CN112884481A

CN112884481A - Block chain payment processing method based on cloud computing and big data service center

Info

Publication number: CN112884481A
Application number: CN202110388331.7A
Authority: CN
Inventors: 刘明明
Original assignee: Individual
Current assignee: Individual
Priority date: 2020-09-15
Filing date: 2020-09-15
Publication date: 2021-06-01
Also published as: CN112200577B; CN112990935A; CN112200577A

Abstract

According to the block chain payment processing method based on cloud computing and the big data service center, the message header identification of each piece of message information in each group of information packets and the message correlation degree between every two pieces of message information in each group of information packets are analyzed, and the corresponding information verification dimension can be determined. In this way, each group of information packets may be verified based on the corresponding information verification dimension by running each group of parallel verification threads to obtain a verification result. Therefore, the accuracy and the time sequence relevance of the parallel check thread for checking the information packet can be ensured.

Description

Block chain payment processing method based on cloud computing and big data service center

The application is a divisional application with the application date of '09/15/2020', the application number of 'CN 202010964875.9', the name of 'block chain payment processing method combined with cloud computing analysis and big data service center'.

Technical Field

The application relates to the technical field of cloud computing and block chain payment, in particular to a block chain payment processing method based on cloud computing and a big data service center.

Background

Although the consensus mechanism of the blockchain (blockchain) can solve and ensure the security problem of each transaction on all accounting nodes when the blockchain network transfers information and value, the blockchain can still cooperate and complete operation efficiently in a large scale without depending on a centralized organization. However, this consensus mechanism requires that the block nodes use different consensus algorithms to match the cryptography to achieve the above objective.

Further, the consensus mechanism mainly comprises: (1) a workload certification mechanism pow, (2) an equity certification mechanism pos, (3) a delegation equity certification Dpos; and (4) verifying pool consensus mechanism pool. However, these common recognition mechanisms require memory resources of the blockchain node, which may reduce the processing efficiency of the blockchain node at other service levels.

In summary, it is desirable to develop a technology for ensuring the security of blockchain transaction and blockchain payment without affecting the processing efficiency of blockchain nodes on other business layers.

Disclosure of Invention

The application provides a block chain payment processing method based on cloud computing and a big data service center, which are used for solving or partially solving the technical problems mentioned in the background technology.

In a first aspect of the present application, a method for processing a blockchain payment based on cloud computing is provided, including:

when checking the current identity information of a payee block chain node, judging whether the current identity information is checked;

when the current identity information is not verified, calculating the residual verification time consumption of the current identity information based on the information association degree of the current identity information among different information packets in the current verification time period and the information verification category of the current identity information;

judging whether the calculated residual verification time reaches a set time;

starting a parallel verification mode aiming at the current identity information on the premise that the calculated residual verification time consumption reaches a set time consumption;

when the parallel verification mode is started, dividing the current identity information based on the information verification requirement of the payer block link point for the current identity information to obtain a grouped information packet;

and checking the grouped information packet based on the parallel checking mode so as to realize the identity information checking of the payee block chain node.

In a second aspect of the present application, a big data service center is provided, which includes a blockchain payment processing apparatus integrated with a plurality of functional modules, where the plurality of functional modules implement the steps of the method when running.

A third aspect of the present application is directed to a computer readable storage medium having a computer program stored thereon, which when executed by a processor, performs the steps of the above method.

A fourth aspect of the present application is to provide a big data service center, which includes a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of the method when executing the program.

Through one or more technical scheme of this application, this application has following beneficial effect or advantage:

firstly, when the current identity information of a payee block chain node is judged to be not verified, calculating the residual verification time consumption of the current identity information based on the information association degree of the current identity information among different information packets in the current verification time period and the information verification type of the current identity information, secondly, starting a parallel verification mode aiming at the current identity information on the premise that the calculated residual verification time consumption reaches the set time consumption, then, dividing the current identity information based on the information verification requirement of the payer block chain node aiming at the current identity information to obtain grouped information packets, and finally, verifying the grouped information packets based on the parallel verification mode to realize the identity information verification of the payee block chain node. Therefore, the identity information of the payee block chain node can be quickly and accurately verified by cloud verification of the identity information of the payee block chain node and then parallel verification is realized, so that the safety of block chain transaction and block chain payment is ensured on the premise of not influencing the processing efficiency of the block chain node on other business layers.

The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.

Drawings

Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the application. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:

fig. 1 illustrates an architectural schematic diagram of a cloud computing-based blockchain payment processing system according to one embodiment of the present application;

fig. 2 shows a schematic flow diagram of a method of cloud computing-based blockchain payment processing according to an embodiment of the present application;

fig. 3 illustrates a functional block diagram of a cloud computing-based blockchain payment processing apparatus according to one embodiment of the present application;

FIG. 4 shows a schematic diagram of a big data service center according to one embodiment of the present application.

Detailed Description

Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

The inventor has found through research and study that in order to ensure the safety of the blockchain transaction and the blockchain payment, the inventor needs to start from the front end of transaction behavior, and further, the inventor has found that the identity information check on the payee blockchain link point is the key to ensure the safety of the blockchain transaction and the blockchain payment. Therefore, the inventor innovatively provides a cloud computing-based block chain payment processing method and a big data service center, and identity information verification of a payee block chain node can be quickly and accurately realized by verifying the identity information of the payee block chain node to be cloud-ended, so that the safety of block chain transaction and block chain payment is ensured on the premise of not influencing the processing efficiency of the block chain node on other business layers.

Referring first to fig. 1, a cloud computing-based blockchain payment processing system 100 is shown, including a big data server center 110 and a plurality of blockchain nodes 120, wherein the big data server center 110 is deployed in a cloud and is in communication with the plurality of blockchain nodes 120, and the plurality of blockchain nodes 120 are in communication with each other to form different payer blockchain nodes and payee blockchain nodes. On the basis of fig. 1, please refer to fig. 2 in combination, which is a flowchart illustrating a block chain payment processing method based on cloud computing, where the method may be applied to the big data service center 110 in fig. 1, and specifically may include the contents described in the following steps S210 to S260.

Step S210, when checking the current identity information of the payee block chain node, judging whether the current identity information is checked completely.

For example, the current identity information may be information for detecting whether the payee block link node is in a secure payment state, and the current identity information has uniqueness among different payee block link nodes.

Step S220, when the current identity information is not verified, calculating the remaining verification time of the current identity information based on the information association degree between different information packets of the current identity information in the current verification period and the information verification category of the current identity information.

For example, the current verification period may be set according to a CPU clock resource of the big data service center, and is not limited herein. The remaining verification time is used for representing the time length required for completing the verification of the current identity information.

In step S230, it is determined whether the calculated remaining verification time reaches a set time.

Step S240, starting a parallel verification mode for the current identity information on the premise that the calculated remaining verification time reaches a set time.

For example, the parallel verification pattern is loaded and deployed in the big data service center based on the script configuration file in advance.

Step S250, when the parallel verification mode is started, dividing the current identity information based on the information verification requirement of the payer block chain node aiming at the current identity information to obtain a packet information packet.

For example, the current identity information may consist of different packets.

And step S260, verifying the grouping information packet based on the parallel verification mode so as to realize identity information verification of the payee block chain node.

It can be understood that, when the contents described in the above steps S210 to S260 are implemented, when it is determined that the current identity information of the payee block chain node is not verified, the remaining verification time of the current identity information is calculated based on the information association degree between different information packets of the current identity information in the current verification time period and the information verification category of the current identity information, then a parallel verification mode for the current identity information is started on the premise that the calculated remaining verification time reaches the set time, then the current identity information is divided based on the information verification requirement of the payer block chain node for the current identity information to obtain grouped information packets, and finally the grouped information packets are verified based on the parallel verification mode to implement the identity information verification of the payee block chain node.

Therefore, the identity information of the payee block chain node can be quickly and accurately verified by cloud verification of the identity information of the payee block chain node and then parallel verification is realized, so that the safety of block chain transaction and block chain payment is ensured on the premise of not influencing the processing efficiency of the block chain node on other business layers.

In a specific implementation, in order to ensure accuracy, comprehensiveness, and reliability of checking the identity information of the payee block chain node, the step S260 may specifically include the following contents described in steps S261 to S262, and the step S260 may perform checking on the packet information packet based on the parallel checking mode to verify the identity information of the payee block chain node.

Step S261, allocating a corresponding parallel verification thread to each group of information packets based on the extracted information characteristics of each group of information packets, and verifying each group of information packets by running each group of parallel verification threads to obtain a verification result.

Step S262, determining whether the payee block link point passes the identity information verification according to the verification result.

Thus, based on the steps S261 to S262, whether the payee block link point passes the identity information verification can be accurately, comprehensively and reliably determined according to the verification results of multiple dimensions, thereby ensuring the security of block chain payment.

Further, in order to ensure the accuracy and timing relationship of the parallel check threads for checking the packets, the step S261 assigns corresponding parallel check threads to each group of packets based on the extracted information characteristics of each group of packets, and checks each group of packets by running each group of parallel check threads to obtain a check result, which may further include the following steps S2611 to S2616.

Step S2611, aiming at each group of information packet, obtaining the message head identification of each message information in the information packet and the message correlation degree between every two message information in the information packet; the message correlation is used for representing the relevance of every two pieces of message information in a time sequence, and the greater the message correlation is, the greater the relevance of every two pieces of message information in the time sequence is, and the closer the generation time of every two pieces of message information is.

Step S2612, determining an identifier classification list corresponding to the packet header identifier, and determining a correlation matrix corresponding to the packet correlation, where the identifier classification list includes a plurality of list elements, the correlation matrix includes a plurality of matrix elements, the number of the list elements is the same as the number of the matrix elements, each of the list elements and each of the matrix elements have different element identification degrees, and the element identification degrees of the list elements in the identifier classification list have a hierarchical order from large to small.

Step S2613, extract the said message header label in the element attribute information of any list element of the said label classification tabulation, confirm the matrix element with minimum element recognition degree in the said correlation matrix as waiting to correct the element; the element attribute information is used for representing the identification characteristics of the message header identification corresponding to the list element; adding the element attribute information to the element to be corrected based on a message protocol distribution queue between message information in each group of information packets, and obtaining correction attribute information corresponding to the element attribute information from the element to be corrected; constructing a time sequence mapping list between the message header identification and the message correlation degree based on the attribute association track between the element attribute information and the correction attribute information; the time sequence mapping list is used for indicating a one-to-one mapping relation between the message header identification and the message correlation degree.

Step S2614, obtaining corrected attribute information in the element to be corrected by using the comprehensive attribute value of the correction attribute information as a reference attribute value, mapping the corrected attribute information to a list element where the element attribute information is located according to a path priority of a mapping path corresponding to each list unit in the time sequence mapping list, so as to obtain mapping attribute information corresponding to the corrected attribute information in the list element where the element attribute information is located, and determining that a current attribute value of the mapping attribute information is an attribute value to be matched.

Step S2615, obtaining the element attribute information and mapping the element attribute information to an information queue in the element to be corrected, and based on the attribute association between the mapping attribute information and the unit attribute information corresponding to the plurality of queue units in the information queue, sequentially acquiring target matrix elements corresponding to the attribute values to be matched in the correlation matrix according to the magnitude sequence of the element identification degrees until a first relative position coefficient of a matrix element where the target matrix element is located is consistent with a second relative position coefficient of a list element of the attribute values to be matched in the identification classification list, stopping acquiring the target matrix element in the next matrix element, extracting information characteristics of corresponding information packets according to the target matrix elements, listing the information characteristics in a characteristic graph data form and generating current graph data corresponding to the information characteristics; determining an information verification dimension of the information characteristic based on the number of graph data nodes in the current graph data and a transmission path between the graph data nodes, and selecting a parallel detection thread corresponding to a configuration verification dimension which is the same as the information verification dimension as a parallel verification thread of the information packet; and the parallel check threads correspond to the information packets one to one.

Step S2616, by running each group of parallel verification threads, each group of information packets is verified based on the corresponding information verification dimension to obtain a verification result.

In this way, based on the steps S2611 to S2616, the accuracy and timing relationship of the parallel check thread to check the packet can be ensured.

In one possible embodiment, the process of step S2616, by running each group of parallel check threads, checks each group of packets based on the corresponding information check dimension to obtain the check result, may exemplarily include the following steps S2616 a-S2616 d.

Step S2616a, based on the first record mark and the second record mark which are extracted and used for recording the dimension cluster distribution of the information check dimension of each group of parallel check threads, determining the logic weight of a plurality of identification factors which are to be marked and used for identifying the information assembly logic corresponding to the information packet, and the interference coefficient among different identification factors; each second record mark is a continuous dimension clustering distribution record of the information assembly logic corresponding to the information packet, and each first record mark is a discrete dimension clustering distribution record.

Step S2616b, based on the determined logical weights of the plurality of identification factors and the interference coefficients between different identification factors, marks the plurality of identification factors such that the logical weights of the marked identification factors are greater than the set weight and the interference coefficients between the screened identification factors are less than the set coefficient.

Step S2616c, for the determined current thread state parameter of the parallel check thread, according to a mapping value of the information check dimension corresponding to the parallel check thread under each of the marked identification factors, determining whether the dimension cluster distribution record of the parallel check thread matches with the information assembly logic corresponding to the information packet corresponding to the parallel check thread.

Step S2616d, if it is determined that the dimension cluster distribution record of the parallel verification thread matches the information assembly logic corresponding to the information packet corresponding to the parallel verification thread, verifying the target information characteristics of each group of information packets in each information verification dimension based on the information assembly logic to obtain an initial result, and fusing the initial results to obtain the verification result.

It can be understood that based on the above-mentioned steps S2616 a-S2616 d, each group of packets can be checked based on different information checking dimensions to obtain checking results with different dimensions, so as to ensure the comprehensiveness and integrity of the checking results.

In a specific implementation process, the determining, according to the verification result, whether the payee block link point passes the identity information verification in step S262 may specifically include the following steps: after the verification confidence coefficient and the verification aging coefficient of each verification result are determined, a confidence coefficient sequencing queue of the verification confidence coefficient and an aging length sequencing queue of the verification aging coefficient are obtained, wherein the verification confidence coefficient carries a confidence coefficient label, and the verification aging coefficient carries an effective time period label; acquiring each queue element in the confidence degree sequencing queue and each queue element in the aging long and short sequencing queue to obtain a queue element pairing list; determining the matching degree between any two queue elements in the queue element pairing list to obtain an original matching degree set; adjusting the matching degree smaller than a target threshold value in the original matching degree set to be a target threshold value to obtain a current matching degree set; and processing the current matching degree set to obtain a cooperative checking result, wherein the cooperative checking result is used for indicating that the confidence coefficient label and the valid time interval label are mutually matched labels or mutually unmatched labels, and when the confidence coefficient label and the valid time interval label are mutually matched labels, the payee block link point is judged to pass the identity information check, and when the confidence coefficient label and the valid time interval label are mutually unmatched labels, the payee block link point is judged not to pass the identity information check. Therefore, whether the payee block link point passes the identity information verification or not can be determined based on the matching result of the confidence degree label and the valid time period label, and the accuracy and timeliness of the identity information verification can be ensured.

On the basis, processing the current matching degree set to obtain a collaborative verification result, specifically including:

determining historical transaction records of the payee block chain node according to the current matching degree set, and removing invalid transaction records in the historical transaction records by adopting a transaction category screening rule to obtain a plurality of valid transaction records; the historical transaction record is a comprehensive transaction record comprising invalid transaction records for recording abnormal transaction results;

in the next step, respectively determining multiple groups of transaction node information of each effective transaction record according to the current transaction evaluation value of the payee block chain node; determining target transaction node information in the transaction node information of the same node type; the node type of the transaction node information is used for representing the business event type of the transaction node information in the valid transaction record; the determining of the target transaction node information in the transaction node information of the same node category includes: determining an event identification value of each transaction node information; the event identification value of the transaction node information is a transaction event calibration value of the transaction node information; according to the event identification value, recognizing multiple groups of node parameter information in the transaction node information of the same node type by adopting a pre-trained event recognition model, and determining target transaction node information based on repeated information among the multiple groups of node parameter information;

in the next step, information of a plurality of target transaction nodes of different node types is merged to obtain transaction behavior portrait information of the payee block chain node, a verification result corresponding to the matching degree corresponding to the transaction behavior portrait information is selected from the current matching degree set, a cooperative verification weight is distributed to the verification result, and the verification result is weighted according to the cooperative verification weight to obtain the cooperative verification result.

Therefore, by applying the steps, the integrity of the cooperative verification result can be ensured, and the loss during the weighting of the verification result is avoided.

In a possible embodiment, in order to ensure accurate partition of packet information packets and avoid cross interference between packet information packets, the partition of the current identity information based on the information verification requirement of the payer block chain node for the current identity information to obtain packet information packets in the implementation process described in step S250 may specifically include the following contents described in step S251 to step S253.

Step S251, determining a service item to which an event belongs in an expected verification event of the information verification requirement, where the service item to which the event belongs is used to characterize a service item executed by a payee block chain node corresponding to the expected verification event.

Step S252, processing the service item to which the event belongs through an item classification list and an item detection list in a service item list in a preset service item database, and determining service item data matched with the service item to which the event belongs.

Step S253, based on the service item data, determining data access authority information matched with the service item to which the event belongs through interactive service behavior data in a service item list in the preset service item database; and identifying the business item to which the event belongs through an authority pairing list of the preset business item database based on the data access authority information matched with the business item to which the event belongs so as to output an identification result of the business item to which the event belongs, which is identified by the authority, and dividing the current identity information according to an information division identifier in the identification result to obtain a grouping information packet.

Thus, by applying the above steps S251 to S253, accurate division of packet packets can be ensured, and cross interference between packet packets can be avoided.

In an alternative embodiment, in order to accurately calculate the remaining verification time of the current identity information, the step S22 of calculating the remaining verification time of the current identity information based on the information association degree between different information packets of the current identity information in the current verification period and the information verification category of the current identity information may include the following steps S221 to S223.

Step S221, determining histogram distribution characteristics corresponding to a correlation degree histogram of information correlation degrees among different information packets of the current identity information in a current verification period and histogram updating frequency of the correlation degree histogram, wherein the histogram updating frequency represents correlation degree updating heat of the correlation degree histogram of the information correlation degrees among the different information packets of the current identity information in the current verification period; the histogram update frequency includes at least: and the current updating heat and the historical updating heat mean value of the association degree histogram of the information association degree between different information packets of the current identity information in the current verification period.

Step S222, obtaining a category information feature corresponding to the information verification category and the histogram distribution feature, where the category information feature includes an information tracing level of pre-extracted category information, and the information tracing level of the category information indicates a correlation degree heat weight corresponding to the histogram distribution feature and located in the category information feature; the information tracing level of the category information at least comprises: and representing the current relevance degree heat weight and the historical relevance degree heat weight of the relevance degree histogram corresponding to the category dimension contained in the category information feature.

Step S223, according to the histogram distribution feature and the histogram update frequency, searching for a target trace back level matching the information association degree between different information packets of the current identity information in the current verification period in the category information feature, determining a mapping trace back duration of the target trace back level according to the matching degree, and calculating the remaining verification time of the current identity information according to the mapping trace back duration.

In this way, based on the contents described in the above steps S221 to S223, the remaining verification time of the current identity information can be accurately calculated.

In step S23, the set consumed time is determined according to the current remaining memory resources of the big data service center and the payment order information of the current block chain payment of the payee block chain node, and further, the set consumed time may be specifically determined through the following steps a to d.

Step a, determining the residual resource percentage corresponding to the current residual memory resource of the big data service center.

And b, extracting the number of the order processing nodes in the payment order information and the event information corresponding to each order processing node.

And c, determining a first time consumption weight based on the percentage of the remaining resources, and generating a second time consumption weight based on the event response delay corresponding to each event message and the number of the order processing nodes.

Step d, weighting the reference consumed time by adopting the first consumed time weight and the second consumed time weight to obtain the set consumed time; and obtaining the reference consumed time based on the original configuration information of the big data server center.

Therefore, when the contents described in the steps a to d are applied, the setting time can be accurately determined, and the accurate judgment of the subsequent identity verification process is ensured.

Based on the same inventive concept as in the foregoing embodiment, there is also provided a cloud computing-based blockchain payment processing apparatus 300 as shown in fig. 3, where the apparatus is applied to the big data service center 110 in fig. 1, and specifically includes the following functional modules:

the verification judging module 310 is configured to judge whether verification of current identity information of a payee block link node is completed when verifying the current identity information;

a time consumption calculating module 320, configured to calculate remaining verification time consumption of the current identity information based on information association degrees between different information packets of the current identity information in a current verification time period and an information verification category of the current identity information when the current identity information is not verified;

a time-consuming judging module 330, configured to judge whether the calculated remaining verification time reaches a set time-consuming;

a parallel starting module 340, configured to start a parallel verification mode for the current identity information on the premise that the calculated remaining verification time reaches a set time;

an information partitioning module 350, configured to, when the parallel verification mode is started, partition the current identity information based on an information verification requirement of a payer block link point for the current identity information to obtain a packet information packet;

and a parallel verification module 360, configured to verify the packet information packet based on the parallel verification mode, so as to verify the identity information of the payee block chain node.

On the basis of the above, please refer to fig. 4, which shows a schematic diagram of a hardware structure of the big data service center 110, where the big data service center 110 includes a memory 112, a processor 114, and a computer program stored on the memory 112 and capable of running on the processor 114, and the processor 114 implements the steps of the above method when executing the program.

Further, a computer-readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method.

The algorithms and displays presented herein are not inherently related to any particular computer, virtual machine, or other apparatus. Various general purpose systems may also be used with the teachings herein. The required structure for constructing such a system will be apparent from the description above. In addition, this application is not directed to any particular programming language. It will be appreciated that a variety of programming languages may be used to implement the teachings of the present application as described herein, and any descriptions of specific languages are provided above to disclose the best modes of the present application.

In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the application may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure the understanding of this description.

Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the application, various features of the application are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: this application is intended to cover such departures from the present disclosure as come within known or customary practice in the art to which this invention pertains. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this application.

Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this application (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this application (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.

Moreover, those skilled in the art will appreciate that while some embodiments herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the application and form different embodiments. For example, in the following claims, any of the claimed embodiments may be used in any combination.

The various component embodiments of the present application may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functionality of some or all of the components of a gateway, proxy server, system according to embodiments of the present application. The present application may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present application may be stored on a computer readable medium or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.

It should be noted that the above-mentioned embodiments illustrate rather than limit the application, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The application may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.

Based on the above, the present application also provides two possible embodiments, which are embodiment a and embodiment B, respectively, which will be described below in their entirety.

The description about embodiment a is as follows.

A1. A block chain payment processing method based on cloud computing comprises the following steps:

when the current identity information is not verified, calculating the remaining verification time consumption of the current identity information based on the information association degree of the current identity information between different information packets in the current verification period and the information verification category of the current identity information, specifically comprising: determining histogram distribution characteristics corresponding to a correlation degree histogram of information correlation degrees among different information packets of the current identity information in a current verification period and histogram updating frequency of the correlation degree histogram, wherein the histogram updating frequency represents correlation degree updating heat of the correlation degree histogram of the information correlation degrees among the different information packets of the current identity information in the current verification period; the histogram update frequency includes at least: the current updating heat and the historical updating heat mean value of a correlation degree histogram representing the information correlation degree of the current identity information among different information packets in the current verification period; acquiring category information characteristics corresponding to the information verification category and the histogram distribution characteristics, wherein the category information characteristics comprise information tracing levels of pre-extracted category information, and the information tracing levels of the category information represent association degree heat weights which are located in the category information characteristics and correspond to the histogram distribution characteristics; the information tracing level of the category information at least comprises: representing the current relevance degree heat weight and the historical relevance degree heat weight of a relevance degree histogram corresponding to the category dimension contained in the category information feature; according to the histogram distribution characteristics and the histogram updating frequency, searching a target tracing level matched with the information correlation degree of the current identity information among different information packets in the current verification time period in the category information characteristics, determining the mapping tracing duration of the target tracing level according to the matching degree, and calculating the residual verification time consumption of the current identity information through the mapping tracing duration;

judging whether the calculated residual verification time reaches a set time;

A2. According to the method described in a1, verifying the packet information packet based on the parallel verification pattern to verify the identity information of the payee block chain node includes:

distributing corresponding parallel verification threads for each group of information packets based on the extracted information characteristics of each group of information packets, and verifying each group of information packets by running each group of parallel verification threads to obtain a verification result;

and judging whether the payee block link point passes the identity information verification or not according to the verification result.

A3. According to the method described in a2, allocating corresponding parallel verification threads to each group of packets based on the extracted information characteristics of each group of packets, and performing verification on each group of packets by running each group of parallel verification threads to obtain a verification result, including:

aiming at each group of information packets, acquiring a message header identifier of each piece of message information in the information packet and message correlation between every two pieces of message information in the information packet; the message correlation degree is used for representing the relevance of every two pieces of message information on a time sequence, and the greater the message correlation degree is, the greater the relevance of every two pieces of message information on the time sequence is, and the closer the generation time of every two pieces of message information is;

determining an identifier classification list corresponding to the message header identifier, and determining a correlation matrix corresponding to the message correlation, wherein the identifier classification list comprises a plurality of list elements, the correlation matrix comprises a plurality of matrix elements, the number of the list elements is the same as that of the matrix elements, each list element and each matrix element respectively have different element identification degrees, and the element identification degrees of the list elements in the identifier classification list have a hierarchical order from large to small;

extracting element attribute information of the message header identifier in any list element of the identifier classification list, and determining a matrix element with the minimum element identification degree in the correlation matrix as an element to be corrected; the element attribute information is used for representing the identification characteristics of the message header identification corresponding to the list element; adding the element attribute information to the element to be corrected based on a message protocol distribution queue between message information in each group of information packets, and obtaining correction attribute information corresponding to the element attribute information from the element to be corrected; constructing a time sequence mapping list between the message header identification and the message correlation degree based on the attribute association track between the element attribute information and the correction attribute information; the time sequence mapping list is used for indicating a one-to-one mapping relation between the message header identification and the message correlation degree;

acquiring corrected attribute information in the element to be corrected by taking the comprehensive attribute value of the corrected attribute information as a reference attribute value, mapping the corrected attribute information to a list element where the element attribute information is located according to the path priority of a mapping path corresponding to each list unit in the time sequence mapping list, so as to obtain mapping attribute information corresponding to the corrected attribute information in the list element where the element attribute information is located, and determining the current attribute value of the mapping attribute information as an attribute value to be matched;

acquiring the element attribute information, mapping the element attribute information to an information queue in the element to be corrected, and based on the attribute association degree between the mapping attribute information and unit attribute information corresponding to a plurality of queue units in the information queue, sequentially acquiring target matrix elements corresponding to the attribute values to be matched in the correlation matrix according to the magnitude sequence of the element identification degrees until a first relative position coefficient of a matrix element where the target matrix element is located is consistent with a second relative position coefficient of a list element of the attribute values to be matched in the identification classification list, stopping acquiring the target matrix element in the next matrix element, extracting information characteristics of corresponding information packets according to the target matrix elements, listing the information characteristics in a characteristic graph data form and generating current graph data corresponding to the information characteristics; determining an information verification dimension of the information characteristic based on the number of graph data nodes in the current graph data and a transmission path between the graph data nodes, and selecting a parallel detection thread corresponding to a configuration verification dimension which is the same as the information verification dimension as a parallel verification thread of the information packet; the parallel check threads correspond to the information packets one by one;

and verifying each group of information packets based on the corresponding information verification dimension by running each group of parallel verification threads to obtain a verification result.

A4. According to the method described in a3, by running each group of parallel check threads, checking each group of packets based on corresponding information check dimensions to obtain a check result, the method includes:

determining logic weights of a plurality of identification factors to be marked for identifying information assembly logic corresponding to an information packet and interference coefficients among different identification factors based on the extracted first record identification and second record identification which are used for recording the dimension clustering distribution of the information verification dimensions of each group of parallel verification threads; each second record mark is a continuous dimension clustering distribution record of information assembly logic corresponding to the information packet, and each first record mark is a discrete dimension clustering distribution record;

marking the plurality of identification factors based on the determined logic weights of the plurality of identification factors and interference coefficients among different identification factors, so that the logic weights of the marked identification factors are larger than the set weight, and the interference coefficients among the screened identification factors are smaller than the set coefficient;

according to the determined current thread state parameter of the parallel verification thread, judging whether the dimension clustering distribution record of the parallel verification thread is matched with the information assembly logic corresponding to the information packet corresponding to the parallel verification thread according to the mapping value of the information verification dimension corresponding to the parallel verification thread under each identification factor in the marked identification factors;

and if the fact that the dimension cluster distribution records of the parallel verification threads are matched with the information assembly logic corresponding to the information packets corresponding to the parallel verification threads is determined, checking the target information characteristics of each group of information packets under each information verification dimension based on the information assembly logic to obtain an initial result, and fusing the initial result to obtain the verification result.

A5. The method of any one of a2-a4, wherein determining whether the payee chunk node passes identity verification based on the verification comprises:

after the verification confidence coefficient and the verification aging coefficient of each verification result are determined, a confidence coefficient sequencing queue of the verification confidence coefficient and an aging length sequencing queue of the verification aging coefficient are obtained, wherein the verification confidence coefficient carries a confidence coefficient label, and the verification aging coefficient carries an effective time period label; acquiring each queue element in the confidence degree sequencing queue and each queue element in the aging long and short sequencing queue to obtain a queue element pairing list; determining the matching degree between any two queue elements in the queue element pairing list to obtain an original matching degree set; adjusting the matching degree smaller than a target threshold value in the original matching degree set to be a target threshold value to obtain a current matching degree set; and processing the current matching degree set to obtain a cooperative checking result, wherein the cooperative checking result is used for indicating that the confidence coefficient label and the valid time interval label are mutually matched labels or mutually unmatched labels, and when the confidence coefficient label and the valid time interval label are mutually matched labels, the payee block link point is judged to pass the identity information check, and when the confidence coefficient label and the valid time interval label are mutually unmatched labels, the payee block link point is judged not to pass the identity information check.

A6. According to the method of a5, processing the current matching degree set to obtain a collaborative verification result, including:

respectively determining multiple groups of transaction node information of each effective transaction record according to the current transaction evaluation value of the payee block chain node; determining target transaction node information in the transaction node information of the same node type; the node type of the transaction node information is used for representing the business event type of the transaction node information in the valid transaction record; the determining of the target transaction node information in the transaction node information of the same node category includes: determining an event identification value of each transaction node information; the event identification value of the transaction node information is a transaction event calibration value of the transaction node information; according to the event identification value, recognizing multiple groups of node parameter information in the transaction node information of the same node type by adopting a pre-trained event recognition model, and determining target transaction node information based on repeated information among the multiple groups of node parameter information;

merging a plurality of target transaction node information of different node types to obtain transaction behavior portrait information of the payee block chain node, selecting a verification result corresponding to the matching degree corresponding to the transaction behavior portrait information from the current matching degree set, distributing cooperative verification weight to the verification result, and weighting the verification result according to the cooperative verification weight to obtain the cooperative verification result.

A7. The method of claim a1 or a2, partitioning the current identity information based on information verification requirements of payer block chain nodes for the current identity information, resulting in a grouped information package, comprising:

determining a business item to which an event belongs in an expected verification event of the information verification requirement, wherein the business item to which the event belongs is used for representing a business item executed by a payee block chain node corresponding to the expected verification event;

processing the business items to which the events belong through an item classification list and an item detection list in a business item list in a preset business item database, and determining business item data matched with the business items to which the events belong;

determining data access authority information matched with the business item to which the event belongs through interactive business behavior data in a business item list in the preset business item database based on the business item data; and identifying the business item to which the event belongs through an authority pairing list of the preset business item database based on the data access authority information matched with the business item to which the event belongs so as to output an identification result of the business item to which the event belongs, which is identified by the authority, and dividing the current identity information according to an information division identifier in the identification result to obtain a grouping information packet.

A8. A big data service center comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor when executing the program implementing the steps of the method of any of a1-a 7.

The description about embodiment B is as follows.

B1. A block chain payment processing method based on cloud computing comprises the following steps:

judging whether the calculated residual verification time reaches a set time; the set consumed time is determined according to the current residual memory resources of the big data service center and the payment order information of the current block chain payment of the payee block chain node;

B2. According to the method of B1, verifying the packet based on the parallel verification pattern to verify the identity information of the payee block chain node includes:

B3. According to the method described in B2, allocating a corresponding parallel verification thread to each group of packets based on the extracted information characteristics of each group of packets, and performing verification on each group of packets by running each group of parallel verification threads to obtain a verification result, including:

B4. According to the method described in B3, by running each group of parallel check threads, checking each group of packets based on the corresponding information check dimension to obtain a check result, the method includes:

B5. The method of any one of B2-B4, wherein determining whether the payee chunk node passes identity verification based on the verification comprises:

B6. According to the method of B5, processing the current matching degree set to obtain a collaborative verification result, including:

B7. The method of claim B1 or B2, partitioning the current identity information based on information verification requirements of payer block nexus for the current identity information, resulting in a grouped information package, comprising:

B8. A big data service center comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor when executing the program implementing the steps of the method of any of B1-B7.

Claims

1. A block chain payment processing method based on cloud computing is characterized by comprising the following steps:

the identity information of the block chain node of the payee is verified by performing the following steps in a parallel verification mode:

2. The method of claim 1, wherein running each set of parallel check threads to check each set of packets based on corresponding information check dimensions to obtain a check result comprises:

3. The method of claim 1, wherein the packet is determined by:

judging whether the calculated residual verification time reaches a set time;

when the parallel verification mode is started, the current identity information is divided based on the information verification requirement of the payer block link point for the current identity information, and a grouping information packet is obtained.

4. The method of claim 3, wherein calculating the remaining verification time of the current identity information based on the information association degree between different information packets of the current identity information in the current verification period and the information verification category of the current identity information comprises:

determining histogram distribution characteristics corresponding to a correlation degree histogram of information correlation degrees among different information packets of the current identity information in a current verification period and histogram updating frequency of the correlation degree histogram, wherein the histogram updating frequency represents correlation degree updating heat of the correlation degree histogram of the information correlation degrees among the different information packets of the current identity information in the current verification period; the histogram update frequency includes at least: the current updating heat and the historical updating heat mean value of a correlation degree histogram representing the information correlation degree of the current identity information among different information packets in the current verification period;

acquiring category information characteristics corresponding to the information verification category and the histogram distribution characteristics, wherein the category information characteristics comprise information tracing levels of pre-extracted category information, and the information tracing levels of the category information represent association degree heat weights which are located in the category information characteristics and correspond to the histogram distribution characteristics; the information tracing level of the category information at least comprises: representing the current relevance degree heat weight and the historical relevance degree heat weight of a relevance degree histogram corresponding to the category dimension contained in the category information feature;

according to the histogram distribution characteristics and the histogram updating frequency, searching a target tracing level matched with the information association degree of the current identity information among different information packets in the current verification time period in the category information characteristics, determining the mapping tracing duration of the target tracing level according to the matching degree, and calculating the residual verification time consumption of the current identity information through the mapping tracing duration.

5. The method of claim 3, wherein partitioning the current identity information based on information verification requirements of payer block nodes for the current identity information to obtain grouped information packets comprises:

6. A big data service center comprising a blockchain payment processing apparatus integrated with a plurality of functional modules, the plurality of functional modules implementing the steps of the method of any one of claims 1 to 5 when run.

7. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 5.

8. A big data service center comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method of any of claims 1-5 when executing the program.