Transaction processing method, device, storage medium and electronic device

Abstract

The present specification discloses a transaction processing method, device, storage medium and electronic device, wherein the method comprises: monitoring a target file writing operation input by a target user for a target transaction approval document, determining target writing handwriting data corresponding to the target file writing operation, performing identity verification on the target user based on the target writing handwriting data and a reference signature file, and obtaining an identity verification result, wherein the reference signature file is a signature file of the target user for the target transaction, and performing target transaction approval processing on the target user based on the identity verification result.

Description

Technical Field

[0001] The present specification relates to the field of digital information transmission, and in particular to a transaction processing method, device, storage medium and electronic device. Background Art

[0002] With the rapid development of computers, the standardized development of global e-commerce and e-government has been greatly promoted. Nowadays, online financial transactions, online procurement, online office, online tax declaration, online banking, online payment, online contract signing and other e-commerce and e-government activities can be quickly completed through electronic document signing. Convenient electronic document signing not only saves the operating and management costs of enterprises, groups and other departments, but more importantly, greatly improves work efficiency. Summary of the invention

[0003] This specification provides a transaction processing method, device, storage medium and electronic device, and the technical solution is as follows:

[0004] In a first aspect, this specification provides a transaction processing method, the method comprising:

[0005] Monitoring a target document writing operation input by a target user for a target transaction approval document, and determining target writing handwriting data corresponding to the target document writing operation;

[0006] Performing identity verification on the target user based on the target handwriting data and the reference signature document to obtain an identity verification result, wherein the reference signature document is a signature document of the target user for the target transaction;

[0007] The target transaction approval process is performed on the target user based on the identity verification result.

[0008] In a second aspect, this specification provides a transaction processing device, the device comprising:

[0009] A monitoring module, used to monitor the target file writing operation input by the target user for the target business approval document, and determine the target writing handwriting data corresponding to the target file writing operation;

[0010] A verification module, used to verify the identity of the target user based on the target handwriting data and a reference signature document to obtain an identity verification result, wherein the reference signature document is a signature document of the target user for the target transaction;

[0011] A processing module is used to perform target transaction approval processing on the target user based on the identity verification result.

[0012] In a third aspect, the present specification provides a computer storage medium, wherein the computer storage medium stores at least one instruction, wherein the instruction is suitable for being loaded by a processor and executing the method steps of one or more embodiments of the present specification.

[0013] In a fourth aspect, the present specification provides a computer program product, wherein the computer program product stores at least one instruction, wherein the instruction is suitable for being loaded by a processor and executing the method steps of one or more embodiments of the present specification.

[0014] In a fifth aspect, the present specification provides an electronic device, which may include: a processor and a memory; wherein the memory stores a computer program, and the computer program is suitable for being loaded by the processor and executing the method steps of one or more embodiments of the present specification.

[0015] The beneficial effects brought by the technical solutions provided by some embodiments of this specification include at least:

[0016] In one or more embodiments of the present specification, when the target user inputs a target file writing operation for a target transaction approval document, the electronic device determines the target handwriting data corresponding to the target file writing operation, verifies the identity of the target user based on the target handwriting data and a reference signature document, and performs target transaction approval processing on the target user based on the identity verification result, which can effectively improve the security of transaction approval and reduce the risk of fraud, prevent unauthorized operations through accurate identity verification of the handwriting combined with the reference signature document, enhance the accuracy of user verification, adapt to different environments and application scenarios, and enhance the flexibility and adaptability of identity verification. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in this specification or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 It is a scenario diagram of a transaction processing system provided in this specification;

[0019] Figure 2 It is a flowchart of a transaction processing method provided in this specification;

[0020] Figure 3 This is a schematic diagram of the collection of a reference signature document provided in this manual;

[0021] Figure 4 This is a flowchart of an identity verification method provided in this manual;

[0022] Figure 5 It is a flowchart of another identity verification method provided in this manual;

[0023] Figure 6 It is a structural schematic diagram of a transaction processing device provided in this specification;

[0024] Figure 7 It is a structural diagram of a verification module provided in this specification;

[0025] Figure 8 It is a structural schematic diagram of an electronic device provided in this manual. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in this specification to clearly and completely describe the technical solutions in this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this specification.

[0027] In the description of this specification, it should be understood that the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In the description of this specification, it should be noted that, unless otherwise clearly specified and limited, "including" and "having" and any of their variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally also includes steps or units that are not listed, or optionally also includes other steps or units inherent to these processes, methods, products or devices. For those of ordinary skill in the art, the specific meanings of the above terms in this specification can be understood by specific circumstances. In addition, in the description of this specification, unless otherwise specified, "multiple" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships can exist, for example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects before and after are an "or" relationship.

[0028] In related technologies, convenient electronic document signing has subsequently raised concerns about identity security. For identity security reasons, electronic document signing usually needs to ensure that the document signing behavior is initiated by a trusted subject, rather than security issues caused by subject impersonation. Based on this, a secure and reliable transaction processing method is needed to ensure identity trust during the electronic document signing process.

[0029] The present specification is described in detail below with reference to specific embodiments.

[0030] See also Figure 1 , is a scenario diagram of a transaction processing system provided in this specification. Figure 1 As shown, the transaction processing system may include at least a client cluster and a service platform 100 .

[0031] The client cluster may include at least one client, such as Figure 1 As shown, it specifically includes client 1 corresponding to user 1, client 2 corresponding to user 2, ..., client n corresponding to user n, where n is an integer greater than 0.

[0032] Each client in the client cluster may be an electronic device with communication function, including but not limited to: wearable device, handheld device, personal computer, tablet computer, vehicle-mounted device, smart phone, computing device or other processing device connected to a wireless modem, etc. Electronic devices may be called different names in different networks, such as: user equipment, access terminal, user unit, user station, mobile station, mobile station, remote station, remote terminal, mobile device, user terminal, terminal, wireless communication device, user agent or user device, cellular phone, cordless phone, personal digital assistant (PDA), electronic devices in 5G network or future evolution network, etc.

[0033] The service platform 100 can be a separate server device, such as a rack-mounted, blade, tower, or cabinet-mounted server device, or a workstation, mainframe computer, or other hardware device with strong computing power; it can also be a server cluster composed of multiple servers, and the servers in the service cluster can be composed in a symmetrical manner, wherein each server has equivalent functions and status in the transaction link, and each server can provide services to the outside independently, and the independent service can be understood as not requiring the assistance of other servers.

[0034] In one or more embodiments of the present specification, the service platform 100 may establish a communication connection with at least one client in the client cluster, and complete user identity verification during the transaction processing based on the communication connection.

[0035] It should be noted that the service platform 100 and at least one client in the client cluster establish a communication connection through a network for interactive communication, wherein the network can be a wireless network or a wired network, the wireless network includes but is not limited to a cellular network, a wireless local area network, an infrared network or a Bluetooth network, and the wired network includes but is not limited to Ethernet, a universal serial bus (USB) or a controller local area network. In one or more embodiments of the specification, technologies and / or formats including Hyper Text Mark-up Language (HTML), Extensible Markup Language (XML), etc. are used to represent data (such as a target compressed package) exchanged through the network. In addition, conventional encryption technologies such as Secure Socket Layer (SSL), Transport Layer Security (TLS), Virtual Private Network (VPN), Internet Protocol Security (IPsec), etc. can also be used to encrypt all or some links. In other embodiments, customized and / or dedicated data communication technologies can also be used to replace or supplement the above data communication technologies.

[0036] The transaction processing system embodiment provided in this specification and the transaction processing method in one or more embodiments belong to the same concept. The execution subject corresponding to the transaction processing method involved in one or more embodiments of the specification can be the above-mentioned service platform 100; the execution subject corresponding to the transaction processing method involved in one or more embodiments of the specification can also be the electronic device corresponding to the client, which is determined based on the actual application environment. The embodiment of the transaction processing system and its implementation process can be detailed in the following method embodiment, which will not be repeated here.

[0037] based on Figure 1 The scenario diagram is shown, and the transaction processing method provided by one or more embodiments of this specification is introduced in detail below.

[0038] See also Figure 2 , a flowchart of a transaction processing method is provided for one or more embodiments of the present specification, the method can be implemented by a computer program and can be run on a transaction processing device based on the von Neumann system. The computer program can be integrated into an application or run as an independent tool application. The transaction processing device can be an electronic device.

[0039] Specifically, the transaction processing method includes:

[0040] S102: monitoring a target document writing operation input by a target user for a target transaction approval document, and determining target writing handwriting data corresponding to the target document writing operation;

[0041] The handwriting data includes handwriting data such as writing speed, writing pressure, pause time between writing strokes, writing acceleration, writing stroke angle, duration information, etc.;

[0042] Specifically, when the target user uses the target user terminal to write a document for an approval document of a target transaction, the electronic device can monitor the target user's target document writing operation on the approval document through the device. The target document writing operation includes any form of writing input, such as electronic handwriting or writing keyboard input, and then the electronic device collects the target handwriting data:

[0043] When the user is writing a document, the electronic device will support high-precision writing capture through sensors, so that the target user can collect the target writing handwriting data when performing the target document writing operation on the approval document.

[0044] S104: verifying the identity of the target user based on the target handwriting data and the reference signature document to obtain an identity verification result, wherein the reference signature document is a signature document of the target user for the target transaction;

[0045] The reference signature file is a sample of the user's past signature file collected by the target user in a preset trusted environment, and is stored in a database.

[0046] In this specification, when the target user is currently writing the approval document for the target transaction, the target handwriting data is collected and combined with the target user's past reference signature documents to verify his identity to prevent unauthorized users from accessing and operating.

[0047] The identity verification result may at least include identity verification success or identity verification failure;

[0048] Specifically, the identity verification process uses reference signature files collected from the target user when approving the same target transaction. These reference signature files are signature files containing electronic signature data or user writing samples when the user previously operated the same transaction.

[0049] Specifically, the target handwriting data is compared with the data in the reference signature document to verify the user's identity, and finally an identity verification result is obtained, which can effectively identify and resist attempts to forge signatures and reduce financial losses and reputation damage caused by identity theft or fraud.

[0050] For example, taking the target transaction as data transfer approval service, when users activate the data transfer service, they will be required to sign the relevant data transfer activation signature agreement and data transfer related signature contract online, such as Figure 3 As shown, Figure 3 It is a schematic diagram of the collection of reference signature documents. When the target user initiates the data transfer, it involves the signing of a data transfer contract. Then the electronic device will collect the aforementioned reference signature documents, monitor the user's reference document writing operation for the data transfer contract, determine the reference writing handwriting data corresponding to the reference document writing operation, generate a reference electronic signature based on the reference writing handwriting data, sign the data transfer contract based on the reference electronic signature, complete the contract signing process to obtain the reference signature document, and then archive the reference signature document;

[0051] When the target user subsequently initiates the actual data transfer approval matter, the target user needs to write relevant content into the new approval document for the target transaction. At this time, the target file writing operation will be input into the approval document, and the electronic device will collect the target writing handwriting data corresponding to the target file writing operation. The electronic device will then compare the target writing handwriting data with the data in the reference signature file to verify the user's identity, thereby ensuring the security of transaction processing.

[0052] In a feasible implementation manner, the electronic device performs identity verification on the target user based on the target handwriting data and the reference signature file, and obtains the identity verification result in the following manner:

[0053] The electronic device extracts the handwriting behavior characteristics of the target handwriting data to obtain the target handwriting behavior characteristics;

[0054] The reference handwriting behavior feature corresponding to the target user is obtained from the user handwriting feature library, and the handwriting feature comparison is performed based on the target handwriting behavior feature and the reference handwriting behavior feature to obtain a first identity verification result. The reference handwriting behavior feature is generated based on the reference signature file of the target user for the target transaction.

[0055] In a feasible implementation manner, the electronic device performs identity verification on the target user based on the target handwriting data and the reference signature file, and obtains the identity verification result in the following manner:

[0056] Query the reference signature file of the target user and obtain the reference electronic signature data corresponding to the reference signature file;

[0057] The identity handwriting verification is performed based on the target handwriting data and the reference electronic signature data to obtain a second identity verification result.

[0058] Optionally, the electronic device may generate a final identity verification result based on only one of the first identity verification result and the second identity verification result.

[0059] S106: Perform target transaction approval processing on the target user based on the identity verification result.

[0060] Indicatively, when the identity verification result is that the identity authentication is successful, the identity verification result is fed back to the target transaction processing system of the relevant target transaction, such as the target transaction approval process, the target transaction access control system, etc., to complete the target transaction approval processing for the target user;

[0061] Optionally, when the identity verification result is identity verification failure, the target transaction approval for the target user is stopped, and a security environment check for the current target user may be triggered.

[0062] In one or more embodiments of the present specification, when the target user inputs a target file writing operation for a target transaction approval document, the electronic device determines the target handwriting data corresponding to the target file writing operation, verifies the identity of the target user based on the target handwriting data and a reference signature document, and performs target transaction approval processing on the target user based on the identity verification result, which can effectively improve the security of transaction approval and reduce the risk of fraud, prevent unauthorized operations through accurate identity verification of the handwriting combined with the reference signature document, enhance the accuracy of user verification, adapt to different environments and application scenarios, and enhance the flexibility and adaptability of identity verification.

[0063] See also Figure 4 , Figure 4 This is a flowchart of an identity verification method proposed in one or more embodiments of this specification. To specifically perform the identity verification of the target user based on the target handwriting data and the reference signature file and obtain the identity verification result, the following method can be referred to:

[0064] S202: extracting handwriting behavior features from the target handwriting data to obtain target handwriting behavior features;

[0065] Exemplarily, the collected handwriting data is preprocessed, and then handwriting writing behavior features are extracted.

[0066] Preprocessing includes but is not limited to the following:

[0067] De-noising: Use filtering techniques (such as Gaussian filtering and median filtering) to remove noise from the target handwriting data.

[0068] Smoothing: Apply curve smoothing algorithms (such as Bezier curves and Kalman filters) to smooth the target handwriting data.

[0069] Coordinate transformation: transforming the handwriting coordinates in the target handwriting data into a consistent reference frame, which may involve normalization processing so that the data is not affected by the specific writing position and size.

[0070] For example, the writing speed feature: the speed of the handwriting is calculated based on the target handwriting data, that is, the speed of the pen tip moving. The writing speed feature can be expressed as the rate of change of the handwriting coordinate point within a time.

[0071] For example, the writing acceleration feature: the writing acceleration is calculated from the speed data based on the target handwriting data, that is, how fast the writing speed changes;

[0072] For example, stroke pressure characteristics: based on the target handwriting data, determine the pressure intensity of the handwriting touch on the screen;

[0073] For example, pause time feature: analyzing the pause time in handwriting based on the target handwriting data, such as the pause between letters or strokes.

[0074] For example, handwriting direction feature: based on the target handwriting data, the handwriting direction change information, that is, the direction of the pen tip movement, is analyzed, and the direction change information feature is vectorized to obtain the handwriting direction feature.

[0075] For example, handwriting curvature features: the curvature of handwriting, that is, the degree of handwriting bending, can be analyzed based on the target handwriting data, which can be used to identify the writing habits of a specific user for characters;

[0076] For example, handwriting density feature: the density of handwriting is analyzed based on the target handwriting data, that is, the degree of handwriting coverage per unit area.

[0077] Optionally, all extracted target handwriting behavior features are feature encoded and converted into target handwriting behavior features in the form of feature vectors;

[0078] In a feasible implementation, the feature extraction type for the target user is determined based on the reference handwriting writing behavior characteristics of the reference signature document collected by the target user. When the target user is involved in subsequent approval, the user-specific feature extraction type of the target user is first determined, and then the handwriting writing behavior characteristics of the collected target handwriting data are extracted according to the user-specific feature extraction type of the target user to obtain the target handwriting writing behavior characteristics; by extracting the reference handwriting writing behavior characteristics from the reference handwriting data of the target user under the trusted environment line in advance during the reference signature document collection stage, and then analyzing the user-specific writing feature type of the reference handwriting writing behavior characteristics to find the user-specific writing feature (extraction) type that distinguishes it from other users, and subsequently analyzing the target handwriting writing behavior characteristics based on the specified user-specific writing feature (extraction) type for the target user, the accuracy and reliability of feature analysis can be improved to build a unique writing feature profile for the target user, which is difficult to be imitated and deceived due to its personalized feature settings.

[0079] Selection of user-specific writing feature types: Convert the reference handwriting writing behavior features into reference handwriting writing behavior features represented in the form of vector features, and then use feature selection technology to compare the reference handwriting writing behavior features with other handwriting writing behavior features of other users to identify which features are most effective for the target user to distinguish different users. The goal is to find the feature type combination corresponding to the user-specific writing feature type that best represents the unique writing behavior of the target user, and then extract the corresponding target handwriting writing behavior features based on the feature type combination corresponding to the user-specific writing feature type;

[0080] Among them, feature selection techniques such as principal component analysis (PCA) model, linear discriminant analysis (LDA) model, and feature importance evaluation model through machine learning model;

[0081] Similarly, the above method is used to establish a feature type mapping relationship between different users and their corresponding user-specific writing features. In the actual application stage, the feature type mapping relationship can be directly used to query the current user's current user-specific writing features, and the handwriting writing behavior features of the specified feature type can be extracted based on the current user's unique writing features.

[0082] S204: Obtain a reference handwriting behavior feature corresponding to the target user from a user handwriting feature library, perform handwriting feature comparison based on the target handwriting behavior feature and the reference handwriting behavior feature, and obtain a first identity verification result.

[0083] The reference handwriting behavior feature is generated based on the reference signature file of the target user for the target transaction. The reference signature file is the signature file of the target user for the same target transaction;

[0084] In a feasible implementation, a handwriting verification model can be constructed and trained based on a machine learning model. By setting sample data under a variety of implementation environments to train the handwriting verification model, the writing environment on different devices and the influence of handwriting changes in different time periods can be covered, thereby improving recognition accuracy.

[0085] In actual applications, the target handwriting behavior characteristics corresponding to the target user are input into the handwriting verification model, and the reference handwriting behavior characteristics corresponding to the target user are obtained from the user handwriting feature library through the handwriting verification model. The handwriting features are compared based on the target handwriting behavior characteristics and the reference handwriting behavior characteristics to obtain the first identity verification result.

[0086] The handwriting verification model is obtained by training the initial handwriting verification model based on the handwriting writing behavior feature samples with the identity verification result labels, and the initial handwriting verification model is created based on the machine learning model;

[0087] Exemplarily, the model training process of the handwriting verification model is explained below:

[0088] Model creation: Create an initial handwriting verification model based on the machine learning model;

[0089] Sample data acquisition: obtain the sample handwriting behavior characteristics of sample users in a large number of different implementation environments (writing environments of the same user on different devices, writing environments of the same user at different time periods);

[0090] Sample data labeling: Introduce expert-side services to manually label the reference handwriting behavior features and sample handwriting behavior features of sample users in the user handwriting feature library, and label the identity verification result labels for the sample handwriting behavior features;

[0091] Model training process: input sample data into the initial handwriting verification model for at least one round of model training to obtain the predicted identity verification result, and use the model loss function to determine the model loss value based on the predicted identity verification result and the identity verification result label. Adjust the model parameters of the initial handwriting verification model based on the model loss value until the model training end conditions are met to obtain the handwriting verification model.

[0092] Optionally, the model loss function may be a hinge loss function, a cross entropy loss function, a feature distance loss function, etc.

[0093] Optionally, the model training end condition of the model may include, for example, the value of the loss function is less than or equal to a preset loss function threshold, the number of iterations reaches a preset number threshold, etc. The specific model training end condition can be determined based on actual conditions and is not specifically limited here.

[0094] It should be noted that the machine learning models involved in one or more embodiments of this specification include but are not limited to the fitting of one or more machine learning models such as Convolutional Neural Network (CNN) model, Deep Neural Network (DNN) model, Recurrent Neural Networks (RNN) model, embedding model, Gradient Boosting Decision Tree (GBDT) model, Logistic Regression (LR) model, etc.

[0095] Optionally, the following methods may be used to maintain and manage the reference handwriting behavior characteristics:

[0096] B2: obtaining reference handwriting data of a transaction document of at least one reference user for a target transaction, extracting handwriting behavior features from the reference handwriting data, and obtaining reference handwriting behavior features;

[0097] Illustratively, the reference handwriting data is handwriting data collected when the reference user performs a writing operation on the transaction writing document of the target transaction;

[0098] For a large number of reference users, when the reference users perform a file writing operation on a transaction writing file under a target transaction, handwriting data corresponding to the file writing operation is collected, and handwriting writing behavior features are extracted from the reference handwriting data to obtain reference handwriting writing behavior features;

[0099] Exemplarily, the collected reference handwriting data is preprocessed, and then the reference handwriting writing behavior feature is extracted after the preprocessing.

[0100] Illustratively, handwriting behavior features are extracted from the preprocessed reference handwriting data. The reference handwriting behavior features to be extracted may be a fit of one or more of the following features: writing speed features, writing acceleration features, stroke pressure features, pause time features, handwriting direction features, handwriting curvature features, stroke length features, and handwriting density features.

[0101] B4: electronically sign the transaction writing document based on the reference handwriting behavior feature to obtain the transaction signature document containing reference electronic signature data, and / or update the user handwriting feature library based on at least one reference handwriting behavior feature.

[0102] Illustratively, an electronic signature is generated based on reference handwriting writing behavior characteristics, and a transaction writing document is signed based on the electronic signature. To prevent the handwriting data from being tampered with, the reference handwriting writing behavior characteristics are creatively used as the source data of the signature in this specification. Based on the reference handwriting writing behavior characteristics, a signature algorithm in related technologies is used to perform signature calculations and convert them into electronic signature data. The electronic signature data is then embedded in the transaction writing document to obtain a transaction signature document, thereby effectively reducing the risk of fraud and improving security.

[0103] Indicatively, the signature signing process is completed to obtain a transaction signature document, and then the transaction signature document is archived;

[0104] In some embodiments, after obtaining the transaction signature file in the above manner, the transaction signature file can be stored; optionally, the electronic device will continuously extract the handwriting behavior characteristics according to the new reference handwriting data of the reference user to generate an electronic signature and then implant it into the new transaction writing file to obtain a new transaction signature file, and then the electronic device can save and update the transaction signature file for the reference user;

[0105] In some embodiments, after obtaining the transaction signature file in the above manner, the user handwriting feature library can also be updated based on the reference handwriting behavior feature. The electronic device will continuously extract handwriting behavior features based on the new reference handwriting data of the reference user and update the user handwriting feature library;

[0106] In one or more embodiments of the present specification, when a target user inputs a target file writing operation for a target transaction approval document, the electronic device determines the target writing handwriting data corresponding to the target file writing operation, performs handwriting writing behavior feature extraction on the target writing handwriting data to obtain the target handwriting writing behavior feature, obtains the reference handwriting writing behavior feature corresponding to the target user from the user handwriting writing behavior library, performs handwriting feature comparison based on the target handwriting writing behavior feature and the reference handwriting writing behavior feature to obtain a first identity verification result, and performs target transaction approval processing on the target user based on the identity verification result, which can effectively improve the security of transaction approval and reduce the risk of fraud, prevent unauthorized operations through accurate identity verification of the handwriting combined with the reference signature document, enhance the accuracy of user verification, and can adapt to different environments and application scenarios, thereby enhancing the flexibility and adaptability of identity verification.

[0107] See also Figure 5 , Figure 5This is a flowchart of another identity verification method proposed in one or more embodiments of this specification. To specifically perform the identity verification of the target user based on the target handwriting data and the reference signature file to obtain the identity verification result, the following method can be referred to:

[0108] S302: Query the reference signature file of the target user to obtain reference electronic signature data corresponding to the reference signature file;

[0109] In a feasible implementation, a large number of transaction signature files of reference users are pre-stored, and the electronic device can query the reference signature file of the target user and obtain the electronic signature data from the reference signature file;

[0110] Among the related technologies, electronic signature is an application technology that combines the digital signature of Public Key Infrastructure (PKI) with the electronic seal technology. The digital signature supports identity authentication, digital integrity, and non-repudiation functions. The electronic seal solves the visual expression of the digital signature. As the last link of paperless office, the electronic signature provides technical support for the legal effect of electronic documents with functions such as encrypting documents and preventing malicious tampering.

[0111] In this specification, for the first time, handwriting behavior characteristics are used as a source data in the electronic signature process, so that the electronic signature data after electronic signature contains handwriting behavior components, further improving security and convenience of identity verification;

[0112] S304: Perform identity handwriting verification based on the target handwriting data and the reference electronic signature data to obtain a second identity verification result.

[0113] Exemplarily, the electronic device may parse the reference electronic signature data to obtain the signature handwriting behavior features contained therein, and then compare the target handwriting behavior features of the target handwriting data with the signature handwriting behavior features;

[0114] Exemplarily, the electronic device may generate new electronic signature data based on the target handwriting data to compare the new electronic signature data with the reference electronic signature data.

[0115] In one or more embodiments of the present disclosure, the above method can be used to effectively extract the user's signature handwriting behavior characteristics from the electronic signature data, which are very important for high-accuracy user verification and identity confirmation. This method not only enhances the security of electronic document processing, but also provides an effective means to prevent signature forgery and identity theft.

[0116] In a feasible implementation, the following method may be adopted:

[0117] C2: Decoding the reference electronic signature data to obtain decoded signature data, and extracting signature handwriting behavior characteristics of the target user for the target transaction from the decoded signature data;

[0118] Decrypt the electronic signature data using the decryption key or decoding algorithm corresponding to the signature encryption, and restore it to the original signature vector data (which may include the signature image vector data) in the original format, which contains the signature handwriting behavior characteristics. According to the decoded electronic signature data format, identify the data area where the signature handwriting behavior characteristics are located, and then extract the signature handwriting behavior characteristics;

[0119] C4: extracting handwriting behavior features from the target handwriting data to obtain target handwriting behavior features;

[0120] For details, please refer to the method steps in other embodiments of this specification, which will not be repeated here;

[0121] C6: Perform handwriting behavior identity verification based on the signature handwriting behavior characteristics and the target handwriting behavior characteristics to obtain a second identity verification result.

[0122] For example, the signature handwriting behavior characteristics and the target handwriting writing behavior characteristics can be simultaneously input into the handwriting verification model, and the handwriting verification model is used to compare whether the signature handwriting writing behavior characteristics and the target handwriting writing behavior characteristics match, thereby obtaining a second identity verification result.

[0123] For example, the feature similarity between the signature handwriting behavior features and the target handwriting writing behavior features can be calculated, and the second identity verification result can be obtained based on the feature similarity and the similarity threshold. For example, if the feature similarity is greater than the similarity threshold, then the second identity verification result passes, otherwise the second identity verification result fails.

[0124] In a feasible implementation, an electronic signature generation process may be performed based on the target handwriting data to obtain target electronic signature data; and then an electronic signature identity verification may be performed based on the target electronic signature data and the reference electronic signature data to obtain a second identity verification result.

[0125] Exemplarily, the handwriting behavior feature of the target handwriting data is extracted to obtain the target handwriting behavior feature; the target handwriting behavior feature is input into the electronic signature generation algorithm as the newly added electronic signature source data and the original electronic signature source data to complete the encoding of the electronic signature data, and then the electronic signature comparison is performed based on the target electronic signature data and the reference electronic signature data, and according to the result of the electronic signature comparison, it is decided whether to authenticate the identity of the user. If the feature of the target electronic signature matches the reference data, the verification result of the second identity verification result is successful; if not, the verification result of the second identity verification result is failed.

[0126] In one or more embodiments of this specification, the above method is used to effectively realize the generation of electronic signatures and identity verification based on handwriting data. By using handwriting behavior characteristics as a biometric means, the security of identity authentication can be significantly improved. It can effectively identify and resist attempts to forge signatures, reduce financial losses and reputation damage caused by identity theft or fraud, and can also run on a variety of devices to adapt to different environments and application scenarios, enhancing the availability of transaction processing.

[0127] The following will be combined Figure 6 , the transaction processing device provided in this specification is introduced in detail. It should be noted that, Figure 6 The transaction processing device shown is used to execute this specification Figure 1~Figure 5 For the convenience of explanation, only the parts related to this specification are shown. For the specific technical details not disclosed, please refer to this specification. Figure 1~Figure 5 The embodiment shown.

[0128] See also Figure 6 , which shows a schematic diagram of the structure of the transaction processing device of this specification. The transaction processing device 1 can be implemented as all or part of the device through software, hardware or a combination of both. According to some embodiments, the transaction processing device 1 includes a monitoring module 11, a verification module 12 and a processing module 13, which are specifically used to:

[0129] The monitoring module 11 is used to monitor the target document writing operation input by the target user for the target business approval document, and determine the target writing handwriting data corresponding to the target document writing operation;

[0130] A verification module 12, configured to verify the identity of the target user based on the target handwriting data and a reference signature document to obtain an identity verification result, wherein the reference signature document is a signature document of the target user for the target transaction;

[0131] The processing module 13 is used to perform target transaction approval processing on the target user based on the identity verification result.

[0132] Optional, such as Figure 7 As shown, the verification module 12 includes:

[0133] A feature extraction unit 121 is used to extract the handwriting behavior feature of the target handwriting data to obtain the target handwriting behavior feature;

[0134] The feature comparison unit 122 is used to obtain the reference handwriting behavior feature corresponding to the target user from the user handwriting feature library, perform handwriting feature comparison based on the target handwriting behavior feature and the reference handwriting behavior feature, and obtain a first identity verification result.

[0135] The reference handwriting behavior feature is generated based on a reference signature file of the target user for the target transaction.

[0136] Optionally, the device 1 is also used for:

[0137] Acquire reference handwriting data of a transaction writing document of at least one reference user for a target transaction, extract handwriting behavior features from the reference handwriting data, and obtain reference handwriting behavior features;

[0138] The transaction writing document is electronically signed based on the reference handwriting behavior feature to obtain the transaction signature document containing reference electronic signature data, and / or the user handwriting feature library is updated based on at least one reference handwriting behavior feature.

[0139] Optionally, the feature comparison unit 122 is used to:

[0140] The target handwriting writing behavior characteristics corresponding to the target user are input into the handwriting verification model, and the reference handwriting writing behavior characteristics corresponding to the target user are obtained from the user handwriting writing behavior library through the handwriting verification model. A handwriting feature comparison is performed based on the target handwriting writing behavior characteristics and the reference handwriting writing behavior characteristics to obtain a first identity verification result.

[0141] Optionally, the verification module 12 is used to:

[0142] Query the reference signature file of the target user and obtain the reference electronic signature data corresponding to the reference signature file;

[0143] An identity handwriting verification is performed based on the target handwriting data and the reference electronic signature data to obtain a second identity verification result.

[0144] Optionally, the verification module 12 is used to:

[0145] Decoding the reference electronic signature data to obtain decoded signature data, and extracting signature handwriting behavior characteristics of the target user for the target transaction from the decoded signature data;

[0146] Extracting handwriting behavior features from the target handwriting data to obtain target handwriting behavior features;

[0147] Based on the signature handwriting behavior characteristics and the target handwriting behavior characteristics, handwriting behavior identity verification is performed to obtain a second identity verification result.

[0148] Optionally, the verification module 12 is used to:

[0149] Performing electronic signature generation processing based on the target handwriting data to obtain target electronic signature data;

[0150] An electronic signature identity verification is performed based on the target electronic signature data and the reference electronic signature data to obtain a second identity verification result.

[0151] It should be noted that the transaction processing device provided in the above embodiment only uses the division of the above functional modules as an example when executing the transaction processing method. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the transaction processing device provided in the above embodiment and the transaction processing method embodiment belong to the same concept, and the implementation process thereof is detailed in the method embodiment, which will not be repeated here.

[0152] The above serial numbers in this specification are for description only and do not represent the advantages or disadvantages of the embodiments.

[0153] In this specification, when the target user inputs a target file writing operation for a target transaction approval document, the electronic device determines the target handwriting data corresponding to the target file writing operation, verifies the identity of the target user based on the target handwriting data and the reference signature document, and performs target transaction approval processing on the target user based on the identity verification result. This can effectively improve the security of transaction approval and reduce the risk of fraud, prevent unauthorized operations through accurate identity verification of the handwriting combined with the reference signature document, enhance the accuracy of user verification, adapt to different environments and application scenarios, and enhance the flexibility and adaptability of identity verification.

[0154] The present specification also provides a computer storage medium, which can store multiple instructions, which are suitable for being loaded and executed by a processor as described above. Figure 1~Figure 4 The transaction processing method of the embodiment shown in the figure can be found in the specific execution process. Figure 1~Figure 4The specific description of the illustrated embodiment will not be repeated here.

[0155] The present specification also provides a computer program product, which stores at least one instruction, and the at least one instruction is loaded and executed by the processor as described above. Figure 1~Figure 4 The transaction processing method of the embodiment shown in the figure can be found in the specific execution process. Figure 1~Figure 4 The specific description of the illustrated embodiment will not be repeated here.

[0156] Please refer to Figure 8 , is a block diagram of a structure of an electronic device provided in an embodiment of this specification. The electronic device in this specification may include one or more of the following components: a processor 1010, a memory 1020, an input device 1030, an output device 1040, and a bus 1050. The processor 1010, the memory 1020, the input device 1030, and the output device 1040 may be connected via a bus 1050.

[0157] The processor 1010 may include one or more processing cores. The processor 1010 uses various interfaces and lines to connect various parts in the entire terminal, and executes various functions and processes data of the terminal 100 by running or executing instructions, programs, code sets or instruction sets stored in the memory 1020, and calling data stored in the memory 1020. Optionally, the processor 1010 can be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), and programmable logic array (PLA). The processor 1010 can integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. Among them, the CPU mainly processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing display content; and the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 1010, but may be implemented separately through a communication chip.

[0158] The memory 1020 may include a random access memory (RAM) or a read-only memory (ROM). Optionally, the memory 1020 includes a non-transitory computer-readable storage medium. The memory 1020 may be used to store instructions, programs, codes, code sets, or instruction sets.

[0159] The input device 1030 is used to receive input instructions or data, and the input device 1030 includes but is not limited to a keyboard, a mouse, a camera, a microphone, or a touch device. The output device 1040 is used to output instructions or data, and the output device 1040 includes but is not limited to a display device and a speaker. In the embodiment of this specification, the input device 1030 can be a temperature sensor for obtaining the operating temperature of the terminal. The output device 1040 can be a speaker for outputting audio signals.

[0160] In addition, those skilled in the art will understand that the structure of the terminal shown in the above drawings does not constitute a limitation on the terminal, and the terminal may include more or fewer components than shown, or combine certain components, or arrange the components differently. For example, the terminal also includes a radio frequency circuit, an input unit, a sensor, an audio circuit, a wireless fidelity (WIFI) module, a power supply, a Bluetooth module and other components, which will not be described in detail here.

[0161] In the embodiments of this specification, the execution subject of each step may be the terminal described above. Optionally, the execution subject of each step is the operating system of the terminal. The operating system may be an Android system, an IOS system, or other operating systems, which is not limited in the embodiments of this specification.

[0162] exist Figure 8 In the electronic device, the processor 1010 may be used to call the program stored in the memory 1020 and execute it to implement the following steps:

[0163] Monitoring a target document writing operation input by a target user for a target transaction approval document, and determining target writing handwriting data corresponding to the target document writing operation;

[0164] Performing identity verification on the target user based on the target handwriting data and the reference signature document to obtain an identity verification result, wherein the reference signature document is a signature document of the target user for the target transaction;

[0165] The target transaction approval process is performed on the target user based on the identity verification result.

[0166] In a feasible implementation manner, the processor 1010 may perform the following steps when performing the identity verification of the target user based on the target handwriting data and the reference signature file to obtain the identity verification result:

[0167] Extracting handwriting behavior features from the target handwriting data to obtain target handwriting behavior features;

[0168] A reference handwriting behavior feature corresponding to the target user is obtained from a user handwriting feature library, and a handwriting feature comparison is performed based on the target handwriting behavior feature and the reference handwriting behavior feature to obtain a first identity verification result.

[0169] The reference handwriting behavior feature is generated based on a reference signature file of the target user for the target transaction.

[0170] In a feasible implementation manner, the processor 1010, while executing the transaction processing method, further performs the following steps:

[0171] Acquire reference handwriting data of a transaction writing document of at least one reference user for a target transaction, extract handwriting behavior features from the reference handwriting data, and obtain reference handwriting behavior features;

[0172] The transaction writing document is electronically signed based on the reference handwriting behavior feature to obtain the transaction signature document containing reference electronic signature data, and / or the user handwriting feature library is updated based on at least one reference handwriting behavior feature.

[0173] In a feasible implementation manner, the processor 1010 performs the following steps when acquiring the reference handwriting behavior feature corresponding to the target user from the user handwriting feature library, performing handwriting feature comparison based on the target handwriting behavior feature and the reference handwriting behavior feature, and obtaining a first identity verification result:

[0174] The target handwriting writing behavior characteristics corresponding to the target user are input into the handwriting verification model, and the reference handwriting writing behavior characteristics corresponding to the target user are obtained from the user handwriting writing behavior library through the handwriting verification model. A handwriting feature comparison is performed based on the target handwriting writing behavior characteristics and the reference handwriting writing behavior characteristics to obtain a first identity verification result.

[0175] In a feasible implementation manner, the processor 1010 performs the following steps after performing the identity verification on the target user based on the target handwriting data and the reference signature file to obtain the identity verification result:

[0176] Query the reference signature file of the target user and obtain the reference electronic signature data corresponding to the reference signature file;

[0177] An identity handwriting verification is performed based on the target handwriting data and the reference electronic signature data to obtain a second identity verification result.

[0178] In a feasible implementation manner, the processor 1010 performs the following steps after executing the identity handwriting verification based on the target handwriting data and the reference electronic signature data to obtain a second identity verification result:

[0179] Decoding the reference electronic signature data to obtain decoded signature data, and extracting signature handwriting behavior characteristics of the target user for the target transaction from the decoded signature data;

[0180] Extracting handwriting behavior features from the target handwriting data to obtain target handwriting behavior features;

[0181] Based on the signature handwriting behavior characteristics and the target handwriting behavior characteristics, handwriting behavior identity verification is performed to obtain a second identity verification result.

[0182] In a feasible implementation manner, the processor 1010 performs the following steps after executing the identity handwriting verification based on the target handwriting data and the reference electronic signature data to obtain a second identity verification result:

[0183] Performing electronic signature generation processing based on the target handwriting data to obtain target electronic signature data;

[0184] An electronic signature identity verification is performed based on the target electronic signature data and the reference electronic signature data to obtain a second identity verification result.

[0185] In one or more embodiments of the present specification, when the target user inputs a target file writing operation for a target transaction approval document, the electronic device determines the target handwriting data corresponding to the target file writing operation, verifies the identity of the target user based on the target handwriting data and a reference signature document, and performs target transaction approval processing on the target user based on the identity verification result, which can effectively improve the security of transaction approval and reduce the risk of fraud, prevent unauthorized operations through accurate identity verification of the handwriting combined with the reference signature document, enhance the accuracy of user verification, adapt to different environments and application scenarios, and enhance the flexibility and adaptability of identity verification.

[0186] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only storage memory, or a random access memory, etc.

[0187] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.) and signals involved in the embodiments of this specification are all authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of relevant countries and regions. For example, the handwriting data, reference signature texts and user information involved in this specification are all obtained with full authorization.

[0188] The above disclosure is only the preferred embodiment of this specification, which certainly cannot be used to limit the scope of rights of this specification. Therefore, equivalent changes made according to the claims of this specification are still within the scope covered by this specification.

Claims

1. A transaction processing method, the method comprising: Monitoring a target document writing operation input by a target user for a target transaction approval document, and determining target writing handwriting data corresponding to the target document writing operation; The target user is verified based on the target handwriting data and the reference signature file to obtain an identity verification result, wherein the reference signature file is a transaction signature file obtained by converting the reference handwriting writing behavior characteristics of the target user for the target transaction into electronic signature data based on the reference handwriting writing behavior characteristics, and then embedding the electronic signature data into the transaction writing file; Performing target transaction approval processing on the target user based on the identity verification result; The step of performing identity verification on the target user based on the target handwriting data and the reference signature document to obtain an identity verification result includes: Querying the reference signature file of the target user, obtaining the reference electronic signature data corresponding to the reference signature file, performing identity handwriting verification based on the target handwriting data and the reference electronic signature data, and obtaining a second identity verification result; The performing identity handwriting verification based on the target handwriting data and the reference electronic signature data to obtain a second identity verification result includes: Perform handwriting behavior identity verification based on the target handwriting writing behavior characteristics corresponding to the target handwriting data and the signature handwriting writing behavior characteristics extracted from the reference electronic signature data to obtain a second identity verification result; or, generate target electronic signature data based on the target handwriting data, and perform electronic signature verification based on the target electronic signature data and the reference electronic signature data to obtain a second identity verification result.

2. According to the method of claim 1, the step of verifying the identity of the target user based on the target handwriting data and the reference signature document to obtain an identity verification result comprises: Extracting handwriting behavior features from the target handwriting data to obtain target handwriting behavior features; Acquire a reference handwriting behavior feature corresponding to the target user from a user handwriting feature library, and perform handwriting feature comparison based on the target handwriting behavior feature and the reference handwriting behavior feature to obtain a first identity verification result; The reference handwriting behavior feature is generated based on a reference signature file of the target user for the target transaction.

3. The method according to claim 1 or 2, further comprising: Acquire reference handwriting data of a transaction writing document of at least one reference user for a target transaction, extract handwriting behavior features from the reference handwriting data, and obtain reference handwriting behavior features; The transaction writing document is electronically signed based on the reference handwriting behavior feature to obtain the transaction signature document containing reference electronic signature data, and / or the user handwriting feature library is updated based on at least one reference handwriting behavior feature.

4. The method according to claim 2, wherein obtaining the reference handwriting behavior feature corresponding to the target user from the user handwriting feature library, performing handwriting feature comparison based on the target handwriting behavior feature and the reference handwriting behavior feature to obtain the first identity verification result, comprises: The target handwriting writing behavior characteristics corresponding to the target user are input into the handwriting verification model, and the reference handwriting writing behavior characteristics corresponding to the target user are obtained from the user handwriting writing behavior library through the handwriting verification model. A handwriting feature comparison is performed based on the target handwriting writing behavior characteristics and the reference handwriting writing behavior characteristics to obtain a first identity verification result.

5. According to the method of claim 1, the handwriting behavior identity verification is performed based on the target handwriting behavior characteristics corresponding to the target handwriting data and the signature handwriting behavior characteristics extracted from the reference electronic signature data to obtain a second identity verification result, comprising: Decoding the reference electronic signature data to obtain decoded signature data, and extracting signature handwriting behavior characteristics of the target user for the target transaction from the decoded signature data; Extracting handwriting behavior features from the target handwriting data to obtain target handwriting behavior features; Based on the signature handwriting behavior characteristics and the target handwriting behavior characteristics, handwriting behavior identity verification is performed to obtain a second identity verification result.

6. The method according to claim 1, wherein generating target electronic signature data based on the target handwriting data comprises: An electronic signature generation process is performed based on the target handwriting data to obtain target electronic signature data.

7. A transaction processing device, comprising: A monitoring module, used to monitor the target file writing operation input by the target user for the target business approval document, and determine the target writing handwriting data corresponding to the target file writing operation; A verification module, used to verify the identity of the target user based on the target handwriting data and the reference signature file to obtain an identity verification result, wherein the reference signature file uses the reference handwriting writing behavior characteristics of the target user for the target transaction as the source data of the electronic signature to perform electronic signature calculation based on the reference handwriting writing behavior characteristics and convert them into electronic signature data, and then implant the electronic signature data into the transaction writing file to obtain a transaction signature file; A processing module, used for performing target transaction approval processing on the target user based on the identity verification result; The step of performing identity verification on the target user based on the target handwriting data and the reference signature document to obtain an identity verification result includes: Querying the reference signature file of the target user, obtaining the reference electronic signature data corresponding to the reference signature file, performing identity handwriting verification based on the target handwriting data and the reference electronic signature data, and obtaining a second identity verification result; The performing identity handwriting verification based on the target handwriting data and the reference electronic signature data to obtain a second identity verification result includes: Perform handwriting behavior identity verification based on the target handwriting behavior characteristics corresponding to the target handwriting data and the signature handwriting behavior characteristics extracted from the reference electronic signature data to obtain a second identity verification result; or Target electronic signature data is generated based on the target handwriting data, and electronic signature verification is performed based on the target electronic signature data and the reference electronic signature data to obtain a second identity verification result.

8. A computer storage medium storing a plurality of instructions, wherein the instructions are suitable for being loaded by a processor and executing the method steps as claimed in any one of claims 1 to 6.

9. A computer program product, wherein the computer program product stores at least one instruction, wherein the at least one instruction is loaded by a processor and executes the method steps according to any one of claims 1 to 6.

10. An electronic device, comprising: A processor and a memory; wherein the memory stores a computer program, and the computer program is suitable for being loaded by the processor and executing the method steps as claimed in any one of claims 1 to 6.

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