Medical privacy data acquisition method and device, storage medium and electronic equipment

Abstract

The invention provides a medical privacy data acquisition method and device, a storage medium and electronic equipment, and is applied to a client, the method comprises the following steps: sending a query request for medical privacy data to a server, the server holding the medical privacy data of a plurality of patients, the query request carries a demand function of the client for the medical privacy data; under the condition that the client passes the identity authentication, receiving encrypted medical privacy calculation data returned by the server, the encrypted medical privacy calculation data being obtained after the server calculates and encrypts the medical privacy data according to the demand function; and performing decryption processing on the encrypted medical privacy calculation data to obtain the medical privacy calculation data corresponding to the demand function.

Description

Technical Field

[0001] One or more embodiments of the present specification relate to the field of computer technology, and in particular, to a method, device, storage medium, and electronic device for acquiring medical privacy data. Background Art

[0002] With the rapid development of information technology, people have gained unprecedented convenience. Taking the medical industry as an example, more and more data are transitioning from paper to electronic versions, and the way of information input has also changed from handwriting to keyboard input and voice input. Based on the rapid development of electronicization, the amount of medical privacy data is also increasing. Medical privacy data storage usually includes multimedia information in various formats such as medical records, identity information, and test results.

[0003] In related technologies, the massive amount of medical privacy data is usually stored on the server side, and when the user needs to use the medical privacy data, he can access the server side through the client side to obtain the corresponding medical privacy data. Furthermore, for the security of the data, the server side can encrypt the medical privacy data and send it to the client side. However, the above data acquisition method still has the risk of privacy leakage. Even if the server side encrypts the medical privacy data, once it is decrypted by criminals, the original medical privacy data can be obtained. Summary of the invention

[0004] In order to overcome the problems existing in the related art, this specification provides a method, device, storage medium and electronic device for obtaining medical privacy data.

[0005] According to a first aspect of an embodiment of this specification, a method for obtaining medical privacy data is provided, which is applied to a client, and the method includes: Sending a query request for the medical privacy data to a server, the server holding medical privacy data of multiple patients, the query request carrying a demand function of the client for the medical privacy data; When the client passes the identity authentication, receiving the encrypted medical privacy calculation data returned by the server, the encrypted medical privacy calculation data is obtained by the server calculating and encrypting the medical privacy data according to the demand function; The encrypted medical privacy calculation data is decrypted to obtain the medical privacy calculation data corresponding to the demand function.

[0006] According to a second aspect of the embodiments of this specification, a device for obtaining medical privacy data is provided, which is applied to a client, and the device includes: A sending unit, configured to send a query request for the medical privacy data to a server, wherein the server holds medical privacy data of multiple patients, and the query request carries a demand function of the client for the medical privacy data; A receiving unit, configured to receive the encrypted medical privacy calculation data returned by the server when the client passes the identity authentication, wherein the encrypted medical privacy calculation data is obtained by the server after calculating and encrypting the medical privacy data according to the demand function; The decryption unit is used to decrypt the encrypted medical privacy calculation data to obtain the medical privacy calculation data corresponding to the demand function.

[0007] According to a third aspect of the embodiments of this specification, there is provided an electronic device, including: A processor; a memory for storing processor executable instructions; wherein the processor is configured to implement the steps of the method described in the first aspect above.

[0008] According to a fourth aspect of the embodiments of this specification, a computer-readable storage medium is provided, on which executable instructions are stored; wherein, when the instructions are executed by a processor, the steps of the method described in the first aspect above are implemented.

[0009] Based on the above embodiments of this specification, it can be known that: In the method for obtaining medical privacy data described in this specification, the client can send a corresponding query request to the server, and the query request can carry a corresponding demand function. For example, the demand function is a function of the average value of the patient's age. The server can authenticate the client. If the identity authentication is passed, the server can calculate based on the medical privacy data it holds and the demand function to obtain a corresponding calculation result, such as the average value calculation result of the patient's age (such as 29.3). The server can then encrypt the result, thereby sending the encrypted encrypted medical privacy calculation data to the client. After the client decrypts it, it can obtain the result of the corresponding query request. It can be seen that the method for obtaining medical privacy data described in this specification transmits the result calculated based on the demand function, not the original medical privacy data. Even if the criminals perform brute force solution, they will not obtain the original medical privacy data, but only the corresponding calculation result (such as 29.3). However, the criminals do not know what the calculation result refers to (that is, they do not know that this is the average value of the patient's age). They can only obtain a value with unclear meaning (such as 29.3) and cannot know the actual meaning of the value, thereby greatly improving the security of data transmission.

[0010] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present specification. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the specification and, together with the description, serve to explain the principles of the specification.

[0012] Figure 1 It is an architecture diagram of a system for acquiring medical privacy data provided by an exemplary embodiment of this specification.

[0013] Figure 2 It is a flowchart of a method for obtaining medical privacy data provided by an exemplary embodiment of this specification.

[0014] Figure 3 It is a schematic structural diagram of an electronic device provided by an exemplary embodiment of this specification.

[0015] Figure 4 It is a block diagram of a device for acquiring medical privacy data provided by an exemplary embodiment of this specification. Implementation

[0016] Here, exemplary embodiments will be described in detail, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with one or more embodiments of this specification. Instead, they are only examples of devices and methods consistent with some aspects of one or more embodiments of this specification.

[0017] It should be noted that in other embodiments, the steps of the corresponding method are not necessarily performed in the order shown and described in this specification. In some other embodiments, the steps included in the method may be more or less than those described in this specification. In addition, the single step described in this specification may be decomposed into multiple steps for description in other embodiments; and the multiple steps described in this specification may also be combined into a single step for description in other embodiments. It should be understood that although the terms first, second, third, etc. may be used in this specification to describe various information, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of this specification, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein can be interpreted as "at the time of" or "when" or "in response to determination".

[0018] With the rapid development of information technology, people have gained unprecedented convenience. Taking the medical industry as an example, more and more data are transitioning from paper to electronic versions, and the way of information input has also changed from handwriting to keyboard input and voice input. Based on the rapid development of electronicization, the amount of medical privacy data is also increasing. Medical privacy data storage usually includes multimedia information in various formats such as medical records, identity information, and test results.

[0019] In the related art, for this massive amount of medical privacy data, it is usually stored on the server side, and when the user needs to use the medical privacy data, he can access the server side through the client side to obtain the corresponding medical privacy data. Furthermore, for the security of the data, the server side can encrypt the medical privacy data and send it to the client side. However, the above-mentioned data acquisition method still has the risk of privacy leakage. Even if the server side encrypts the medical privacy data, once it is decrypted by criminals, the original medical privacy data can be obtained. For example, as shown in Table 1, Table 1 is a schematic table of medical privacy data provided by an exemplary embodiment of this specification.

[0020] Table 1:

[0021] As can be seen from Table 1, the server holds the medical privacy data of 4 patients, which records the names and ages of the patients. In the related art, if the client needs to call the medical privacy data shown in Table 1, the server can encrypt it and send it to the client. After the client decrypts it, the medical privacy data shown in Table 1 can be obtained. However, the method of obtaining this data has the risk of privacy leakage, that is, user E can maliciously intercept the data packet sent by the server to the client, and then crack it. Finally, user E can obtain the medical privacy data shown in Table 1. In view of this, this specification proposes an improved solution, which is described in detail in conjunction with the accompanying drawings.

[0022] Figure 1 is an architecture diagram of a medical privacy data acquisition system provided by an exemplary embodiment of this specification, such as Figure 1 As shown, the system may include multiple clients (such as client 13 , client 14 and client 15 ) and a server 11 .

[0023] The server 11 can be deployed on a physical server including an independent host, or the data source 10 can be deployed on a virtual server (such as a cloud server) carried by a host cluster, and this specification does not limit this. The server 11 can be configured with a method for obtaining medical privacy data described in this specification (corresponding to the server), so that the server can accept the query request sent by the client and initiate identity authentication for the client. When the client passes the identity authentication, the server can perform calculations according to the demand function and encrypt the calculation results, and the server 11 can send the encrypted calculation results to the client.

[0024] In one embodiment, the server 12 may include a server deployed on a blockchain node. Blockchains are generally divided into three types: public blockchain, private blockchain, and consortium blockchain. In addition, there may be a combination of the above types, such as private blockchain + consortium blockchain, consortium blockchain + public blockchain, etc. Among them, the public chain has the highest degree of decentralization. Participants who join the public chain (also known as nodes in the blockchain) can read data records on the chain, participate in transactions, and compete for the right to record new blocks. Moreover, each node can freely join or exit the network and perform related operations. On the contrary, the private chain has a network write permission controlled by an organization or institution, and the data read permission is regulated by the organization. In short, the private chain can be a weakly centralized system with strict restrictions on nodes and a small number of nodes. This type of blockchain is more suitable for use within a specific organization. The consortium chain is a blockchain between the public chain and the private chain, which can achieve "partial decentralization". Each node in the alliance chain usually has a corresponding entity or organization; the node joins the network through authorization and forms a stakeholder alliance to jointly maintain the operation of the blockchain. Based on the basic characteristics of the blockchain, the blockchain is usually composed of several blocks. In these blocks, the timestamp corresponding to the creation time of the block is recorded respectively. All blocks strictly follow the timestamp recorded in the block to form a data chain in time order. For data generated outside the chain, it can be constructed into a standard transaction format supported by the blockchain, and then published to the blockchain. The node devices in the blockchain will reach a consensus on the transaction. After reaching a consensus, the node device as the accounting node in the blockchain will package the transaction into a block and store it persistently in the blockchain. Among them, the consensus algorithms supported in the blockchain may include: the first type of consensus algorithm, that is, the consensus algorithm in which the node devices need to compete for the accounting rights of each accounting cycle; for example, consensus algorithms such as Proof of Work (POW), Proof of Stake (POS), and Delegated Proof of Stake (DPOS); the second type of consensus algorithm, that is, the consensus algorithm that elects accounting nodes in advance for each accounting cycle (without the need to compete for accounting rights); for example, consensus algorithms such as Practical Byzantine Fault Tolerance (PBFT). As mentioned above, no matter which consensus algorithm shown above is adopted by the blockchain, the accounting nodes of this round can package the received transactions to generate candidate blocks, and send the generated candidate blocks or the block headers of the candidate blocks to other node devices for consensus verification.If other node devices receive the candidate block or the block header of the candidate block and verify that there is no problem, the candidate block can be appended to the end of the original blockchain as the latest block, thereby completing the blockchain accounting process. In the process of other nodes verifying the new block or block header sent by the accounting node, the transactions contained in the block can also be executed. The node can be configured as the server described in this specification.

[0025] The network 12 for interaction between the client and the server 11 may include various types of wired or wireless networks. In one embodiment, the network may include a public switched telephone network (PSTN) and the Internet.

[0026] The client can be configured on a terminal device, for example, the terminal device can be a PC 13, a mobile phone 14, and a wearable device 15 (such as a smart watch or smart glasses), and this specification does not limit this. The terminal electronic device can run a client configured with a method for obtaining medical privacy data described in this specification. The client can receive the encrypted calculation result sent by the server and decrypt it to obtain the corresponding calculation result.

[0027] Figure 2 This is a flowchart of a method for obtaining medical privacy data provided by an exemplary embodiment of this specification, which is applied to a client and may include the following steps: Step 202: Send a query request for the medical privacy data to a server, where the server holds medical privacy data of multiple patients, and the query request carries a demand function of the client for the medical privacy data.

[0028] The server can store the medical privacy data of multiple patients, which can include at least one of the following: the patient's medical record data, the patient's identity data, the test result data and / or the privacy data of the diagnosis and treatment application. For example, the medical record data is an electronic record of the medical activities such as the occurrence, development and prognosis of the patient's disease, the examination, diagnosis and treatment by medical personnel, and is also an electronic medical health file of the patient written in the prescribed format and requirements by summarizing, organizing and comprehensively analyzing the collected data. The patient's identity data may refer to the patient's age, gender, home address, contact number and other data. The test result data may refer to the patient's blood routine test results, CT (computer tomography) results, MRI (magnetic resonance imaging) results, etc., and the privacy data of the diagnosis and treatment application can be diverse. For example, taking digital medicine as an example, in the field of insomnia correction, digital medical technology can provide patients with corresponding diagnosis and treatment applications (APP or applet or H5, etc.), and the corresponding patients will leave corresponding privacy data when using the above application for treatment, such as sleep duration, insomnia duration, deep sleep duration, etc.

[0029] In one embodiment, the demand function may include at least one of the following: an average function, a maximum function, a minimum function, or a standard deviation function. The demand function described in this specification is mainly used to characterize the needs of the client, that is, when the user accesses the server through the client, the corresponding demand function can be determined in advance by the needs of this visit. For example, in this visit, if you want to obtain the average age of the patient, the corresponding demand function can be the average function; for another example, in this visit, if you want to obtain the average value, maximum value, minimum value, etc. of the user's blood sugar in the past month, the corresponding demand function can be the average function, maximum function, minimum function, etc. It can be understood that the demand function described in this specification can be determined according to actual conditions and is not limited to the above.

[0030] After the user determines the demand function according to actual needs, the user can send a query request to the server, and the query request can carry the demand function.

[0031] Step 204: When the client passes identity authentication, receive the encrypted medical privacy calculation data returned by the server, where the encrypted medical privacy calculation data is obtained by the server calculating and encrypting the medical privacy data according to the demand function.

[0032] The purpose of identity authentication is to ensure the legitimacy and rationality of the client and to avoid malicious access. Correspondingly, the methods of identity authentication can be diverse. For example, the server can initiate face recognition authentication, voiceprint authentication, fingerprint authentication, etc. to the client, or the data query request sent by the client can carry the corresponding identity key, and the server can store the identity key set corresponding to the authenticated user. When the identity key carried in the data query request matches the identity key set, it can be confirmed that the client identity authentication is successful. For another example, the data query request can carry a corresponding identity identifier. After receiving the data query request, the server can send a corresponding verification code SMS to the registered mobile phone number corresponding to the identity identifier. After the client fills in the corresponding verification code in the verification code SMS, the server will verify it. This manual does not limit the method of identity authentication.

[0033] The encrypted medical privacy calculation data described in this specification is obtained by the server calculating and encrypting the medical privacy data according to the demand function. Taking the medical privacy data shown in Table 1 as an example, assuming that the demand function carried in the data query request sent by the client is the average age function, the server can calculate based on the medical privacy data shown in Table 1 to obtain the average age of patients A, B, C, and D, that is, 26.25 years old. This 26.25 can be regarded as medical privacy calculation data. Further, after the server calculates and obtains the calculation result (medical privacy calculation data), it can encrypt the medical privacy calculation data to obtain encrypted medical privacy calculation data. The specific encryption method is not limited in this specification. For example, it can be server public key encryption and client private key decryption.

[0034] In one embodiment, the server may hold medical privacy data corresponding to multiple institutions, such as the medical privacy data of the first hospital, the medical privacy data of the second hospital, and the medical privacy data of the third hospital. Therefore, when the server holds medical privacy data corresponding to multiple institutions, the query request may carry identification information corresponding to the institution, and the identification information is used to instruct the server to return the encrypted medical privacy calculation data that matches the institution corresponding to the identification information. For example, the identification information of the first hospital is 001, the identification information of the second hospital is 002, and the identification information of the third hospital is 003. Therefore, the query request may carry the corresponding identification information, for example, the query request may carry the representation information 002, thereby instructing the server to return the encrypted medical privacy calculation data of the second hospital.

[0035] Step 206: decrypt the encrypted medical privacy calculation data to obtain the medical privacy calculation data corresponding to the demand function.

[0036] As mentioned above, the client can receive the encrypted medical privacy calculation data sent by the server, and then the client can perform decryption processing to obtain the medical privacy calculation data. For example, taking the medical privacy data and average function shown in Table 1 as an example, after the client performs decryption, it can obtain the average value of the patient's age, 26.25. However, the client will not receive the original medical privacy data, that is, the client will not obtain the medical privacy data shown in Table 1, so even if it is intercepted by criminals, it will not cause data leakage, because they do not know the specific meaning of 26.25, and even think it is invalid data, thereby improving the security of data transmission.

[0037] As can be seen from the above embodiments, in the method for obtaining medical privacy data described in this specification, the client can send a corresponding query request to the server, and the query request can carry a corresponding demand function, for example, the demand function is an average value function of the patient's age. The server can authenticate the client. If the identity authentication is passed, the server can calculate based on the medical privacy data it holds and the demand function to obtain the corresponding calculation result, such as the average value calculation result of the patient's age (such as 29.3). The server can then encrypt the result, thereby sending the encrypted encrypted medical privacy calculation data to the client. , and then after the client performs decryption, it can obtain the result of the corresponding query request. It can be seen that the method for obtaining medical privacy data described in this specification transmits the result calculated based on the demand function, not the original medical privacy data. Even if the criminals perform brute force solution, they will not obtain the original medical privacy data, but only the corresponding calculation result (such as 29.3). However, the criminals do not know what the calculation result refers to (that is, they do not know that this is the average value of the patient's age). They can only obtain an unclear value (such as 29.3) and cannot know the actual meaning of the value, thereby greatly improving the security of data transmission.

[0038] Corresponding to the above method embodiments, this specification also provides device embodiments.

[0039] Figure 3 This is a schematic structural diagram of an electronic device provided by an exemplary embodiment. Please refer to Figure 3 At the hardware level, the electronic device includes a processor 301, a network interface 302, a memory 303, a non-volatile memory 304, and an internal bus 305, and may also include hardware required for other functions. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it. Of course, in addition to the software implementation, this application does not exclude other implementation methods, such as logic devices or a combination of software and hardware, etc., that is to say, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0040] Please refer to Figure 4 , Figure 4 is a block diagram of a device for acquiring medical privacy data provided by an exemplary embodiment. Figure 4 As shown, the device comprises: A sending unit 402 is used to send a query request for the medical privacy data to a server, the server holds medical privacy data of multiple patients, and the query request carries a demand function of the client for the medical privacy data; The receiving unit 404 is used to receive the encrypted medical privacy calculation data returned by the server when the client passes the identity authentication, wherein the encrypted medical privacy calculation data is obtained by the server after calculating and encrypting the medical privacy data according to the demand function; The decryption unit 406 is used to decrypt the encrypted medical privacy calculation data to obtain the medical privacy calculation data corresponding to the demand function.

[0041] Optionally, the demand function includes at least one of the following: The mean, maximum, minimum, or standard deviation function.

[0042] Optionally, the medical privacy data includes at least one of the following: Patient’s medical history data, patient’s identity data, test result data, and / or private data of diagnosis and treatment applications.

[0043] Optionally, when the server holds medical privacy data corresponding to multiple institutions, the query request carries identification information corresponding to the institution, and the identification information is used to instruct the server to return encrypted medical privacy calculation data matching the institution corresponding to the identification information.

[0044] Optionally, the server includes a server deployed on a blockchain node.

[0045] For the device embodiment, since it basically corresponds to the method embodiment, the relevant parts can refer to the partial description of the method embodiment. The device embodiment described above is only schematic, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, that is, they may be located in one place, or they may be distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this specification. A person of ordinary skill in the art can understand and implement it without paying creative labor.

[0046] In a typical configuration, a computer device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0047] Memory may include non-permanent storage in a computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0048] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0049] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0050] 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, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with this specification. Instead, they are merely examples of devices and methods consistent with some aspects of this specification as detailed in the appended claims.

[0051] The terms used in this specification are for the purpose of describing specific embodiments only and are not intended to limit this specification. The singular forms "a", "the" and "the" used in this specification and the appended claims are also intended to include plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0052] It should be understood that although the terms first, second, third, etc. may be used in this specification to describe various information, this information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of this specification, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0053] The above description is only a preferred embodiment of this specification and is not intended to limit this specification. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of this specification should be included in the scope of protection of this specification.

Claims

1. A method for obtaining medical privacy data, characterized in that: Applied to a client, the method comprises: Sending a query request for the medical privacy data to a server, the server holding medical privacy data of multiple patients, the query request carrying a demand function of the client for the medical privacy data; When the client passes the identity authentication, receiving the encrypted medical privacy calculation data returned by the server, the encrypted medical privacy calculation data is obtained by the server calculating and encrypting the medical privacy data according to the demand function; The encrypted medical privacy calculation data is decrypted to obtain the medical privacy calculation data corresponding to the demand function.

2. The method according to claim 1, characterized in that The demand function includes at least one of the following: The mean, maximum, minimum, or standard deviation function.

3. The method according to claim 1, characterized in that The medical privacy data includes at least one of the following: Patient’s medical history data, patient’s identity data, test result data, and / or private data of diagnosis and treatment applications.

4. The method according to claim 1, characterized in that: In the case where the server holds medical privacy data corresponding to multiple institutions, the query request carries identification information corresponding to the institution, and the identification information is used to instruct the server to return encrypted medical privacy calculation data matching the institution corresponding to the identification information.

5. The method according to claim 1, characterized in that The server includes a server deployed on a blockchain node.

6. A device for acquiring medical privacy data, characterized in that: Applied to a client, the device comprises: A sending unit, configured to send a query request for the medical privacy data to a server, wherein the server holds medical privacy data of multiple patients, and the query request carries a demand function of the client for the medical privacy data; A receiving unit, configured to receive the encrypted medical privacy calculation data returned by the server when the client passes the identity authentication, wherein the encrypted medical privacy calculation data is obtained by the server after calculating and encrypting the medical privacy data according to the demand function; The decryption unit is used to decrypt the encrypted medical privacy calculation data to obtain the medical privacy calculation data corresponding to the demand function.

7. A computer-readable storage medium having a computer program stored thereon, wherein when the program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

8. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method according to any one of claims 1 to 5 when executing the program.

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