Data processing method and device

Abstract

The embodiment of the invention provides a data processing method and device, and the method comprises the steps: querying user data according to a query instruction, encrypting the queried user data to obtain encrypted user data, transmitting the encrypted user data to a server, obtaining user features according to the user data, and transmitting the user features to the server; the user features are input into a prediction model for access prediction to obtain access prediction data of each SIM card application, the access prediction data are sent to a server, the server uploads encrypted user data and the access prediction data to a block chain, and a smart contract deployed by the block chain carries out right distribution, so that the accuracy of access prediction is improved, and the user experience is improved. And the data processing efficiency and reliability are improved.

Description

Technical Field

[0001] This document relates to the field of data processing technology, and in particular to a data processing method and device. Background Art

[0002] With the continuous development of Internet technology and the continuous increase of user data, more and more user data needs to be stored and processed. More appropriate services can be provided to users through user data collected after user authorization. However, as more and more user data is generated, problems such as data security and inaccurate recommendations also arise, which causes troubles for users and service providers. In the prior art, recommendation indicators are usually obtained by collecting user data and then processing the data, which is prone to problems such as data security and large recommendation deviations. How to better provide recommendation services is an issue that all parties need to pay attention to. Summary of the invention

[0003] An embodiment of the present specification aims to provide a data processing method and device to solve the problems of poor data security and poor service recommendation accuracy encountered in the process of collecting and processing user data.

[0004] To solve the above technical problems, one embodiment of this specification is implemented as follows: In a first aspect, an embodiment of this specification provides a data processing method, the method comprising: Querying user data according to the query instruction and encrypting the queried user data to obtain encrypted user data, and sending the encrypted user data to the server; the server uploads the encrypted user data to the blockchain; Obtaining user characteristics according to the user data, and inputting the user characteristics into a prediction model to perform access prediction to obtain access prediction data of each SIM card application; The access prediction data is sent to the server; the server uploads the access prediction data to the blockchain; and the smart contract deployed by the blockchain distributes rights and interests according to the user data and the access prediction data.

[0005] The data processing method provided in this embodiment queries user data according to an externally input query instruction during user data processing, encrypts the user data and sends it to the server, so that the server uploads the encrypted user data to the blockchain for storage, manages the storage, access and update of the data through the smart contract deployed on the blockchain, ensures that the data cannot be tampered with, then extracts features from the user data to obtain user features, inputs the user features into the prediction model for near-field access prediction to obtain access prediction data for each SIM card application, and predicts the user's behavior more accurately through the pre-trained prediction model to improve the accuracy and effectiveness of service recommendations and / or rights issuance, and finally sends the access prediction data to the server so that the server uploads it to the blockchain, and issues rights through the smart contract deployed on the blockchain, thereby improving the user's SIM card application experience and improving data processing efficiency.

[0006] In a second aspect, another embodiment of this specification provides another data processing method, which is applied to a smart contract deployed on a blockchain, and the method includes: Obtaining the encrypted user data sent by the server and the access prediction data of each SIM card application; the access prediction data is obtained by performing access prediction through a prediction model; decrypting the encrypted user data to obtain user data, and calculating equity data according to the user data and the access prediction data; The rights and interests corresponding to the rights and interests data are issued to the user.

[0007] Another data processing method provided by this embodiment is that during the user data processing process, the smart contract deployed by the blockchain obtains the encrypted user data sent by the server and the access prediction data of each SIM card application, and stores the encrypted user data. The blockchain ensures that the data cannot be tampered with, thereby improving the security of the user data. The encrypted user data is decrypted to obtain the user data, and the rights and interests data is calculated based on the user data and the access prediction data, and the rights and interests corresponding to the rights and interests data are issued to the user. By providing rights and interests to the user, the user is attracted to participate in the activity. At the same time, the access prediction data is further issued to the user in advance, further attracting the user to participate in the activity, thereby improving the user experience of the SIM card application. At the same time, the smart contract method is used to reduce manual intervention, simplify data management, and improve data processing efficiency.

[0008] In a third aspect, another embodiment of the present specification provides a data processing device, including: A data sending module, used to query user data according to a query instruction, encrypt the queried user data to obtain encrypted user data, and send the encrypted user data to a server; the server uploads the encrypted user data to a blockchain; An access prediction module, used to obtain user characteristics based on the user data, and input the user characteristics into a prediction model to perform access prediction to obtain access prediction data for each SIM card application; A prediction data uploading module is used to send the access prediction data to the server; the server uploads the access prediction data to the blockchain; and the smart contract deployed by the blockchain distributes rights and interests according to the user data and the access prediction data.

[0009] In a fourth aspect, another embodiment of the present specification provides another data processing device, including: A data acquisition module is used to acquire the encrypted user data sent by the server and the access prediction data of each SIM card application; the access prediction data is obtained by performing access prediction through a prediction model; An equity calculation module, used for decrypting the encrypted user data to obtain user data, and calculating equity data according to the user data and the access prediction data; The rights issuance module is used to issue the rights corresponding to the rights data to the user.

[0010] In the fifth aspect, another embodiment of the present specification provides a data processing device, comprising: a memory, a processor, and computer executable instructions stored in the memory and executable on the processor, wherein the computer executable instructions, when executed by the processor, implement the steps of the data processing method as described in the first aspect above.

[0011] In the sixth aspect, another embodiment of the present specification provides another data processing device, comprising: a memory, a processor, and computer executable instructions stored in the memory and executable on the processor, wherein the computer executable instructions, when executed by the processor, implement the steps of the data processing method as described in the second aspect above.

[0012] In the seventh aspect, another embodiment of the present specification provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store computer-executable instructions, and when the computer-executable instructions are executed by a processor, the steps of the data processing method described in the first aspect above are implemented.

[0013] In an eighth aspect, another embodiment of the present specification provides another computer-readable storage medium, wherein the computer-readable storage medium is used to store computer-executable instructions, and when the computer-executable instructions are executed by a processor, the steps of the data processing method described in the second aspect above are implemented.

[0014] In the ninth aspect, another embodiment of the present specification provides a computer program product, wherein the computer program product includes a data processing program, and the data processing program is executed by a processor to implement the steps of the data processing method as described in the first aspect above.

[0015] In the tenth aspect, another embodiment of the present specification provides another computer program product, wherein the computer program product includes a data processing program, and the data processing program is executed by a processor to implement the steps of the data processing method as described in the second aspect above. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate one or more embodiments of the present specification or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present specification. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work. Figure 1 A data processing method processing flow chart provided for one or more embodiments of this specification; Figure 2 A processing flow chart of a data processing method applied to a rights issuance scenario provided by one or more embodiments of this specification; Figure 3 A schematic diagram of another data processing flow provided for one or more embodiments of this specification; Figure 4 A schematic diagram of a data processing device provided for one or more embodiments of this specification; Figure 5 A schematic diagram of another data processing device provided for one or more embodiments of this specification; Figure 6 A schematic diagram of the structure of a data processing device provided for one or more embodiments of this specification; Figure 7 A schematic diagram of the structure of another data processing device provided for one or more embodiments of this specification. DETAILED DESCRIPTION

[0017] In order to enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the following will be combined with the drawings in one or more embodiments of this specification to clearly and completely describe the technical solutions in one or more embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this document.

[0018] This specification provides a data processing method embodiment: Reference Figure 1 , which shows a data processing method processing flow chart provided by this embodiment, referring to Figure 2 , which shows a processing flow chart of a data processing method applied to a rights issuance scenario provided in this embodiment.

[0019] Reference Figure 1 The data processing method provided in this embodiment can be applied to a SIM card and / or a user terminal configured with a SIM card, and specifically includes the following steps S102 to S106.

[0020] Step S102: querying user data according to the query instruction and encrypting the queried user data to obtain encrypted user data, and sending the encrypted user data to the server.

[0021] In this embodiment, user data refers to the data stored by the user in the SIM card and / or the SIM card configured by the user terminal. Specifically, the user data may include: the user's call data, such as: call duration and / or call times, the user data may also include: the user's SMS data, such as: SMS content, SMS times and / or sender and receiver information, the user data may also include: SIM card application usage data, such as: SIM card application access times; in addition, the user data may also include: the user's traffic information, such as: traffic information consumed by each SIM card application. It should be noted that the user data may include any one of the above-mentioned data, or a combination of two or more of the above-mentioned data, which is not limited in this embodiment.

[0022] It should be pointed out that, considering that user data belongs to the user's privacy to a certain extent, if you want to obtain the user's user data, you can obtain the authorization of the user before obtaining the user data. The authorization method can be to send an authorization application page to the user's user terminal when the user activates the SIM card. The user can obtain the authorization to obtain the user data after confirming the authorization through the instruction; in addition, the authorization of the user can also be obtained through other methods, such as obtaining the authorization to obtain the user data through the signing of an agreement, such as: signing the agreement when the user applies for a SIM card. That is to say: the user data used in this application are all legal user data authorized by the user.

[0023] In specific implementation, the user data stored in the SIM card is queried according to the query instruction input from the outside, and the encrypted user data is obtained after the user data is encrypted, and the encrypted user data is sent to the server; after obtaining the encrypted user data, the server uploads the encrypted user data to the blockchain to store the data through the blockchain. Optionally, the server uploads the encrypted user data to the blockchain.

[0024] Specifically, the query instruction can be generated by the data collection application configured by the SIM card, and the SIM card and / or the user terminal can collect the user data stored in the SIM card, and encrypt the user data through asymmetric encryption by the SIM card, the user terminal and / or the server and then send it to the server. For example, automatically collect historical data D from the SIM card 1 , which can cover call records, text message records, data usage and other information, and uses asymmetric encryption technology to encrypt the collected data. 1 Get E(D 1 ), the encrypted data E(D 1 ) is stored on the blockchain. Smart contracts SC are used to manage the storage, access and update operations of data. Smart contracts SC can include data storage rules, access rights and update mechanisms to ensure the immutability and access control of data.

[0025] Step S104, obtaining user characteristics according to the user data, and inputting the user characteristics into a prediction model to perform access prediction to obtain access prediction data of each SIM card application.

[0026] In specific implementation, feature extraction is performed on user data to obtain multiple user features, and after feature preprocessing of the multiple user features, the preprocessed multiple user features are input into the prediction model. The prediction model performs access prediction based on the multiple user features and obtains and outputs access prediction data of each SIM card application.

[0027] In this embodiment, the access prediction data refers to the data predicted for the user to access each SIM card application. Specifically, the access prediction data may include the probability of the user accessing each SIM card application. The access prediction data may also include the access data of the user accessing each SIM card, such as: the user's SMS usage and / or the number of times the user accesses the SIM card application within the predicted time. It should be noted that the access prediction data may also be a combination of two or more of the above, such as: the probability corresponding to the number of times the user accesses each SIM card application.

[0028] In the specific implementation process, in order to improve the accuracy of access prediction and the validity of access prediction data, the user characteristics may be normalized and converted first, and the access prediction data of each SIM card application may be calculated based on the normalized characteristics and the converted characteristics; in an optional implementation manner provided in this embodiment, the access prediction includes: Normalizing the user feature to obtain a first feature, and performing feature conversion on the user feature to obtain a second feature; The access probability of each SIM card application is calculated according to the first feature and the second feature and used as the access prediction data.

[0029] Specifically, the user feature may include feature data corresponding to multiple user behaviors. For each feature data, the feature data may be first normalized to obtain a normalized first feature, the feature data may be converted into a periodic function to obtain a converted second feature, the first feature and the second feature may be composited to obtain a composite feature, and a probability calculation may be performed based on the composite feature to obtain the probability of the user behavior corresponding to the feature data, that is, the access probability of the SIM card application, and the probability may be used as access prediction data.

[0030] For example, first collect the original data D from the SIM card 1 Extract features, including but not limited to call duration, number of text messages, data usage, etc. Then, preprocess these feature data, such as normalization, to facilitate model processing, and use h(X i ) This normalization function handles the nonlinear relationship of Xi, through g(X i ,t) this periodic function captures the periodic changes of Xi through f(X i ) For each feature X i The algorithm is compounded, including an integral function and a logarithmic function, and finally P(U) is used to predict the probability of the user's future behavior.

[0031] ; ; ; ; Among them, X i is the i-th characteristic data of the user, such as call duration, data usage, etc. i is the weight of the i-th feature. b is a bias term used to adjust the threshold of the prediction model. α and β are constants used to adjust the impact of the logarithmic function. a and b are the upper and lower limits of the integral, and their specific values ​​depend on X. i n and m represent the total number of features and h(X i ). The above formula can more accurately capture and simulate the complex patterns of user behavior by comprehensively considering the periodic changes and nonlinear characteristics of user behavior data. This improves the model's prediction accuracy for future user behavior. Advanced mathematical operations such as integrals and complex functions in the formula bring deeper processing capabilities to data analysis, revealing more detailed user behavior characteristics and trends. In addition, accurate behavior prediction enables SIM card application providers to better understand user needs and preferences, thereby improving user satisfaction.

[0032] It should be noted that the prediction model in this embodiment refers to a pre-trained prediction model. In the specific training process, the prediction model can be trained on a cloud server, or offline, or on a blockchain. In an optional implementation manner provided in this embodiment, the prediction model is trained in the following manner: Taking historical user data as samples and taking user behavior data corresponding to the historical user data as labels; Inputting the sample into the model to be trained to perform service recommendation prediction and obtain prediction data; The parameters of the model to be trained are adjusted according to the prediction data and the label to obtain the prediction model.

[0033] Specifically, historical user data may include the user's historical call times, historical SMS usage and / or historical SIM card application access times, and user behavior data may include behavior data in the next data collection cycle corresponding to the historical user data, such as: the call probability in the next cycle of the historical cycle. The user behavior data can be obtained by calculating the historical user data and the user data of the next data collection cycle of the historical user data.

[0034] In the specific training process, the model training can also be carried out in a distributed manner on the blockchain network, and the nodes of the blockchain network are used for parallel computing, which not only improves the training efficiency but also enhances the privacy protection of the data. In view of this, a federated learning method can be adopted to send the initial model and initial parameters as training tasks to the SIM card and / or the user terminal configured with the SIM card, so that the SIM card and / or the user terminal configured with the SIM card is used as a training node for federated learning. The central node of the federated learning can also be configured in the server to improve the training efficiency. In an optional implementation manner provided in this embodiment, the model to be trained is obtained in the following manner: Obtaining the initial model and initial parameters sent by the server; The initial model is configured according to the initial parameters to obtain the model to be trained.

[0035] In the specific training process, federated learning can also be performed by cooperating with the training nodes and the central node to aggregate and update parameters. The federated learning method improves the model training efficiency and the prediction accuracy of the prediction model. In an optional implementation manner provided in this embodiment, the parameters of the model to be trained are adjusted in the following manner: Calculate a training loss according to the predicted data and the label, and calculate a first parameter according to the training loss; Sending the first parameter to the server; the server aggregates and updates parameters according to the first parameter, sends the updated parameter and uploads the updated parameter to the blockchain; The updated parameters are received and the parameters of the model to be trained are adjusted to obtain the prediction model.

[0036] In addition, blockchain can also record every update of the predictive model to improve the efficiency and traceability of data management.

[0037] Step S106: sending the access prediction data to the server.

[0038] In specific implementation, the SIM card and / or user terminal obtains the access prediction data output by the prediction model, and sends the access prediction data to the server; the server uploads the access prediction data to the blockchain; the smart contract deployed by the blockchain issues rights and interests to the user based on the user data and the access prediction data. Optionally, the server uploads the access prediction data to the blockchain; the smart contract deployed by the blockchain issues rights and interests based on the user data and the access prediction data.

[0039] During the specific execution process, the smart contract can be used to first detect whether the user data meets the rights issuance conditions, and the smart contract can be used to ensure the security and privacy protection of the data, while improving the data processing efficiency; in an optional implementation manner provided by this embodiment, after sending the access prediction data, it also includes: Detecting whether the user data meets the conditions for issuing rights and interests; If not, no action is required; If so, the equity data is calculated according to the user data and the access prediction data.

[0040] Optionally, the benefit issuance condition includes: the number of service access times in the user data is greater than a number threshold and / or the amount of accessed data in the user data is greater than a data amount threshold.

[0041] For example, detect whether the number of calls, the number of text messages and / or the number of times each SIM card application is used is greater than a number threshold. If so, determine that the user data meets the conditions for the issuance of rights and interests; or detect whether the duration of call records and / or the number of text message records is greater than a data volume threshold. If so, determine that the user data meets the conditions for the issuance of rights and interests.

[0042] During the specific execution process, the smart contract deployed on the blockchain can calculate the rights and interests according to the user data and issue the rights and interests to the user, so as to improve the user's experience of using the SIM card application and enhance the user's enthusiasm for participating in the interaction of the SIM card application. In view of this, the rights and interests data can be calculated according to the data contained in the user data to improve the accuracy of the rights and interests calculation. In an optional implementation manner provided in this embodiment, the rights and interests data calculation includes: Extracting the number of service accesses and the amount of access data from the user data; A first equity value is calculated as the equity data according to the number of service accesses and the amount of accessed data.

[0043] Specifically, the equity value may be calculated according to the number of accesses of each SIM card application in the user data and the amount of access data of each SIM card application.

[0044] For example, extract the call records and / or SMS records in the user data, as well as the number of calls, number of SMS messages and / or number of times each SIM card application is used in the user data, and use the formula R=f(A,B) to calculate the reward value: ; Among them, A represents the number of service visits and / or activity participation, which is reflected by an integral function that combines sine and cosine functions to capture the complex changes in user participation over time. B represents the amount of accessed data and / or user data contribution, which is reflected by a logarithmic function to simulate the impact of data contribution on rewards. α and β are the weight coefficients of activity participation and data contribution, respectively, which allow dynamic adjustment according to platform goals and economic conditions. The formula reflects a comprehensive evaluation of user contributions by taking user activity participation and data contribution as input parameters. Processing these parameters through integral and logarithmic functions can more accurately reflect the complexity and multi-dimensional characteristics of user behavior. The weight coefficients α and β allow dynamic adjustment according to the economic conditions and goals of the platform, making the reward distribution mechanism more flexible.

[0045] In addition, in order to improve user participation and enhance user enthusiasm for sharing user data, rights and interests may be further pre-issued to users based on the predicted access prediction data; in this regard, a second equity value may be calculated based on the access prediction data, and rights and interests may be issued to users based on the second equity value; in an optional implementation manner provided in this embodiment, the equity data calculation includes: Extracting the access probability of the access prediction data; A second equity value is calculated according to the access probability as the equity data.

[0046] Specifically, a rights comparison table can be configured for access probability, and the corresponding rights value can be queried in the table according to the access probability, or fixed rights data can be configured as the rights value, or the rights value corresponding to the SIM card application in the previous cycle can be used as the rights value of the rights pre-issued starting from this week. In addition, the access probability of each SIM card application can be statistically calculated, and the second rights value can be determined according to the statistical calculation results. The specific determination method can refer to the three rights value calculation methods provided above.

[0047] During the specific rights issuance process, the user rights account associated with the user and / or SIM card can be queried, and the rights can be issued to the user rights account to improve user participation; in an optional implementation manner provided by this embodiment, after the access prediction data is sent, it also includes: querying the user rights account associated with the user, and issuing the rights to the user rights account.

[0048] It should be noted that during the rights and interests distribution process, the rights and interests corresponding to the first rights and interests value and the rights and interests corresponding to the second rights and interests value can be distributed separately, that is, the rights and interests can be distributed in sequence; in addition, the rights and interests corresponding to the first rights and interests value and the rights and interests corresponding to the second rights and interests value can also be distributed at the same time, that is, the first rights and interests value and the second rights and interests value are used as rights and interests data, and the rights and interests corresponding to the rights and interests data are distributed to users.

[0049] In the specific execution process, the user's preferred service can also be determined according to the access prediction data, and the user's preferred service can be recommended to the user to improve the user's experience of using the SIM card application; in this regard, the access probability and probability threshold of each SIM card application can be detected, and the recommendation can be made after the detection passes; in an optional implementation manner provided by this embodiment, after sending the access prediction data, it also includes: the server recommends a service according to the access prediction data; Make service recommendations based on visit prediction data, including: querying the access rights of the provider of the target SIM card application, and filtering the access probability of the target SIM card application in the access prediction data based on the access rights; It is detected whether the access probability reaches a threshold value, and if so, a recommendation message of the target SIM card application is generated and sent to the user.

[0050] In this embodiment, access rights are used to characterize the scope of user data that can be perceived by the providers of each SIM card application. For example, under the authority of the provider of application A, only the number of visits to application A can be perceived; the provider of application B has higher authority and can perceive the number of visits to application B, the number of calls and text messages of the user. For another example, the provider of application C can perceive the number of visits to application C and the number of visits to other applications of the same type. In addition, access rights may also include information access rights, data modification rights and / or incentive collection rights. Access rights can also be combined with smart contracts to use encryption technology to achieve identity authentication and permission verification to ensure that each data access and modification meets the preset permission requirements.

[0051] It should be noted that each SIM card application can be recommended by the above-mentioned target SIM card application recommendation method. The specific operations can be performed with reference to the above-mentioned implementation mode, which will not be described in detail in this embodiment.

[0052] In addition, the user's preferred recommendation channel can be determined according to the access prediction data, and recommendations can be made to the user through the user's preferred recommendation channel to improve the user's experience of using the SIM card application. For example, if the user prefers to receive recommendations by phone, the recommended channel is the call channel. In this regard, the channel for sending the recommendation message can be determined according to the access probability of each channel in the access recommendation data. In another optional implementation manner provided by this embodiment, after sending the access prediction data, it also includes: the server recommends services according to the access prediction data; Make service recommendations based on visit prediction data, including: Querying the recommended channels associated with the provider of the target SIM card application, and filtering out the access probability of the target channel matching the recommended channel from the access prediction data; It is detected whether the access probability reaches a threshold value, and if so, the target channel is used as a channel for sending a recommendation message of the target SIM card application.

[0053] It should be noted that the recommended channels of each SIM card application can be determined by the above-mentioned method of determining the recommended channels of the target SIM card application. The specific operations can be performed with reference to the above-mentioned implementation mode, which will not be described in detail in this embodiment.

[0054] In summary, the one or more data processing methods provided in this embodiment, during the user data processing process, query the user data according to the query instruction input externally and encrypt the user data and then send it to the server, so that the server uploads the encrypted user data to the blockchain for storage, manages the storage, access and update of the data through the smart contract deployed by the blockchain, ensures that the data cannot be tampered with, and then extracts the user data to obtain the user features, inputs the user features into the prediction model for near-field access prediction to obtain the access prediction data of each SIM card application, and predicts the user's behavior more accurately through the pre-trained prediction model to improve the accuracy and effectiveness of service recommendation and / or rights issuance, and finally sends the access prediction data to the server so that the server uploads it to the blockchain, and issues rights through the smart contract deployed by the blockchain, thereby improving the user's SIM card application experience and improving data processing efficiency.

[0055] The following combination Figure 2 , taking the application of the data processing method provided by this embodiment in the identification code signing scenario as an example, the data processing method provided by this embodiment is further explained. Figure 2 The data processing method applied to the equity issuance scenario specifically includes steps S202 to S208.

[0056] Step S202: query user data according to the query instruction and encrypt it to obtain encrypted user data.

[0057] Step S204: Send the encrypted user data to the server.

[0058] After that, the server uploads the encrypted user data to the blockchain.

[0059] Step S206: extracting features from user data to obtain user features, and inputting the user features into a prediction model to perform access prediction to obtain access prediction data for each SIM card application.

[0060] Optionally, the access prediction includes: normalizing user features to obtain a first feature, and converting user features to obtain a second feature; and calculating the access probability of each SIM card application according to the first feature and the second feature and using the access prediction data.

[0061] Step S208: sending the access prediction data to the server.

[0062] After that, the server uploads the access prediction data to the blockchain. Optionally, the server performs service recommendation processing based on the access prediction data.

[0063] It should be noted that any one of steps S202 to S208 or a combination of any multiple steps can be selected from steps S102 to S106 to form a new implementation method according to the needs of implementation deployment; and any one or multiple technical features in the technical scheme composed of steps S202 to S208 can be selected from steps S102 to S106 to form a new implementation method according to the needs of actual deployment, or the technical features in one or more optional implementation methods provided by steps S102 to S106 can be selected to form a new implementation method, which will not be described one by one here.

[0064] Another data processing method embodiment provided in this specification: Reference Figure 3 , which shows a processing flow chart of another data processing method provided by this embodiment. Another data processing method provided by this embodiment can be applied to smart contracts deployed on blockchain, specifically including the following steps S302 to S306, refer to Figure 2 , which shows a processing flow chart of a data processing method applied to a rights issuance scenario provided in this embodiment.

[0065] Step S302: Obtain the encrypted user data sent by the server and the access prediction data of each SIM card application.

[0066] In this embodiment, user data refers to the data stored by the user in the SIM card and / or the SIM card configured by the user terminal. Specifically, the user data may include: the user's call data, such as: call duration and / or call frequency. The user data may also include: the user's SMS data, such as: SMS content, SMS frequency and / or sender and receiver information. The user data may also include: SIM card application usage data, such as: SIM card application access times; in addition, the user data may also include: the user's traffic information, such as: traffic information consumed by each SIM card application. It should be noted that the user data may include any of the above-mentioned data, or a combination of two or more of the above-mentioned data, which is not limited in this embodiment. Correspondingly, encrypted user data refers to encrypted user data, and the specific encryption operation may be performed by the SIM card, the user terminal and / or the server.

[0067] It should be pointed out that, considering that user data belongs to the user's privacy to a certain extent, if you want to obtain the user's user data, you can obtain the authorization of the user before obtaining the user data. The authorization method can be to send an authorization application page to the user's user terminal when the user activates the SIM card. The user can obtain the authorization to obtain the user data after confirming the authorization through the instruction; in addition, the authorization of the user can also be obtained through other methods, such as obtaining the authorization to obtain the user data through the signing of an agreement, such as: signing the agreement when the user applies for a SIM card. That is to say: the user data used in this application are all legal user data authorized by the user.

[0068] In specific implementation, the encrypted user data sent by the server after being encrypted by the SIM card and / or the user terminal, and the access prediction data of each SIM card application obtained by performing access prediction through the prediction model are obtained. Optionally, the access prediction data is obtained by performing access prediction through the prediction model.

[0069] Step S304: decrypt the encrypted user data to obtain user data, and calculate equity data according to the user data and the access prediction data.

[0070] In specific implementation, the encrypted user data is decrypted by the key corresponding to the encrypted user data to obtain the user data, and the equity data is calculated according to the user data and the access prediction data. Specifically, the first equity data can be calculated according to the user data, the second equity data can be calculated according to the access prediction data, the equity can be issued according to the first equity data, and the equity can be issued twice according to the second equity data. In addition, the first equity data and the second equity data can be used together as equity data for equity issuance, that is, a single equity issuance is performed.

[0071] During the specific execution process, the smart contract deployed on the blockchain can calculate the rights and interests according to the user data and issue the rights and interests to the user, so as to improve the user's experience of using the SIM card application and enhance the user's enthusiasm for participating in the interaction of the SIM card application. In view of this, the rights and interests data can be calculated according to the data contained in the user data to improve the accuracy of the rights and interests calculation. In an optional implementation manner provided in this embodiment, the rights and interests data calculation includes: Extracting the number of service accesses and the amount of access data from the user data; A first equity value is calculated as the equity data according to the number of service accesses and the amount of accessed data.

[0072] Specifically, the equity value may be calculated according to the number of accesses of each SIM card application in the user data and the amount of access data of each SIM card application.

[0073] For example, extract the call records and / or SMS records in the user data, as well as the number of calls, number of SMS messages and / or number of times each SIM card application is used in the user data, and use the formula R=f(A,B) to calculate the reward value: ; Among them, A represents the number of service visits and / or activity participation, which is reflected by an integral function that combines sine and cosine functions to capture the complex changes in user participation over time. B represents the amount of accessed data and / or user data contribution, which is reflected by a logarithmic function to simulate the impact of data contribution on rewards. α and β are the weight coefficients of activity participation and data contribution, respectively, which allow dynamic adjustment according to platform goals and economic conditions. The formula reflects a comprehensive evaluation of user contributions by taking user activity participation and data contribution as input parameters. Processing these parameters through integral and logarithmic functions can more accurately reflect the complexity and multi-dimensional characteristics of user behavior. The weight coefficients α and β allow dynamic adjustment according to the economic conditions and goals of the platform, making the reward distribution mechanism more flexible.

[0074] In addition, in order to improve user participation and enhance user enthusiasm for sharing user data, rights and interests may be further pre-issued to users based on the predicted access prediction data; in this regard, a second equity value may be calculated based on the access prediction data, and rights and interests may be issued to users based on the second equity value; in another optional implementation manner provided by this embodiment, the equity data calculation includes: Extracting the access probability of the access prediction data; A second equity value is calculated according to the access probability as the equity data.

[0075] Specifically, a rights comparison table can be configured for access probability, and the corresponding rights value can be queried in the table according to the access probability, or fixed rights data can be configured as the rights value, or the rights value corresponding to the SIM card application in the previous cycle can be used as the rights value of the rights pre-issued starting from this week. In addition, the access probability of each SIM card application can be statistically calculated, and the second rights value can be determined according to the statistical calculation results. The specific determination method can refer to the three rights value calculation methods provided above.

[0076] In addition, the first equity value and the second equity value may be used as equity data for equity distribution; in an optional implementation manner provided in this embodiment, the equity data calculation includes: Extracting the number of service accesses and the amount of access data from the user data, and extracting the access probability of the access prediction data; A first equity value is calculated according to the number of service accesses and the amount of access data, a second equity value is calculated according to the access probability, and the first equity value and the second equity value are used as the equity data.

[0077] Step S306: issuing the rights and interests corresponding to the rights and interests data to the user.

[0078] In specific implementation, the rights and interests to be issued to users are determined based on the rights and interests data, and the rights and interests are issued to users.

[0079] During the specific rights issuance process, the user rights account associated with the user and / or SIM card can be queried, and the rights can be issued to the user rights account to improve user participation; in an optional implementation manner provided by this embodiment, after the access prediction data is sent, it also includes: querying the user rights account associated with the user, and issuing the rights to the user rights account.

[0080] In summary, in the one or more data processing methods provided by the present embodiment, during the user data processing process, the smart contract deployed by the blockchain obtains the encrypted user data sent by the server and the access prediction data of each SIM card application, and stores the encrypted user data. The blockchain ensures that the data cannot be tampered with, thereby improving the security of the user data. The encrypted user data is decrypted to obtain the user data, and the rights and interests data is calculated based on the user data and the access prediction data, and the rights and interests corresponding to the rights and interests data are issued to the user. By providing rights and interests to the user, the user is attracted to participate in the activity. At the same time, the access prediction data is further issued to the user in advance, further attracting the user to participate in the activity, thereby improving the user's experience of using the SIM card application. At the same time, the smart contract is used to reduce manual intervention, simplify data management, and improve data processing efficiency.

[0081] It should be noted that the data processing method provided in the above embodiment can be applied to SIM cards and / or user terminals. Another data processing method provided in this embodiment can be applied to smart contracts deployed on blockchain. The data processing method provided in this embodiment that can be applied to smart contracts deployed on blockchain and the data processing method provided in the above embodiment that can be applied to SIM cards and / or user terminals have a coordinated relationship during execution. Therefore, when reading this embodiment, you can refer to the relevant content of the above embodiment. The relevant content of this embodiment is similar to the relevant content of the above embodiment, and this embodiment will not be repeated here.

[0082] The following combination Figure 2 , taking the application of the data processing method provided in this embodiment in the equity issuance scenario as an example, the data processing method provided in this embodiment is further explained. Figure 2 The data processing method applied to the equity issuance scenario specifically includes steps S210 to S220.

[0083] Step S210, obtaining the encrypted user data sent by the server, and storing the encrypted user data.

[0084] Step S212: obtaining access prediction data of each SIM card application sent by the server.

[0085] Step S214, decrypt the encrypted user data to obtain user data.

[0086] Step S216, extracting the service access times and access data volume from the user data, and extracting the access probability of each SIM card application from the access prediction data.

[0087] Step S218, calculating a first equity value according to the number of service accesses and the amount of accessed data, and calculating a second equity value according to the access probability.

[0088] Step S220: Use the first equity value and the second equity value as equity data, and distribute the equity corresponding to the equity data to the user.

[0089] It should be noted that any one of steps S212 to S220 or any combination of multiple steps can be combined with any one of steps S302 to S306 to form a new implementation method according to the needs of implementation deployment; and any one or multiple technical features in the technical scheme composed of steps S212 to S220 can be combined with any one or multiple technical features in the technical scheme composed of steps S302 to S306 to form a new implementation method according to the needs of actual deployment, or the technical features in one or more optional implementation methods provided by steps S302 to S306 can be combined with a new implementation method, which will not be elaborated here one by one.

[0090] Figure 4 A schematic diagram of a data processing device provided by an embodiment of the present invention is shown in FIG. Figure 4 As shown, the device comprises: The data sending module 402 is used to query user data according to the query instruction and encrypt the queried user data to obtain encrypted user data, and send the encrypted user data to the server; the server uploads the encrypted user data to the blockchain; An access prediction module 404 is used to obtain user characteristics according to the user data, and input the user characteristics into a prediction model to perform access prediction to obtain access prediction data of each SIM card application; The prediction data uploading module 406 is used to send the access prediction data to the server; the server uploads the access prediction data to the blockchain; and the smart contract deployed by the blockchain distributes rights and interests according to the user data and the access prediction data.

[0091] A data processing device provided in this embodiment, during the user data processing process, firstly runs a data sending module 402 to query user data according to an externally input query instruction and encrypts the user data and then sends it to a server, so that the server uploads the encrypted user data to the blockchain for storage, manages the storage, access and update of the data through the smart contract deployed on the blockchain, and ensures that the data cannot be tampered with, then runs an access prediction module 404 to extract features from the user data to obtain user features, inputs the user features into the prediction model for near-field access prediction to obtain access prediction data of each SIM card application, and predicts the user's behavior more accurately through the pre-trained prediction model to improve the accuracy and effectiveness of service recommendation and / or rights issuance, and finally runs the prediction data upload module 406 to send the access prediction data to the server, so that the server uploads it to the blockchain, and issues rights through the smart contract deployed on the blockchain, thereby improving the user's SIM card application usage experience and improving data processing efficiency.

[0092] The data processing device provided in one embodiment of this specification can implement each process in the aforementioned method embodiment and achieve the same functions and effects, which will not be repeated here.

[0093] Figure 5 A schematic diagram of another data processing device provided by an embodiment of the present invention is shown in FIG. Figure 5 As shown, the device comprises: The data acquisition module 502 is used to acquire the encrypted user data sent by the server and the access prediction data of each SIM card application; the access prediction data is obtained by performing access prediction through the prediction model; The equity calculation module 504 is used to decrypt the encrypted user data to obtain user data, and calculate the equity data according to the user data and the access prediction data; The rights issuance module 506 is used to issue the rights corresponding to the rights data to the user.

[0094] Another data processing device provided by this embodiment, during the user data processing process, the smart contract deployed by the blockchain runs the data acquisition module 502 to obtain the encrypted user data sent by the server and the access prediction data of each SIM card application, and stores the encrypted user data. The blockchain ensures that the data cannot be tampered with, thereby improving the security of the user data. The equity calculation module 504 is run to decrypt the encrypted user data to obtain the user data, and the equity data is calculated based on the user data and the access prediction data. Finally, the equity issuance module 506 is run to issue the equity corresponding to the equity data to the user. By providing the user with the equity, the user is attracted to participate in the activity. At the same time, the access prediction data is further issued to the user in advance, further attracting the user to participate in the activity, thereby improving the user's experience of using the SIM card application. At the same time, the smart contract is used to reduce manual intervention, simplify data management, and improve data processing efficiency.

[0095] Another data processing device provided in an embodiment of this specification can implement each process in the aforementioned method embodiment and achieve the same functions and effects, which will not be repeated here.

[0096] Furthermore, an embodiment of the present specification also provides a data processing device, Figure 6 A schematic diagram of a data processing device provided in an embodiment of this specification is shown in FIG. Figure 6 As shown, the device includes: a memory 601, a processor 602, a bus 603 and a communication interface 604. The memory 601, the processor 602 and the communication interface 604 communicate through the bus 603, and the communication interface 604 may include an input and output interface, which includes but is not limited to a keyboard, a mouse, a display, a microphone, a loudspeaker, etc.

[0097] Figure 6 In the embodiment, the memory 601 stores computer executable instructions that can be run on the processor 602. When the computer executable instructions are executed by the processor 602, the following process is implemented: Querying user data according to the query instruction and encrypting the queried user data to obtain encrypted user data, and sending the encrypted user data to the server; the server uploads the encrypted user data to the blockchain; Obtaining user characteristics according to the user data, and inputting the user characteristics into a prediction model to perform access prediction to obtain access prediction data of each SIM card application; The access prediction data is sent to the server; the server uploads the access prediction data to the blockchain; and the smart contract deployed by the blockchain distributes rights and interests according to the user data and the access prediction data.

[0098] The data processing device provided in this embodiment, through the cooperation of the memory 601, the processor 602, the bus 603 and the communication interface 604, in the process of user data processing, queries the user data according to the query instruction input externally and encrypts the user data and sends it to the server, so that the server uploads the encrypted user data to the blockchain for storage, manages the storage, access and update of the data through the smart contract deployed by the blockchain, ensures that the data cannot be tampered with, then extracts the user data to obtain the user features, inputs the user features into the prediction model for near-field access prediction to obtain the access prediction data of each SIM card application, predicts the user's behavior more accurately through the pre-trained prediction model, so as to improve the accuracy and effectiveness of service recommendation and / or rights issuance, and finally sends the access prediction data to the server, so that the server uploads it to the blockchain, and issues rights through the smart contract deployed by the blockchain, thereby improving the user's SIM card application experience and improving data processing efficiency.

[0099] The data processing device provided in one embodiment of this specification can implement each process in the aforementioned method embodiment and achieve the same functions and effects, which will not be repeated here.

[0100] Furthermore, an embodiment of the present specification also provides another data processing device, Figure 7 A structural diagram of another data processing device provided in an embodiment of this specification, such as Figure 7 As shown, the device includes: a memory 701, a processor 702, a bus 703 and a communication interface 704. The memory 701, the processor 702 and the communication interface 704 communicate through the bus 703, and the communication interface 704 may include an input and output interface, which includes but is not limited to a keyboard, a mouse, a display, a microphone, a loudspeaker, etc.

[0101] Figure 7 In the embodiment, the memory 701 stores computer executable instructions that can be run on the processor 702, and when the computer executable instructions are executed by the processor 702, the following process is implemented: Obtaining the encrypted user data sent by the server and the access prediction data of each SIM card application; the access prediction data is obtained by performing access prediction through a prediction model; decrypting the encrypted user data to obtain user data, and calculating equity data according to the user data and the access prediction data; The rights and interests corresponding to the rights and interests data are issued to the user.

[0102] Another data processing device provided by this embodiment, through the cooperation of the memory 701, the processor 702, the bus 703 and the communication interface 704, in the process of user data processing, the smart contract deployed by the blockchain obtains the encrypted user data sent by the server and the access prediction data of each SIM card application, and stores the encrypted user data, ensures the immutability of the data through the blockchain, improves the security of the user data, decrypts the encrypted user data to obtain the user data, calculates the rights and interests data according to the user data and the access prediction data, and distributes the rights and interests corresponding to the rights and interests data to the user, attracts the user to participate in the activity by providing the rights and interests to the user, and further distributes the rights and interests to the user in advance by accessing the prediction data, further attracts the user to participate in the activity, improves the user experience of the SIM card application, and reduces manual intervention, simplifies data management, and improves data processing efficiency by means of smart contracts.

[0103] The data processing device provided in one embodiment of this specification can implement each process in the aforementioned method embodiment and achieve the same functions and effects, which will not be repeated here.

[0104] Furthermore, another embodiment of the present specification provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store computer-executable instructions, and when the computer-executable instructions are executed by a processor, the following process is implemented: Querying user data according to the query instruction and encrypting the queried user data to obtain encrypted user data, and sending the encrypted user data to the server; the server uploads the encrypted user data to the blockchain; Obtaining user characteristics according to the user data, and inputting the user characteristics into a prediction model to perform access prediction to obtain access prediction data of each SIM card application; The access prediction data is sent to the server; the server uploads the access prediction data to the blockchain; and the smart contract deployed by the blockchain distributes rights and interests according to the user data and the access prediction data.

[0105] The computer-readable storage medium provided in this embodiment queries user data according to an externally input query instruction during user data processing, encrypts the user data, and then sends it to the server, so that the server uploads the encrypted user data to the blockchain for storage, manages the storage, access, and update of the data through the smart contract deployed on the blockchain, ensures that the data cannot be tampered with, then extracts features from the user data to obtain user features, inputs the user features into the prediction model for near-field access prediction to obtain access prediction data for each SIM card application, and more accurately predicts user behavior through the pre-trained prediction model to improve the accuracy and effectiveness of service recommendations and / or rights issuance, and finally sends the access prediction data to the server so that the server uploads it to the blockchain, and issues rights through the smart contract deployed on the blockchain, thereby improving the user's SIM card application experience and improving data processing efficiency.

[0106] The computer-readable storage medium includes a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0107] The computer-readable storage medium provided in an embodiment of this specification can implement each process in the aforementioned method embodiment and achieve the same functions and effects, which will not be repeated here.

[0108] Furthermore, another embodiment of the present specification provides another computer-readable storage medium, wherein the computer-readable storage medium is used to store computer-executable instructions, and when the computer-executable instructions are executed by a processor, the following process is implemented: Obtaining the encrypted user data sent by the server and the access prediction data of each SIM card application; the access prediction data is obtained by performing access prediction through a prediction model; decrypting the encrypted user data to obtain user data, and calculating equity data according to the user data and the access prediction data; The rights and interests corresponding to the rights and interests data are issued to the user.

[0109] Another computer-readable storage medium provided by this embodiment, during the user data processing process, the smart contract deployed by the blockchain obtains the encrypted user data sent by the server and the access prediction data of each SIM card application, and stores the encrypted user data. The blockchain ensures that the data cannot be tampered with, thereby improving the security of the user data. The encrypted user data is decrypted to obtain the user data, and the rights and interests data is calculated based on the user data and the access prediction data, and the rights and interests corresponding to the rights and interests data are issued to the user. By providing the users with rights and interests, the users are attracted to participate in the activities. At the same time, the access prediction data is further issued to the users in advance, further attracting the users to participate in the activities, thereby improving the user experience of the SIM card application. At the same time, the smart contract method is used to reduce manual intervention, simplify data management, and improve data processing efficiency.

[0110] The computer-readable storage medium includes a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0111] The computer-readable storage medium provided in an embodiment of this specification can implement each process in the aforementioned method embodiment and achieve the same functions and effects, which will not be repeated here.

[0112] Furthermore, another embodiment of the present specification also provides a computer program product, which implements the following process when executed by a processor: Querying user data according to the query instruction and encrypting the queried user data to obtain encrypted user data, and sending the encrypted user data to the server; the server uploads the encrypted user data to the blockchain; Obtaining user characteristics according to the user data, and inputting the user characteristics into a prediction model to perform access prediction to obtain access prediction data of each SIM card application; The access prediction data is sent to the server; the server uploads the access prediction data to the blockchain; and the smart contract deployed by the blockchain distributes rights and interests according to the user data and the access prediction data.

[0113] The computer program product provided in this embodiment queries user data according to an externally input query instruction during user data processing, encrypts the user data and sends it to the server, so that the server uploads the encrypted user data to the blockchain for storage, manages the storage, access and update of the data through the smart contract deployed on the blockchain, ensures that the data cannot be tampered with, then extracts features from the user data to obtain user features, inputs the user features into the prediction model for near-field access prediction to obtain access prediction data of each SIM card application, and predicts the user's behavior more accurately through the pre-trained prediction model to improve the accuracy and effectiveness of service recommendations and / or rights issuance, and finally sends the access prediction data to the server so that the server uploads it to the blockchain, and issues rights through the smart contract deployed on the blockchain, thereby improving the user's SIM card application usage experience and improving data processing efficiency.

[0114] The computer program product provided in one embodiment of this specification can implement each process in the aforementioned method embodiment and achieve the same functions and effects, which will not be repeated here.

[0115] Furthermore, another embodiment of the present specification provides another computer program product, which implements the following process when executed by a processor: Obtaining the encrypted user data sent by the server and the access prediction data of each SIM card application; the access prediction data is obtained by performing access prediction through a prediction model; decrypting the encrypted user data to obtain user data, and calculating equity data according to the user data and the access prediction data; The rights and interests corresponding to the rights and interests data are issued to the user.

[0116] Another computer program product provided by this embodiment, during the user data processing process, the smart contract deployed by the blockchain obtains the encrypted user data sent by the server and the access prediction data of each SIM card application, and stores the encrypted user data. The blockchain ensures that the data cannot be tampered with, thereby improving the security of the user data. The encrypted user data is decrypted to obtain the user data, and the rights and interests data is calculated based on the user data and the access prediction data, and the rights and interests corresponding to the rights and interests data are issued to the user. By providing the users with rights and interests, the users are attracted to participate in the activities. At the same time, the access prediction data is further issued to the users in advance, further attracting the users to participate in the activities, thereby improving the user experience of the SIM card application. At the same time, the smart contract method is used to reduce manual intervention, simplify data management, and improve data processing efficiency.

[0117] Another computer program product provided in an embodiment of this specification can implement each process in the aforementioned method embodiment and achieve the same functions and effects, which will not be repeated here.

[0118] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0119] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0120] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0121] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0122] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0123] Memory may include non-permanent storage in a computer-readable storage medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable storage medium.

[0124] Computer-readable storage 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-readable 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 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 storage media does not include temporary computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0125] 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.

[0126] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0127] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A data processing method, characterized in that: The method comprises: Querying user data according to the query instruction and encrypting the queried user data to obtain encrypted user data, and sending the encrypted user data to the server; the server uploads the encrypted user data to the blockchain; Obtaining user characteristics according to the user data, and inputting the user characteristics into a prediction model to perform access prediction to obtain access prediction data of each SIM card application; The access prediction data is sent to the server; the server uploads the access prediction data to the blockchain; and the smart contract deployed by the blockchain distributes rights and interests according to the user data and the access prediction data.

2. The data processing method according to claim 1, characterized in that: The access prediction includes: Normalizing the user feature to obtain a first feature, and performing feature conversion on the user feature to obtain a second feature; The access probability of each SIM card application is calculated according to the first feature and the second feature and used as the access prediction data.

3. The data processing method according to claim 1, characterized in that: The prediction model is trained in the following way: Taking historical user data as samples and taking user behavior data corresponding to the historical user data as labels; Inputting the sample into the model to be trained to perform service recommendation prediction and obtain prediction data; The parameters of the model to be trained are adjusted according to the prediction data and the label to obtain the prediction model.

4. The data processing method according to claim 3, characterized in that: The step of adjusting parameters of the model to be trained according to the prediction data and the label includes: Calculate a training loss according to the predicted data and the label, and calculate a first parameter according to the training loss; Sending the first parameter to the server; the server aggregates and updates parameters according to the first parameter, sends the updated parameter and uploads the updated parameter to the blockchain; The updated parameters are received and the parameters of the model to be trained are adjusted to obtain the prediction model.

5. The data processing method according to claim 3, characterized in that: The model to be trained is obtained in the following way: Obtaining the initial model and initial parameters sent by the server; The initial model is configured according to the initial parameters to obtain the model to be trained.

6. The data processing method according to claim 1, characterized in that: Also includes: The server makes service recommendations based on the access prediction data; The performing of service recommendation according to the access prediction data comprises: querying the access rights of the provider of the target SIM card application, and filtering the access probability of the target SIM card application in the access prediction data based on the access rights; It is detected whether the access probability reaches a threshold value, and if so, a recommendation message of the target SIM card application is generated and sent to the user.

7. The data processing method according to claim 1, characterized in that: Also includes: The server makes service recommendations based on the access prediction data; The performing of service recommendation according to the access prediction data comprises: Querying the recommended channels associated with the provider of the target SIM card application, and filtering out the access probability of the target channel matching the recommended channel from the access prediction data; It is detected whether the access probability reaches a threshold value, and if so, the target channel is used as a channel for sending a recommendation message of the target SIM card application.

8. A data processing method, characterized in that: A smart contract applied to a blockchain deployment, the method comprising: Obtaining the encrypted user data sent by the server and the access prediction data of each SIM card application; the access prediction data is obtained by performing access prediction through a prediction model; decrypting the encrypted user data to obtain user data, and calculating equity data according to the user data and the access prediction data; The rights and interests corresponding to the rights and interests data are issued to the user.

9. The data processing method according to claim 8, characterized in that: The calculating equity data according to the user data and the access prediction data includes: Extracting the number of service accesses and the amount of access data from the user data, and extracting the access probability of the access prediction data; A first equity value is calculated according to the number of service accesses and the amount of access data, a second equity value is calculated according to the access probability, and the first equity value and the second equity value are used as the equity data.

10. The data processing method according to claim 8, characterized in that: After decrypting the encrypted user data to obtain the user data and before calculating the equity data according to the user data and the access prediction data, the method further includes: Detecting whether the user data meets the conditions for issuing rights and interests; If so, executing the calculation of equity data according to the user data and the access prediction data; The rights issuance conditions include: the number of service access times in the user data is greater than a number threshold, and the amount of accessed data in the user data is greater than a data amount threshold.

11. The data processing method according to claim 8, characterized in that: The issuing of rights and interests corresponding to the rights and interests data to the user includes: Query the user rights account associated with the user, and distribute the rights to the user rights account.

12. A data processing device, characterized in that: The device comprises: A data sending module, used to query user data according to a query instruction, encrypt the queried user data to obtain encrypted user data, and send the encrypted user data to a server; the server uploads the encrypted user data to a blockchain; An access prediction module, used to obtain user characteristics based on the user data, and input the user characteristics into a prediction model to perform access prediction to obtain access prediction data for each SIM card application; A prediction data uploading module is used to send the access prediction data to the server; the server uploads the access prediction data to the blockchain; and the smart contract deployed by the blockchain distributes rights and interests according to the user data and the access prediction data.

13. A data processing device, characterized in that: The device comprises: A data acquisition module is used to acquire the encrypted user data sent by the server and the access prediction data of each SIM card application; the access prediction data is obtained by performing access prediction through a prediction model; An equity calculation module, used for decrypting the encrypted user data to obtain user data, and calculating equity data according to the user data and the access prediction data; The rights issuance module is used to issue the rights corresponding to the rights data to the user.

14. A data processing device, characterized in that: The device includes a memory and a processor, wherein the memory stores computer executable instructions, and when the computer executable instructions are executed on the processor, the steps of the data processing method described in any one of claims 1 to 7 or 8 to 11 can be implemented.

15. A computer-readable storage medium having computer-executable instructions stored therein, characterized in that: When the computer executable instructions are executed by a processor, the steps of the data processing method described in any one of claims 1-7 or 8-11 can be implemented.

16. A computer program product, characterized in that The computer program product includes a data processing program, and when the data processing program is executed by a processor, it can implement the steps of the data processing method described in any one of claims 1-7 or 8-11.

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