when running on a computer, enables the computer program to implement the steps in a method as described in the first aspect of the present invention when executed by a processor.

[0013] One or more of the above technical solutions have the following beneficial effects: The present invention proposes a private information retrieval scheme based on polynomial links. By using polynomial links, the plaintext is divided into segments of equal length, and the first segment of all plaintexts is used as the zero value to construct the first zero-value polynomial. Then, the first segment of all plaintexts is used as the definition domain and the remaining segments are used as the value range to construct interpolation polynomials respectively, so as to achieve the effect of linking plaintexts on the polynomials. Therefore, the scheme can expand the plaintext space in a linked manner while protecting the query content of the client from being leaked, thereby expanding the practicality of private information retrieval.

[0014] The present invention utilizes a cuckoo filter to map keywords into a smaller domain to arrange the keywords densely, which can make polynomial interpolation more accurate and efficient.

[0015] The present invention utilizes fully homomorphic encryption to encrypt the hash result of the client's keywords, thereby ensuring that the client's privacy is not disclosed.

[0016] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0018] Figure 1 This is a flow chart of a homomorphic keyword privacy information retrieval method based on polynomial links according to the first embodiment of the present invention; Figure 2 The data item segmentation and keyword mapping to hash representation in the first embodiment of the present invention; Figure 3 This is a schematic diagram of a polynomial link in Embodiment 1 of the present invention; Figure 4 This is a schematic diagram of the PIR protocol flow in Embodiment 1 of the present invention; Figure 5 It is a schematic diagram of the PIR complexity performance analysis comparison in the first embodiment of the present invention. DETAILED DESCRIPTION

[0019] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0020] It should be noted that the terms used herein are for describing specific embodiments only and are not intended to be limiting of exemplary embodiments according to the present invention.

[0021] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0022] Embodiment 1 This embodiment discloses a homomorphic keyword privacy information retrieval method based on polynomial links, including: Segment the data items in the database to obtain segmented data items; Use cuckoo hashing to process keywords in the database; get the processed elements in the table and publish the hash function used; Using the processed elements in the table to create a zero-value polynomial, and using the polynomial chaining technique to create an interpolation polynomial on the split data items with the hash value as the root; Calculate the hash values ​​of the keywords to be queried respectively using the published hash function; Encrypt the hash value of the keyword of the expected query using fully homomorphic encryption technology; Use the encrypted hash value to calculate the value of each polynomial respectively; First, decrypt the value of the first zero-valued polynomial. If there is no 0, it means that no keyword is matched, then output that the query does not exist and end the protocol; if there is 0, it means that the keyword matches the query, then decrypt the value of the interpolation polynomial and output the result of the query.

[0023] In order to explain this embodiment more clearly, Figure 1 As shown in the figure, the implementation process of homomorphic keyword privacy information retrieval based on polynomial links can be described as follows: In this embodiment, it is divided into two parts, in which the server holds the database , that is, the database includes keywords and data items, and the client Cilent holds a keyword that it wants to query ( ).

[0024] The specific steps are as follows: Step 1: Segment the data items in the database to obtain segmented data items.

[0025] In this embodiment, the data items in the database DB are stored in the server side Server. According to the selected slice length parameter bit is divided into Item, the data item after segmentation is expressed as , where y i Represents a data item shard.

[0026] Step 2: Use cuckoo hashing to process the keywords in the database, obtain the processed elements in the table, and publish the hash function used. In this embodiment, if Figure 2 As shown, the server uses cuckoo hashing to process the keywords in the data items after DB segmentation, which can be specifically expressed as: ; in,

[0027] The hash operation calls an existing hash function implementation.

[0028] Step 2-1: Perform a hash operation, where the hash function is ,get: .

[0029] Step 2-2: If there is a vacancy in the position corresponding to the three calculated hash values, insert it directly; otherwise, randomly select one of the positions and insert the original data Kick out and insert, original data Insert into the table after recalculating the position.

[0030] Step 2-3, after processing all Maps to a set of integers On the top, the elements in the table are formed after processing, where .

[0031] Because the cuckoo hash table will not be exactly full during internal mapping, the overall size is m and the number of integers in it is n. The zero-valued polynomials in the subsequent steps are calculated from the integers in the table.

[0032] Step 2-4: Store the original data in a bucket indexed by an integer. and the split data items .

[0033] In this embodiment, the hash table is specifically regarded as an integer table, in which the buckets are represented as corresponding rows, that is, the original and the split data items Stored after the integer.

[0034] Step 2-5: Server announces the hash function used .

[0035] Cuckoo Hashing is a data structure that resolves hash conflicts. This hashing method allows for lookup, insertion, and deletion operations with constant time complexity O(1) in the worst case. Therefore, using a cuckoo filter to map keywords to a smaller domain to make the keywords densely arranged can make polynomial interpolation more accurate and efficient.

[0036] Step 3: Use the processed elements in the table to create a zero-value polynomial, and use the polynomial chaining technique to create an interpolation polynomial on the data item with the hash value as the root.

[0037] In this embodiment, if Figure 3 As shown, the server uses the processed elements in the table to create zero-value polynomials, and uses polynomial linking technology to create Lagrange interpolation polynomials in each data item fragment.

[0038] The zero-valued polynomial is specifically expressed as: ; in, Represents the cuckoo hash The zero-valued n-degree polynomial, X represents the independent variable of the function, that is, the unknown number. It represents the corresponding integer in the hash table, and there are n of them in total.

[0039] The polynomial link technique is used to create Lagrange interpolation polynomials in each data item slice: .

[0040] in, The interpolation point is , The interpolation point is , and so on The interpolation point is .

[0041] The specific calculation formula of the interpolation polynomial is: ; Among them, y with superscripts and subscripts represents the data items after segmentation, where superscript i corresponds to the i-th slice, that is, the i-th interpolation polynomial, subscript j corresponds to the j-th data item, there are n in total, and x is the unknown independent variable. It is the corresponding integer in the hash table. There are n integers in total. j represents the integer corresponding to the jth data. , a represents the number of loops executed from 0 to n, The subscript a represents the corresponding a-th integer .

[0042] Polynomial chaining is a special interpolation polynomial that divides the plaintext into segments of equal length, and then uses the first segment of all plaintext as the zero value to construct the first zero-value polynomial, and then uses the first segment of all plaintext as the definition domain and the remaining segments as the value range to construct interpolation polynomials respectively, achieving the effect of chaining plaintext on the polynomial. Therefore, the plaintext space can be expanded in a chained manner while protecting the client's query content from being leaked, expanding the practicality of private information retrieval.

[0043] Step 4: Use the published hash function to calculate the hash values ​​of the keywords to be queried.

[0044] In this embodiment, the Client uses the hash function published by the Server. Calculate the hash values ​​of the keywords that the client expects to query respectively, as follows: ; Among them, m1, m2, and m3 respectively represent the hash values ​​of the keywords that the client expects to query.

[0045] Step 5: Use fully homomorphic encryption technology to encrypt the hash value of the keyword you want to query.

[0046] Step 5-1: Generate homomorphic encryption and decryption keys .

[0047] In this embodiment, a fully homomorphic encryption and decryption algorithm is used, and its parameters are set as follows: security parameters , plaintext modulus , ciphertext modulus , ring dimension ; And set the plaintext domain to ; The ciphertext field is ; Randomly sample the private key s in the ciphertext domain to generate homomorphic encryption and decryption keys.

[0048] The specific expression is as follows: : Private Key .

[0049] Step 5-2: The client uses a fully homomorphic encryption method to encrypt the keywords that the client expects to query. Encrypt them separately to get the keyword homomorphic encryption hash value, which is specifically expressed as: ; That is, the specific calculation process of the fully homomorphic encryption method is: First, select , that is, in the ciphertext domain Randomly sample a value in; Then, by Perform calculations; Where e is a polynomial that satisfies Gaussian distribution, m is the plaintext encoded as a polynomial, and the encoding method is , Finally, the ciphertext is represented as (a, b).

[0050] Step 5-3: Generate a query vector using the homomorphic encrypted hash value of the keyword Sent to Server.

[0051] Fully homomorphic encryption is an encryption scheme that allows arbitrary calculations to be performed on ciphertext, and the decrypted result is consistent with the result of performing the same operation directly on the plaintext. Using fully homomorphic encryption to encrypt the hash result of the client's keywords ensures that the client's privacy is not leaked.

[0052] Step 6: Use the encrypted hash value to calculate the value of each polynomial and send it to the client.

[0053] In this embodiment, there is a zero-value polynomial and k interpolation polynomials, all of which are substituted into the ciphertext for homomorphic calculation.

[0054] In this embodiment, the server uses the encrypted hash value of the received keyword Substitute the polynomial into the homomorphic calculation, where the polynomial involves the calculation of homomorphic multiplication and homomorphic addition, and send it to the Client in the form of a 3×k reply matrix: The specific expression is as follows: ; in, Represents the value after cuckoo hash operation A zero-valued n-order polynomial; c1, c2, c3 represent the hash values ​​of the keywords encrypted using fully homomorphic encryption technology; k represents the number of split items, which also represents the number of interpolation polynomials.

[0055] Step 7: First decrypt the value of the first zero-valued polynomial. If there is no 0, it means that no keyword is matched, then output that the query does not exist and end the protocol; if there is 0, it means that the keyword matches the query, then decrypt the value of the interpolation polynomial and output the query result.

[0056] The specific steps are as follows: Step 7-1: Decrypt the homomorphic calculation value of the zero-value polynomial in the first column of the reply matrix.

[0057] ; Step 7-2: If the homomorphic calculation value is , , If both are not equal to 0, the keyword matching fails and the protocol is terminated.

[0058] Step 7-2: If the homomorphic calculation value is , , If any of them is equal to 0, the 3xk reply matrix is ​​decrypted and the homomorphic calculation values ​​of the k interpolation polynomials corresponding to the row equal to 0 are output.

[0059] The specific expressions are as follows: ; in, , and Represents the cuckoo hash operation k zero-valued n-degree polynomials, represents the hash value of the αth item, It represents data item sharding, and the symbol σ represents a certain item. At this time, the number of matching items is unknown, so it is represented by σ.

[0060] This step refers to sending the above ciphertext to the server, which substitutes the polynomial for homomorphic calculation and returns it to the client, which decrypts it.

[0061] The calculation methods include: ; Assume that we get back the ciphertext c = (a, b) by decryption calculation Get the μ value, that is, get the plaintext in polynomial form, and then round it down after performing the modulo operation mod t.

[0062] like Figure 5 As shown in the figure, through the PIR complexity performance analysis and comparison, the storage and communication complexity analysis and comparison of different PIR methods are realized. Because only the hash result of the encrypted keyword needs to be encrypted, and the server only needs to return the corresponding homomorphic calculation result, the communication complexity is O(1); and the computational complexity is O(n) because the database is actually scanned when calculating the polynomial.

[0063] Compared with the existing high-performance solutions, the communication has reached a nearly optimal state, and the client does not need to store additional prompts, which is very friendly to the client. Compared with the high-performance solutions, it is necessary to store the corresponding prompts on the client after preprocessing, which puts a great pressure on the storage cost of the client. Secondly, the prompts are only for static databases. Once the database is updated, the prompts cannot be used. There is no such problem in this solution.

[0064] Through the above analysis and comparison, it can be seen that this embodiment is mainly optimized for the client, and the client only needs to calculate constant hashes and homomorphic encryption and decryption. All computing costs are borne by the server. Although the server throughput will be relatively low, the overall communication is very efficient.

[0065] Embodiment 2 The purpose of this embodiment is to provide a homomorphic keyword privacy information retrieval system based on polynomial links, including: a server and a client; The server side segments the data items in the database to obtain segmented data items; The server uses cuckoo hashing to process keywords in the database, obtains processed table elements, and publishes the hash function used; The server creates a zero-value polynomial using the processed elements in the table, and creates an interpolation polynomial on the segmented data items using a polynomial chaining technique with the hash value as the root; The client uses the hash function published by the server to calculate the hash value of the keyword that the client wants to query; The client encrypts the hash value of the keyword to be queried using fully homomorphic encryption technology and sends the encrypted value to the server. The server calculates the value of each polynomial using the encrypted hash value sent by the client and sends the value to the client; The client first decrypts the value of the first zero-valued polynomial. If there is no 0, it means that no keyword is matched, then the query does not exist and the protocol ends; if there is 0, it means that the keyword matches the query, then the value of the interpolation polynomial is decrypted and the query result is output.

[0066] Embodiment 3 The purpose of this embodiment is to provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the steps of the above method are implemented when the processor executes the program.

[0067] Embodiment 4 The purpose of this embodiment is to provide a computer-readable storage medium.

[0068] A computer-readable storage medium stores a computer program, which executes the steps of the above method when executed by a processor.

[0069] Embodiment 5 The purpose of this embodiment is to provide a computer program product containing instructions, which, when running on a computer, enables the computer to execute the methods and functions involved in any of the above embodiments. The steps involved in the apparatus of the above embodiment correspond to the method embodiment 1, and the specific implementation method can refer to the relevant description part of embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood to include any medium that can store, encode or carry an instruction set for execution by a processor and enable the processor to execute any method in the present invention.

[0070] Those skilled in the art should understand that the modules or steps of the present invention described above can be implemented by a general-purpose computer device, or alternatively, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. The present invention is not limited to any specific combination of hardware and software.

[0071] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without creative work are still within the scope of protection of the present invention.

Claims

1. A homomorphic keyword privacy information retrieval method based on polynomial links, characterized in that: include: Segment the data items in the database to obtain segmented data items; Use cuckoo hashing to process keywords in the database, obtain the processed elements in the table, and publish the hash function used; Using the processed elements in the table to create a zero-value polynomial, and using the polynomial chaining technique to create an interpolation polynomial on the split data items with the hash value as the root; Calculate the hash values ​​of the keywords to be queried respectively using the published hash function; Encrypt the hash value of the keyword of the expected query using fully homomorphic encryption technology; Use the encrypted hash value to calculate the value of each polynomial respectively; First, decrypt the value of the first zero-valued polynomial. If there is no 0, it means that no keyword is matched, then output that the query does not exist and end the protocol; if there is 0, it means that the keyword matches the query, then decrypt the value of the interpolation polynomial and output the query result.

2. A polynomial link-based homomorphic keyword privacy information retrieval method as claimed in claim 1, characterized in that: The method of using cuckoo hash to process keywords in the database to obtain processed table elements specifically includes: Perform hash operations on keywords in the database; If there is a vacancy in the position corresponding to the three calculated hash values, insert it directly. Otherwise, randomly select one of the positions and kick out the keyword of the original data and then insert it. The keyword of the original data is recalculated and inserted into the table. Map all processed keywords to an integer set to form the processed elements in the table.

3. A polynomial link-based homomorphic keyword privacy information retrieval method as claimed in claim 1, characterized in that: The creation of a zero-value polynomial is specifically expressed as: in, Represents the cuckoo hash The zero-valued n-degree polynomial, x represents the independent variable of the function, It represents the corresponding integer in the hash table, and there are n of them; The polynomial linking technique is used to create an interpolation polynomial on the segmented data item with the hash value as the root. The specific calculation formula is: Among them, y with superscripts and subscripts represents the data items after segmentation, where superscript i corresponds to the i-th segment, that is, the i-th interpolation polynomial, subscript j corresponds to the j-th data item, there are n in total, and x is the unknown independent variable. It is the corresponding integer in the hash table. There are n integers in total. j represents the integer corresponding to the jth data. , a represents the number of loops executed from 0 to n, The subscript a represents the corresponding a-th integer .

4. A polynomial link-based homomorphic keyword privacy information retrieval method as claimed in claim 1, characterized in that: The method of encrypting the hash value of the keyword to be queried using the fully homomorphic encryption technology specifically includes: First, generate homomorphic encryption and decryption keys through random sampling; Use the fully homomorphic encryption method to encrypt the keywords of the expected query respectively to obtain the keyword homomorphic encryption hash value; The obtained keyword homomorphic encrypted hash value generates the query vector.

5. A polynomial link-based homomorphic keyword privacy information retrieval method as claimed in claim 1, characterized in that: The encrypted hash value is used to calculate the value of each polynomial respectively, specifically: the encrypted hash value of the keyword of the expected query is substituted into the polynomial homomorphic calculation, the polynomial homomorphic calculation includes the calculation of homomorphic multiplication and homomorphic addition, and a 3×k reply matrix is ​​generated; wherein each polynomial includes a zero-value polynomial and an interpolation polynomial.

6. A polynomial link-based homomorphic keyword privacy information retrieval method as claimed in claim 1, characterized in that: The specific steps for decryption are: Decrypt the homomorphic calculation value of the zero-value polynomial of the first column of the reply matrix; If the obtained homomorphic calculation values ​​are not equal to 0, the keyword matching fails and the protocol is terminated; If any of the obtained homomorphic calculation values ​​is equal to 0, the homomorphic calculation values ​​of the k interpolation polynomials in the row corresponding to the 0th row of the decrypted recovery matrix are output.

7. A homomorphic keyword privacy information retrieval system based on polynomial links, characterized in that: include: Server and client side; The server side segments the data items in the database to obtain segmented data items; The server uses cuckoo hashing to process keywords in the database, obtains processed table elements, and publishes the hash function used; The server creates a zero-value polynomial using the processed elements in the table, and creates an interpolation polynomial on the segmented data items using a polynomial chaining technique with the hash value as the root; The client uses the hash function published by the server to calculate the hash value of the keyword that the client wants to query; The client encrypts the hash value of the keyword to be queried using fully homomorphic encryption technology and sends the encrypted value to the server. The server calculates the value of each polynomial using the encrypted hash value sent by the client and sends the value to the client; The client first decrypts the value of the first zero-valued polynomial. If there is no 0, it means that no keyword is matched, then the query does not exist and the protocol ends; if there is 0, it means that the keyword matches the query, then the value of the interpolation polynomial is decrypted and the query result is output.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the method described in any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method described in any one of claims 1 to 6 are performed.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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