CN112286724B

CN112286724B - Data recovery processing method based on block chain and cloud computing center

Info

Publication number: CN112286724B
Application number: CN202011150651.0A
Authority: CN
Inventors: 袁道红; 曹青青
Original assignee: Nongfu Shop Development Group Co ltd
Current assignee: Nongfu shop Development Group Co.,Ltd.
Priority date: 2020-10-24
Filing date: 2020-10-24
Publication date: 2021-12-07
Anticipated expiration: 2040-10-24
Also published as: CN112286724A; CN113467992A; CN113467991A

Abstract

The embodiment of the application provides a data recovery processing method based on a block chain and cloud computing and a cloud computing center, firstly, a pre-recovery information chain of a plurality of recovery service table items is determined based on an object to be recovered, the pre-recovery information chain is respectively input into a plurality of channel units in a block chain recovery channel, each channel unit is subjected to at least one recovery node matching to obtain at least one recovery node unit, the at least one recovery node matching is carried out based on a related recovery object, the related recovery object is fused with the recovery node units extracted from other channel units of the plurality of channel units, so that the recovery node units extracted from different channel units can be exchanged and fused at least once, and then the recovery node units of different levels can be clustered to improve the representation capability of data recovery by enriching the levels of the recovery node units, thereby the recovery effect is better.

Description

Data recovery processing method based on block chain and cloud computing center

Technical Field

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

Background

The traditional handwriting batch record is suitable for almost all environments and depends on manual record, however, the authenticity of the data is not examined and is easy to be counterfeited; data cannot be recorded in time, and post writing is easily caused; the data is stored after being recorded by paper, and is easy to lose or damage and cannot be recovered; the writer has different writing, which is easy to cause confusion of recognition; too much data is inconvenient to retrieve after the data is stored for a long time.

In the related technology, the electronic batch records read production data in real time by using configuration and are stored in the database to form the electronic batch records, although the timeliness of the records is improved, the data is automatically read at fixed intervals by a system, the data can be artificially and deliberately modified, and the reliability needs to be enhanced.

Based on this, in the research process, the inventor arranges the generated block data packets according to the preset rule, so that the confidence coefficient of the artificial deliberate modification can be reduced, and the block data packets are further stored in the block chain, and whether the data is falsified or not can be conveniently judged at the first time in the following by using the characteristics of the blocks, so that the reliability enhancement is performed by using the characteristics of the block chain. For the electronic batch recording security service for security protection, after the security protection is passed, a recovery process of some key data may be involved, in a conventional scheme, a hierarchy of a recovery node unit is often single, so that a characterization capability of data recovery is weak, and a data recovery effect is poor in a data recovery process of realizing a large data volume level.

Disclosure of Invention

In order to overcome at least the above disadvantages in the prior art, an object of the present application is to provide a data recovery processing method based on a block chain and cloud computing and a cloud computing center, where a pre-recovery information chain of multiple recovery service table entries is determined based on an object to be recovered, the pre-recovery information chain is input to multiple channel units in a block chain recovery channel, and each channel unit performs at least one recovery node matching to obtain at least one recovery node unit. Wherein at least one restoration node matching for each channel unit is performed based on the associated restoration object fused with the restoration node units extracted from the other channel units of the plurality of channel units. Therefore, at least one time of exchange and fusion can be carried out between the recovery node units extracted from different channel units, and then the recovery node units of different layers can be clustered, so that the representation capability of data recovery is improved by enriching the layers of the recovery node units, and the recovery effect is better when the recovery node units extracted from the block chain recovery channel obtain the recovery queue result of the access request parameters.

In a first aspect, the present application provides a data recovery processing method based on a block chain and cloud computing, which is applied to a cloud computing center, where the cloud computing center is in communication connection with a plurality of electronic batch recording terminals, and the method includes:

acquiring a safety protection parameter corresponding to each set safety protection item, analyzing an access request parameter of the target record financial business based on the safety protection parameter, and acquiring a corresponding access service object after safety protection is passed;

acquiring a corresponding object to be recovered based on the access service object, and determining a pre-recovery information chain of a plurality of recovery service table entries based on the object to be recovered;

respectively inputting the pre-recovery information chains into a plurality of channel units in a block chain recovery channel, and performing at least one recovery node matching through the channel units to obtain at least one recovery node unit; wherein at least one recovery node matching by the channel units is performed based on an associated recovery object that fuses recovery node units extracted from other channel units of the plurality of channel units;

clustering the recovery node units output by the channel units to obtain a cluster recovery node unit, obtaining a recovery queue result of the object to be recovered under the access request parameter based on the cluster recovery node unit, and performing data recovery based on the recovery queue result of the object to be recovered under the access request parameter.

In a possible implementation manner of the first aspect, the method further includes:

taking one of the plurality of channel units as a target channel unit;

acquiring a first recovery node unit extracted by the target channel unit and a second recovery node unit extracted by other channel units except the target channel unit in the plurality of channel units;

when the recovery service table entry of the second recovery node unit does not match the recovery service table entry of the first recovery node unit, performing tracking marking on the second recovery node unit, wherein the recovery service table entry of the second recovery node unit after tracking marking is the same as the recovery service table entry of the first recovery node unit;

performing recovery node matching on the fusion result of the second recovery node unit and the first recovery node unit after tracking and marking through the target channel unit;

wherein the number of the second recovery node units is at least two; the method further comprises the following steps:

when a second recovery node unit with recovery service table entries not matched with the recovery service table entries of the first recovery node unit and a second recovery node unit with recovery service table entries matched with the recovery service table entries of the first recovery node unit exist at the same time, tracking and marking are carried out on the second recovery node unit with the recovery service table entries not matched with the recovery service table entries of the first recovery node unit, anti-tracking and marking are carried out on the second recovery node unit with the recovery service table entries matched with the recovery service table entries of the first recovery node unit, and the recovery service table entries of the second recovery node unit after tracking and anti-tracking are the same as the recovery service table entries of the first recovery node unit;

performing recovery node matching on the fusion result of the second recovery node unit after the tracking mark, the second recovery node unit after the anti-tracking mark and the first recovery node unit through the target channel unit;

wherein the method further comprises:

when the recovery service table entry of the second recovery node unit matches the recovery service table entry of the first recovery node unit, performing back tracking marking on the second recovery node unit, wherein the recovery service table entry of the second recovery node unit after back tracking marking is the same as the recovery service table entry of the first recovery node unit;

and performing recovery node matching on the fusion result of the second recovery node unit and the first recovery node unit after the back tracking marking through the target channel unit.

In a possible implementation manner of the first aspect, the step of inputting the pre-recovery information chain into a plurality of channel units in a block chain recovery channel, and performing at least one recovery node matching by using the channel units to obtain at least one recovery node unit includes:

respectively inputting the pre-recovery information chains into a plurality of channel units in the block chain recovery channel;

and for one channel unit, carrying out recovery node matching on the corresponding pre-recovery information chain through the channel unit, obtaining a second recovery node unit extracted through other channel units of the plurality of channel units and carrying out compromise matching on the second recovery node unit and a first recovery node unit after the first recovery node unit is obtained through recovery node matching, and continuing to carry out recovery node matching based on compromise matching results so as to alternately carry out recovery node matching and compromise matching.

In a possible implementation manner of the first aspect, the step of determining a pre-recovery information chain of a plurality of recovery service table entries based on the object to be recovered includes:

performing index matching of the recovery service table items on the object to be recovered to obtain a plurality of pre-recovery information chains of different recovery service table items;

the step of inputting the pre-recovery information chain into a plurality of channel units in a block chain recovery channel respectively, and obtaining at least one recovery node unit by performing at least one recovery node matching through the channel units comprises:

respectively inputting the pre-recovery information chains into a plurality of channel units in the block chain recovery channel; the pre-recovery information chains are respectively in one-to-one correspondence with one of the plurality of channel units;

performing at least one recovery node matching on the corresponding pre-recovery information chain through the channel unit;

the extracted recovery service table entry of the recovery node unit is consistent with the recovery service table entry of the pre-recovery information chain corresponding to the channel unit.

In a possible implementation manner of the first aspect, the pre-recovery information chain at least includes a first pre-recovery information chain, a second pre-recovery information chain, and a third pre-recovery information chain, and the block chain recovery channel includes a first channel unit, a second channel unit, and a third channel unit, where the first pre-recovery information chain, the second pre-recovery information chain, and the third pre-recovery information chain respectively correspond to the pre-recovery information chains of the logic failure data, the hardware failure data, and the RAID data of the disk array, and the first channel unit, the second channel unit, and the third channel unit respectively correspond to the channel units of the logic failure data, the hardware failure data, and the RAID data of the disk array;

the respectively inputting the pre-recovery information chain into a plurality of channel units in a block chain recovery channel, and performing at least one recovery node matching through the channel units to obtain at least one recovery node unit includes:

inputting the first pre-recovery information chain into a first channel unit to perform first-stage recovery node matching to obtain a recovery node unit extracted by the first channel unit at a first stage;

clustering the recovery node unit extracted by the first channel unit in the first stage and the second pre-recovery information chain to obtain a corresponding clustered recovery information chain of the second channel unit in the second stage;

acquiring a recovery node unit extracted by the first channel unit in a first stage, wherein the recovery node unit is used as a corresponding clustering recovery information chain of the first channel unit in a second stage;

performing second-stage first recovery node matching on the corresponding clustering recovery information chain of the first channel unit in the second stage through the first channel unit to obtain a recovery node unit extracted by the first channel unit for the first time in the second stage;

performing second-stage first recovery node matching on the corresponding clustering recovery information chain of the second channel unit in the second stage through the second channel unit to obtain a recovery node unit extracted by the second channel unit in the second stage for the first time;

transmitting the recovery node unit extracted by the first channel unit for the first time in the second stage to the second channel unit, and transmitting the recovery node unit extracted by the second channel unit for the first time in the second stage to the first channel unit;

clustering the recovery node units extracted by the first channel unit at the first stage in the second stage and the recovery node units transmitted by the second channel unit through the first channel unit, and performing recovery node matching on a fusion result;

clustering the recovery node units extracted by the second channel unit in the second stage for the first time and the recovery node units transmitted by the first channel unit through the second channel unit, and performing recovery node matching on a fusion result;

clustering the recovery node unit extracted by the first channel unit in the second stage, the recovery node unit extracted by the second channel unit in the second stage and the third pre-recovery information chain to obtain a corresponding clustered recovery information chain of the third channel unit in the third stage;

and performing third-stage recovery node matching on the basis of the recovery node unit extracted by the first channel unit in the second stage through the first channel unit, performing third-stage recovery node matching on the basis of the recovery node unit extracted by the second channel unit in the second stage through the second channel unit, and performing third-stage recovery node matching on the corresponding clustering recovery information chain of the third channel unit in the third stage through the third channel unit.

In a possible implementation manner of the first aspect, the obtaining, based on the cluster recovery node unit, a recovery queue result of the object to be recovered under the access request parameter includes:

determining a recovery model corresponding to the access request parameter;

inputting the cluster recovery node unit into the recovery model, and obtaining a recovery queue result of the object to be recovered under the access request parameter through the recovery model;

the block chain recovery channel and the recovery model configuring step comprises:

acquiring a cluster recovery node unit sample, the block chain recovery channel and the recovery model, wherein a recovery label of the cluster recovery node unit sample is used for representing a labeling result of the cluster recovery node unit sample under the access request parameter;

determining pre-recovery information chain samples of a plurality of recovery service table entries based on the clustering recovery node unit samples;

respectively inputting the pre-recovery information chain samples into a plurality of channel units in the block chain recovery channel, and performing at least one recovery node matching through the channel units to obtain at least one prediction recovery node unit; wherein at least one recovery node matching by the channel units is based on an associated recovery object that fuses to predicted recovery node units extracted from other channel units of the plurality of channel units;

clustering a plurality of recovery node units output by the plurality of channel units to obtain a target prediction recovery node unit;

inputting the target prediction recovery node unit into the recovery model, and obtaining a prediction result of the clustering recovery node unit sample under the access request parameter through the recovery model;

and configuring the block chain recovery channel and the recovery model based on the prediction result and the recovery label.

In a possible implementation manner of the first aspect, the step of obtaining a corresponding object to be restored based on the access service object includes:

acquiring an object to be restored corresponding to the access service object from a preset restoration object set;

the step of inputting the cluster recovery node unit into the recovery model and obtaining the recovery queue result of the object to be recovered under the access request parameter through the recovery model includes:

and inputting the target prediction recovery node unit into the recovery model, and performing recovery analysis on the target prediction recovery node unit through the recovery model to obtain a recovery queue result of the target prediction recovery node unit.

In a possible implementation manner of the first aspect, the clustering the multiple recovery node units output by the multiple channel units to obtain a clustered recovery node unit includes:

acquiring a plurality of recovery node units output by the plurality of channel units, and determining a target recovery node unit of a global recovery service table entry in the plurality of recovery node units;

clustering other recovery node units except the target recovery node unit in the plurality of recovery node units, wherein the recovery service table entries of the other clustered recovery node units are the same as the recovery service table entries of the target recovery node unit;

and listing the other clustered recovery node units and the target recovery node unit to obtain the clustered recovery node unit.

In a possible implementation manner of the first aspect, the obtaining a security protection parameter corresponding to each set security protection item, analyzing an access request parameter of a target record financial transaction based on the security protection parameter, and obtaining a corresponding access service object after security protection is passed includes:

the method comprises the steps that safety protection testing is carried out on target record financial services under each information safety testing interface by calling electronic batch record safety services of the target record financial services subjected to electronic batch record safety service updating in advance to obtain safety protection testing results;

comparing the safety event evaluation attribute of the set safety protection item in the safety protection test result with the safety event comparison attribute in the safety event database corresponding to the set safety protection item;

according to the comparison result, determining safety protection test targets with different evaluation attributes in the safety protection test result, and acquiring test table item operation parameters of the safety protection test targets with different evaluation attributes in each safety protection test link;

and updating the safety protection parameters corresponding to the set safety protection items in the electronic batch record safety service of the target record financial business according to the test table item operation parameters of the safety protection test targets with different evaluation attributes in each safety protection test link, performing safety protection processing on the access request parameters of the target record financial business accessed through the block chain based on the updated safety protection parameters, and obtaining corresponding access service objects after safety protection is passed.

In a second aspect, an embodiment of the present application further provides a data recovery processing apparatus based on a block chain and cloud computing, which is applied to a cloud computing center, where the cloud computing center is in communication connection with a plurality of electronic batch recording terminals, and the apparatus includes:

the acquisition and analysis module is used for acquiring the safety protection parameters corresponding to each set safety protection item, analyzing the access request parameters of the target record financial business based on the safety protection parameters, and acquiring the corresponding access service object after the safety protection is passed;

a determining module, configured to obtain a corresponding object to be restored based on the access service object, and determine, based on the object to be restored, a pre-restoration information chain of multiple restoration service table entries;

the matching module is used for respectively inputting the pre-recovery information chain into a plurality of channel units in a block chain recovery channel, and performing at least one recovery node matching through the channel units to obtain at least one recovery node unit; wherein at least one recovery node matching by the channel units is performed based on an associated recovery object that fuses recovery node units extracted from other channel units of the plurality of channel units;

the data recovery module is used for clustering the recovery node units output by the channel units to obtain a cluster recovery node unit, obtaining a recovery queue result of the object to be recovered under the access request parameter based on the cluster recovery node unit, and performing data recovery based on the recovery queue result of the object to be recovered under the access request parameter.

In a third aspect, an embodiment of the present application further provides a data recovery processing system based on a block chain and cloud computing, where the data recovery processing system based on the block chain and cloud computing includes a cloud computing center and a plurality of electronic batch recording terminals communicatively connected to the cloud computing center;

the cloud computing center is used for:

In a fourth aspect, an embodiment of the present application further provides a cloud computing center, where the cloud computing center includes a processor, a machine-readable storage medium, and a network interface, where the machine-readable storage medium, the network interface, and the processor are connected through a bus system, the network interface is used for being communicatively connected to at least one electronic batch recording terminal, the machine-readable storage medium is used for storing a program, an instruction, or a code, and the processor is used for executing the program, the instruction, or the code in the machine-readable storage medium to execute the data recovery processing method based on a blockchain and cloud computing in the first aspect or any one of possible implementation manners in the first aspect.

In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium, where instructions are stored in the computer-readable storage medium, and when the instructions are executed, the computer executes the method for processing data recovery based on blockchain and cloud computing in the first aspect or any one of the possible implementations of the first aspect.

Based on any one of the above aspects, the method determines pre-recovery information chains of multiple recovery service table entries based on an object to be recovered, and inputs the pre-recovery information chains into multiple channel units in a block chain recovery channel, where each channel unit performs at least one recovery node matching to obtain at least one recovery node unit. Wherein at least one restoration node matching for each channel unit is performed based on the associated restoration object fused with the restoration node units extracted from the other channel units of the plurality of channel units. Therefore, at least one time of exchange and fusion can be carried out between the recovery node units extracted from different channel units, and then the recovery node units of different layers can be clustered, so that the representation capability of data recovery is improved by enriching the layers of the recovery node units, and the recovery effect is better when the recovery node units extracted from the block chain recovery channel obtain the recovery queue result of the access request parameters.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that need to be called in the embodiments are briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.

Fig. 1 is a schematic application scenario diagram of a data recovery processing system based on a blockchain and cloud computing according to an embodiment of the present application;

fig. 2 is a schematic flowchart of a data recovery processing method based on a blockchain and cloud computing according to an embodiment of the present application;

fig. 3 is a functional module schematic diagram of a data recovery processing apparatus based on a blockchain and cloud computing according to an embodiment of the present application;

fig. 4 is a schematic block diagram of structural components of a cloud computing center for implementing the above data recovery processing method based on a blockchain and cloud computing according to an embodiment of the present application.

Detailed Description

The present application will now be described in detail with reference to the drawings, and the specific operations in the method embodiments may also be applied to the apparatus embodiments or the system embodiments.

Fig. 1 is an interaction diagram of a data recovery processing system 10 based on a blockchain and cloud computing according to an embodiment of the present application. The data recovery processing system 10 based on the blockchain and cloud computing may include a cloud computing center 100 and an electronic batch recording terminal 200 communicatively connected to the cloud computing center 100. The blockchain and cloud computing based data recovery processing system 10 shown in fig. 1 is only one possible example, and in other possible embodiments, the blockchain and cloud computing based data recovery processing system 10 may also include only a portion of the components shown in fig. 1 or may also include other components.

In this embodiment, the electronic batch recording terminal 200 may comprise a mobile device, a tablet computer, a laptop computer, etc., or any combination thereof. In some embodiments, the mobile device may include an internet of things device, a wearable device, a smart mobile device, a virtual reality device, an augmented reality device, or the like, or any combination thereof. In some embodiments, the internet of things device may include a control device of a smart appliance device, a smart monitoring device, a smart television, a smart camera, and the like, or any combination thereof. In some embodiments, the wearable device may include a smart bracelet, a smart lace, smart glass, a smart helmet, a smart watch, a smart garment, a smart backpack, a smart accessory, or the like, or any combination thereof. In some embodiments, the smart mobile device may include a smartphone, a personal digital assistant, a gaming device, and the like, or any combination thereof. In some embodiments, the virtual reality device and the augmented reality device may include a virtual reality helmet, virtual reality glass, a virtual reality patch, an augmented reality helmet, augmented reality glass, an augmented reality patch, or the like, or any combination thereof. For example, virtual reality devices and augmented reality devices may include various virtual reality products and the like.

In this embodiment, the cloud computing center 100 and the electronic batch recording terminal 200 in the data recovery processing system 10 based on the block chain and the cloud computing may execute the data recovery processing method based on the block chain and the cloud computing in the following method embodiment in a matching manner, and for a specific step of the cloud computing center 100 and the electronic batch recording terminal 200, reference may be made to the detailed description of the following method embodiment.

In order to solve the technical problem in the foregoing background art, fig. 2 is a schematic flowchart of a data recovery processing method based on a block chain and cloud computing according to an embodiment of the present application, where the data recovery processing method based on a block chain and cloud computing according to the present embodiment may be executed by the cloud computing center 100 shown in fig. 1, and the data recovery processing method based on a block chain and cloud computing is described in detail below.

Step S110, obtaining the corresponding safety protection parameter aiming at each set safety protection project, analyzing the access request parameter of the target record financial business based on the safety protection parameter, and obtaining the corresponding access service object after the safety protection is passed.

In this embodiment, the security protection parameter may be used to represent a parameter instruction for performing an information analysis decision in the security protection process, the target recording financial service may refer to an identification service for recording financial service data, and the access request parameter may refer to a configuration access parameter related to an initiated access request.

Step S120, obtaining the corresponding object to be recovered based on the access service object, and determining the pre-recovery information chain of a plurality of recovery service table entries based on the object to be recovered.

Step S130, inputting the pre-recovery information chain into a plurality of channel units in the block chain recovery channel respectively, and performing at least one recovery node matching through the channel units to obtain at least one recovery node unit.

In this embodiment, at least one time of the recovery node matching by the channel unit is performed based on the associated recovery object, and the associated recovery object is merged with the recovery node unit extracted from other channel units of the plurality of channel units.

Step S140, clustering the plurality of recovery node units output by the plurality of channel units to obtain a cluster recovery node unit, obtaining a recovery queue result of the object to be recovered under the access request parameter based on the cluster recovery node unit, and performing data recovery based on the recovery queue result of the object to be recovered under the access request parameter.

In this embodiment, the result of the recovery queue of the object to be recovered under the access request parameter may be used to represent a recovery instruction running set of the object to be recovered in a subsequent data recovery process, that is, a recovery control instruction for controlling a flow direction relationship of a recovery data node in the data recovery process, so that the computer program is executed according to an execution sequence of the recovery control instructions, and data recovery is performed.

Based on the above steps, in this embodiment, a pre-recovery information chain of multiple recovery service entries is determined based on an object to be recovered, the pre-recovery information chain is respectively input to multiple channel units in a block chain recovery channel, each channel unit performs at least one recovery node matching to obtain at least one recovery node unit, and the at least one recovery node matching is performed based on an associated recovery object, and the associated recovery object is fused with recovery node units extracted from other channel units of the multiple channel units, so that at least one exchange and fusion can be performed between recovery node units extracted from different channel units, and then recovery node units of different levels can be clustered, so that the representation capability of data recovery is improved by enriching the levels of the recovery node units, and the recovery effect is better.

In a possible implementation manner, on the basis of the above scheme, in this embodiment, one of the plurality of channel units may further be taken as a target channel unit, and then a first recovery node unit extracted by the target channel unit and a second recovery node unit extracted by another channel unit except the target channel unit in the plurality of channel units are obtained.

Therefore, when the recovery service table entry of the second recovery node unit does not match the recovery service table entry of the first recovery node unit, the second recovery node unit is tracked and marked, and the recovery service table entry of the second recovery node unit after tracking and marking is the same as the recovery service table entry of the first recovery node unit. Therefore, the recovery node matching can be carried out on the fusion result of the second recovery node unit and the first recovery node unit after the tracking marking through the target channel unit.

Wherein the number of second recovery node units is at least two.

On the basis, when a second recovery node unit with a recovery service table entry not matched with the recovery service table entry of the first recovery node unit and a second recovery node unit with a recovery service table entry matched with the recovery service table entry of the first recovery node unit exist at the same time, tracking marking is carried out on the second recovery node unit with the recovery service table entry not matched with the recovery service table entry of the first recovery node unit, anti-tracking marking is carried out on the second recovery node unit with the recovery service table entry matched with the recovery service table entry of the first recovery node unit, and the recovery service table entry of the second recovery node unit after tracking marking and the recovery service table entry of the second recovery node unit after anti-tracking marking are the same as the recovery service table entry of the first recovery node unit.

In this way, the target channel unit can perform recovery node matching on the fusion result of the second recovery node unit after the tracking mark, the second recovery node unit after the anti-tracking mark and the first recovery node unit.

For another example, on the basis described above, when the recovery service entry of the second recovery node unit matches the recovery service entry of the first recovery node unit, the second recovery node unit is subjected to anti-tracking marking, and the recovery service entry of the second recovery node unit after anti-tracking marking is the same as the recovery service entry of the first recovery node unit. In this way, the target channel unit can be used for performing recovery node matching on the fusion result of the second recovery node unit and the first recovery node unit after the back tracking marking.

In a possible implementation manner, for step S130, in the process of inputting the pre-recovery information chain into a plurality of channel units in the block chain recovery channel respectively, and performing at least one recovery node matching by the channel units to obtain at least one recovery node unit, the following exemplary sub-steps may be implemented, which are described in detail below.

In the substep S131, the pre-recovery information chains are respectively input to a plurality of channel units in the block chain recovery channel.

And a substep S132, for one of the channel units, performing recovery node matching on the corresponding pre-recovery information chain through the channel unit, obtaining a first recovery node unit after the recovery node matching, performing compromise matching on a second recovery node unit extracted through other channel units of the plurality of channel units and the first recovery node unit, and continuing performing recovery node matching based on a compromise matching result so as to alternately perform recovery node matching and compromise matching.

Further, in step S120, in the process of determining the pre-recovery information chains of multiple recovery service table entries based on the object to be recovered, index matching of the recovery service table entries may be performed on the object to be recovered, so as to obtain the pre-recovery information chains of multiple different recovery service table entries.

For example, the recovery information nodes of the object to be recovered for each recovery service table entry may be index-matched, and all the recovery information nodes are spliced according to the association relationship between them, so as to obtain the pre-recovery information chains of a plurality of different recovery service table entries.

Thus, in another parallel possible implementation manner, for step S130, in the process of inputting the pre-recovery information chain into a plurality of channel units in the block chain recovery channel respectively, and performing at least one recovery node matching by the channel units to obtain at least one recovery node unit, the following exemplary sub-steps may be implemented, which are described in detail below.

And a substep S133 of inputting the pre-restoration information chains into a plurality of channel units in the block chain restoration channel, respectively.

The pre-recovery information chains are respectively in one-to-one correspondence with one of the plurality of channel units.

And a substep S134 of performing at least one restoration node matching on the corresponding pre-restored information chain through the channel unit. The extracted recovery service table entry of the recovery node unit is consistent with the recovery service table entry of the pre-recovery information chain corresponding to the channel unit.

In a parallel possible implementation manner, the pre-recovery information chain at least includes a first pre-recovery information chain, a second pre-recovery information chain, and a third pre-recovery information chain, and the block chain recovery channel includes a first channel unit, a second channel unit, and a third channel unit, where the first pre-recovery information chain, the second pre-recovery information chain, and the third pre-recovery information chain respectively correspond to the pre-recovery information chains of the logic failure data, the hardware failure data, and the RAID data of the disk array, and the first channel unit, the second channel unit, and the third channel unit respectively correspond to the channel units of the logic failure data, the hardware failure data, and the RAID data of the disk array.

On this basis, still referring to step S130, in the process of inputting the pre-recovery information chain into the plurality of channel units in the block chain recovery channel respectively, and performing at least one recovery node matching through the channel units to obtain at least one recovery node unit, the following exemplary sub-steps can be implemented, which are described in detail below.

And a substep S135, inputting the first pre-recovery information chain into the first channel unit for the first-stage recovery node matching, so as to obtain a recovery node unit extracted by the first channel unit in the first stage.

And a substep S136, clustering the recovery node unit extracted by the first channel unit in the first stage and the second pre-recovery information chain to obtain a corresponding clustered recovery information chain of the second channel unit in the second stage.

And substep S137, obtaining the recovery node unit extracted by the first channel unit in the first stage, and using the recovery node unit as the corresponding cluster recovery information chain of the first channel unit in the second stage.

And a substep S138, performing second-stage first recovery node matching on the corresponding clustering recovery information chain of the first channel unit in the second stage through the first channel unit to obtain a recovery node unit extracted by the first channel unit in the second stage for the first time.

And in the substep S1391, performing second-stage first recovery node matching on the corresponding clustering recovery information chain of the second channel unit in the second stage through the second channel unit to obtain a recovery node unit extracted by the second channel unit in the second stage for the first time.

In sub-step S1392, the recovery node unit extracted by the first channel unit in the second stage is transferred to the second channel unit, and the recovery node unit extracted by the second channel unit in the second stage is transferred to the first channel unit.

And a substep S1393 of clustering, by the first channel unit, the recovery node unit extracted by the first channel unit in the second stage for the first time and the recovery node unit transmitted by the second channel unit, and performing recovery node matching on the fusion result.

And a substep S1394, clustering the recovery node unit extracted by the second channel unit in the second stage for the first time and the recovery node unit transmitted by the first channel unit through the second channel unit, and performing recovery node matching on the fusion result.

And in the substep S1395, clustering the recovery node unit extracted by the first channel unit in the second stage, the recovery node unit extracted by the second channel unit in the second stage, and the third pre-recovery information chain to obtain a corresponding clustered recovery information chain of the third channel unit in the third stage.

And in the substep S1396, performing, by the first channel unit, third-stage recovery node matching on the basis of the recovery node unit extracted in the second stage by the first channel unit, performing, by the second channel unit, third-stage recovery node matching on the basis of the recovery node unit extracted in the second stage by the second channel unit, and performing, by the third channel unit, third-stage recovery node matching on the corresponding clustering recovery information chain of the third channel unit in the third stage.

Further, in a possible implementation manner, for step S140, in obtaining the result of the recovery queue of the object to be recovered under the access request parameter based on the cluster recovery node unit, the following exemplary sub-steps may be implemented, which are described in detail below.

And a substep S141 of determining a recovery model corresponding to the access request parameter.

And the substep S142, inputting the clustering recovery node unit into a recovery model, and obtaining a recovery queue result of the object to be recovered under the access request parameter through the recovery model.

The configuration of the blockchain recovery channel and the recovery model can be realized by the following exemplary embodiments:

(1) and acquiring a clustering recovery node unit sample, a block chain recovery channel and a recovery model, wherein a recovery label of the clustering recovery node unit sample is used for representing a labeling result of the clustering recovery node unit sample under the access request parameter.

(2) And determining pre-recovery information chain samples of a plurality of recovery service table entries based on the clustering recovery node unit samples.

(3) And respectively inputting the pre-recovery information chain samples into a plurality of channel units in a block chain recovery channel, and performing recovery node matching at least once through the channel units to obtain at least one prediction recovery node unit.

Wherein the at least one restoration node matching by the channel unit is performed based on an associated restoration object fused with the predicted restoration node units extracted from other channel units of the plurality of channel units.

(4) And clustering a plurality of recovery node units output by a plurality of channel units to obtain a target prediction recovery node unit.

(5) And inputting the target prediction recovery node unit into a recovery model, and obtaining a prediction result of the clustering recovery node unit sample under the access request parameter through the recovery model.

(6) And configuring a block chain recovery channel and a recovery model based on the prediction result and the recovery label.

Further, for step S120, in the process of acquiring the corresponding object to be restored based on the access service object, the object to be restored corresponding to the access service object may be acquired from a preset restoration object set.

On the basis, in the above step, in the process of inputting the cluster recovery node unit into the recovery model and obtaining the recovery queue result of the object to be recovered under the access request parameter through the recovery model, the target prediction recovery node unit may be input into the recovery model, and the recovery analysis is performed on the target prediction recovery node unit through the recovery model to obtain the recovery queue result of the target prediction recovery node unit.

Further, in a possible implementation manner, regarding step S140, in the process of clustering a plurality of recovery node units output by a plurality of channel units to obtain a clustered recovery node unit, the following exemplary sub-steps may be implemented, which are described in detail below.

And a substep S143, obtaining a plurality of recovery node units output by the plurality of channel units, and determining a target recovery node unit for globally recovering the service table entry in the plurality of recovery node units.

And a substep S144, clustering other recovery node units except the target recovery node unit in the plurality of recovery node units, wherein the recovery service table entries of the clustered other recovery node units are the same as the recovery service table entries of the target recovery node unit.

And a substep S145, listing other clustered recovery node units and target recovery node units to obtain clustered recovery node units.

Further, in a possible implementation manner, for step S110, in the process of obtaining the security protection parameter corresponding to each set security protection item, and analyzing the access request parameter of the target record financial transaction based on the security protection parameter, after the security protection is passed, the following exemplary sub-steps may be implemented, which are described in detail below.

And a substep S111 of carrying out safety protection test on the target record financial service under each information safety test interface by calling the electronic batch record safety service of the target record financial service after the electronic batch record safety service is updated in advance to obtain a safety protection test result.

And a substep S112, comparing the security event evaluation attribute of the set security protection item in the security protection test result with the security event comparison attribute in the security event database corresponding to the set security protection item.

And a substep S113, determining safety protection test targets with different evaluation attributes in the safety protection test results according to the comparison results, and acquiring test table item operation parameters of the safety protection test targets with different evaluation attributes in each safety protection test link.

And a substep S114 of updating the safety protection parameters corresponding to the set safety protection items in the electronic batch record safety service of the target record financial service according to the test table item operation parameters of the safety protection test targets with different evaluation attributes in each safety protection test link, and performing safety protection processing on the access request parameters of the target record financial service accessed through the block chain based on the updated safety protection parameters.

For example, in this embodiment, in step S111, in the process of invoking the electronic batch record security service of the target record financial transaction subjected to the electronic batch record security service updating in advance, performing the security protection test on the target record financial transaction under each information security test interface to obtain the security protection test result, the security protection test process may be, for example, performing the targeted security protection test on the target record financial transaction under each information security test interface through the electronic batch record security service, so as to obtain the security event evaluation attribute of each set security protection item in the security protection test result. Each safety protection test item corresponds to a safety event evaluation attribute, the safety protection test items can refer to test items under different safety simulation environments, the corresponding safety event evaluation attributes can refer to simulation index parameters generated under the test items, and in addition, setting the safety protection items can refer to completing an application program layer in an updating process.

For example, in the present embodiment, in step S112, in the process of comparing the security event evaluation attribute of the set security item in the security test result with the security event comparison attribute in the security event database corresponding to the set security item, specifically, a parameter change or a parameter difference existing in the security event evaluation attribute and the security event comparison attribute may be compared, so as to determine a security test target with a difference existing in the evaluation attribute in the subsequent security test result.

For example, in the present embodiment, the test table entry operation parameters may refer to configuration parameters used for controlling the whole security protection process during the security protection test process, and these configuration parameters are generally related to the security protection test items. Therefore, according to the test table item operating parameters of the safety protection test target with different evaluation attributes in each safety protection test link, the safety protection parameters corresponding to the set safety protection items in the electronic batch record safety service of the target record financial business are updated, and performing security protection processing on an access request parameter of the target record financial service accessed through the blockchain based on the updated security protection parameter, the specific updating process may be a process of performing item configuration on the running parameters of the test table entry in each safety protection test item, and the specific item configuration process may be performed according to a scheme in the prior art, for example, for a data download item, the project configuration may be performed by a download configuration category corresponding to the data download project, may be performed manually by a developer, or may be performed automatically by a preset automation script.

Based on the design, in the embodiment, the safety event evaluation attribute of the set safety protection item is compared with the safety event database corresponding to the set safety protection item, the safety protection test target with the evaluation attribute difference in the safety protection test result is determined, then the safety protection parameter corresponding to the set safety protection item in the electronic batch record safety service of the target record financial business is automatically updated according to the safety protection test target with the evaluation attribute difference, and the access request parameter of the target record financial business accessed through the block chain is subjected to safety protection processing based on the updated safety protection parameter, so that the safety protection effect of the electronic batch record safety service of the target record financial business is improved, the manual participation is reduced, and the manual resources are saved. In addition, the safety protection parameters are only updated in the whole process, and the prior updating effect of the electronic batch record safety service is not influenced.

For example, in a possible implementation manner, for step S113, in the process of determining, according to the comparison result, the safety protection test target with the evaluation attribute having a difference in the safety protection test result, a plurality of implementation rules may be selected to determine, which may include at least one or any combination of the following:

the first embodiment: determining a newly added safety protection test target in the safety protection test result according to the comparison result of the safety event evaluation attribute of the set safety protection project and the safety event database, wherein the newly added safety protection test target comprises: the number of evaluation attribute elements that do not appear in the security event database but appear in the security event evaluation attributes matches the first set number of evaluation attribute elements, and the degree of attribute influence at each occurrence in the security event evaluation attributes reaches a security protection test target with a first preset degree of influence proportional to the set proportion.

The second embodiment: and determining a failure safety protection test target in the set safety protection project according to the comparison result of the safety event evaluation attribute of the set safety protection project and the safety event database. Fail safe test objectives include: the number of consecutive evaluation attribute elements that appear in the security event database but not in the security event evaluation attribute matches the security protection test target for the second set number of evaluation attribute elements.

Third embodiment: and determining a differentiated safety protection test target with abnormal differentiation in the set safety protection project according to the comparison result of the safety event evaluation attribute of the set safety protection project and the safety event database. Differentiated safety protection test objectives include: and according to the security event database, determining that the event trigger node information is inconsistent with the event trigger node information in the security event evaluation attribute.

For example, in one possible implementation manner, for the third implementation manner, for candidate security protection test targets whose attribute influence degree matches the first preset influence degree in the security event evaluation attribute, a first global security protection test target list of the candidate security protection test targets may be determined by the security event database.

The first global security protection test target list comprises at least one first global security protection test target, and the first global security protection test target is a security protection test target which is commonly present in the same security event comparison attribute with the candidate security protection test target and has an attribute influence degree reaching a first preset influence degree in the security event comparison attribute.

Then, a second global security protection test target list of the candidate security protection test targets is determined through the security event evaluation attributes.

The second global security protection test target list comprises at least one second global security protection test target, and the second global security protection test target is a security protection test target which is commonly present in the same security event evaluation attribute with the candidate security protection test target and has an attribute influence degree reaching a first preset influence degree in the security event evaluation attribute.

In this way, if the correlation parameter between the first global security protection test target list and the second global security protection test target list is lower than the set correlation parameter, the candidate security protection test target is used as the security protection test target to be confirmed, and for the security protection test target to be confirmed, the security event evaluation attribute with the attribute influence degree reaching the second preset influence degree is selected as the reference security event evaluation attribute.

Or, in another possible implementation manner, a predetermined number of security event evaluation attributes may be selected from the security event evaluation attributes for which the attribute influence degree of the security protection test target to be confirmed reaches the second preset influence degree, and the selected security event evaluation attributes serve as the reference security event evaluation attributes.

In this way, if the proportion of inconsistency between the first event trigger node information of the safety protection test target to be confirmed determined according to the safety event database and the second event trigger node information indicated by the reference safety event evaluation attribute reaches the set proportion, the safety protection test target to be confirmed is determined as a differentiated safety protection test target.

The first event trigger node information is inconsistent with the second event trigger node information, and the method specifically includes: the first event trigger node information is different from the trigger node indicated by the second event trigger node information, or the difference between the trigger nodes indicated by the first event trigger node information and the second event trigger node information exceeds the set difference.

For example, in a possible implementation manner, the information of the first event trigger node of the security test object to be confirmed includes a trigger node where the security test object to be confirmed is located and a trigger segment where the security test object to be confirmed is located.

Therefore, the process of determining the first event trigger node information of the safety protection test target to be confirmed can be that the trigger node where the safety protection test target to be confirmed is located is determined according to the test table entry operating parameters of the safety protection test target to be confirmed in the safety event comparison attributes contained in the safety event database, and then the trigger segment of the safety protection test link where the test table entry operating parameters of the safety protection test target to be confirmed in the determined trigger node are matched with the set test table entry operating parameters is used as the trigger segment where the safety protection test target to be confirmed is located.

Therefore, the trigger node where the safety protection test target to be confirmed is located is determined according to the test table entry operating parameters of the safety protection test target to be confirmed in the safety event comparison attributes contained in the safety event database, and the trigger node meeting the following conditions can be used as a candidate trigger node:

firstly, a triggering node indicated by a security event comparison attribute with the maximum test table item operation parameter of a security protection test target to be confirmed in a security event database.

And secondly, the triggering node with the largest occurrence frequency in the security event comparison attributes of the security protection test target to be confirmed is contained in the security event database.

And the triggering node with the maximum attribute influence average value of the safety protection test target to be confirmed in the third safety event database.

And fourthly, triggering the node with the maximum attribute influence median of the safety protection test target to be confirmed in the safety event database.

And fifthly, in the candidate trigger nodes, if the occurrence frequency of the same trigger node is matched with the set frequency, the same trigger node is used as the trigger node where the safety protection test target to be confirmed is located.

Further, for example, in a possible implementation manner, for step S113, in the process of obtaining the test table entry operation parameters of the safety protection test targets in each safety protection test link, where the safety protection test targets have differences in evaluation attributes, the following exemplary sub-steps may be implemented.

And a substep S1131, performing information matching on the evaluation attribute tracing information corresponding to each safety event evaluation attribute and the tracing object of the safety protection test target.

And a substep S1132 of adding the evaluation attribute tracing information of which the matching degree reaches the set matching degree to the target reference test library.

And a substep S1133 of determining each evaluation attribute tracing information in the triggering subsection interval of the safety protection testing link in the target reference testing library for each safety protection testing link.

And a substep S1134 of determining test table entry operating parameters of the safety protection test target in the safety protection test link according to the attribute influence degree of the safety protection test target on each piece of evaluation attribute tracing information and the difference between each piece of evaluation attribute tracing information and the safety protection test link.

Illustratively, in the sub-step S1131, for each successive piece of the rating attribute tracing information, a tracing object security template corresponding to the rating attribute tracing information in the tracing object is determined, and then a matching degree of the rating attribute tracing information is determined according to a difference between the rating attribute tracing information and the corresponding tracing object security template.

For another example, in sub-step S1131, for example, a plurality of continuous evaluation attribute tracing information may be further combined into an evaluation attribute tracing unit sequence, a plurality of reference tracing partitions are determined according to the initial evaluation attribute tracing information in the plurality of evaluation attribute tracing information and the tracing parameter in the security event evaluation attribute, a reference tracing partition set is formed, and then the matching degree of each evaluation attribute tracing information in the evaluation attribute tracing unit sequence is determined according to the difference between the evaluation attribute tracing unit sequence and the reference tracing partition set.

Further, for example, in a possible implementation manner, for step S114, in the process of performing security protection processing on an access request parameter of the target record financial service accessed via the block chain based on the updated security protection parameter, updating the security protection parameter corresponding to the set security protection item in the electronic batch record security service of the target record financial service according to the security protection test target with the difference in the evaluation attribute in the test table entry operating parameter of each security protection test link, and updating the security protection parameter corresponding to the set security protection item in the electronic batch record security service of the target record financial service, the following exemplary sub-steps may be implemented.

And a substep S1141 of determining a compatibility evaluation index of the safety protection test target according to the test table item operation parameters of the safety protection test target with different evaluation attributes in each safety protection test link.

And a substep S1142 of updating the test table entry operating parameters of the safety protection test targets with the evaluation attributes different in each safety protection test link to the safety protection parameters corresponding to the set safety protection items in the electronic batch record safety service of the target record financial service if the compatibility evaluation index of the safety protection test targets with the evaluation attributes different meets the preset condition, and performing safety protection processing on the access request parameters of the target record financial service accessed via the block chain based on the updated safety protection parameters.

The specific updating process is illustrated in the foregoing description, and is not described herein again.

Further, in some possible examples, the preset condition may include one or any combination of the following:

1) the concentration degree of the source tracing test distribution of the safety protection test target is matched with the set concentration degree.

2) The source tracing test of the safety protection test target is distributed at the adjacent trigger nodes.

3) The coverage range of the signal of the safety protection test target is within the set range interval.

4) The key test table entry operation parameters of the safety protection test target are matched with the preset test table entry operation parameters.

It is understood that, in the actual implementation process, any combination of the above preset conditions can be used for implementation, and the implementation is not limited specifically.

Further, for example, for the aforementioned step S111, the electronic batch record security service of the target record financial transaction after the electronic batch record security service is updated in advance can be obtained through the following exemplary sub-steps, which are described in detail as follows.

In the substep S1111, target protection record information including a target safety protection object in the power batch record safety big data of the financial service to be updated, which provides the cloud computing service to the plurality of electronic batch record terminals 200, is obtained, and the target protection record information is clustered to obtain clustered protection record information corresponding to the target protection record information.

And a substep S1112, obtaining a target security cloud computing model corresponding to the target protection record information, extracting a first protection behavior feature and a second protection behavior feature from the clustered protection record information through the target security cloud computing model, and splicing the first protection behavior feature and the second protection behavior feature to obtain a protection behavior splicing feature associated with the target protection record information.

And a substep S1113 of performing virtual machine access action analysis on the clustering protection record information according to the protection behavior splicing characteristics and the target safety protection cloud computing model to obtain a virtual machine access action analysis result corresponding to the clustering protection record information.

In sub-step S1114, if the virtual machine access action analysis result indicates that clustered protection record information meeting the virtual machine access action monitoring condition exists in the target protection record information, determining the target security protection object as a target action object, and updating the electronic batch record security service of the cloud computing center based on the target action object and the clustered protection record information meeting the virtual machine access action monitoring condition corresponding to the target action object.

In this embodiment, when the target protection record information including the target security protection object is acquired, clustering may be performed on the target protection record information to divide the target protection record information into one or more clusters, where the number of the divided clusters is not limited. It should be understood that the protection recording information corresponding to each cluster may be collectively referred to as cluster protection recording information in the embodiments of the present application. In addition, it can be understood that the target security protection object herein may be a protection object of a certain security protection node in a security protection simulation scene, and optionally, the target security protection object herein may also be identification information for identifying a certain scene object in a recognition scene, where a specific type of the target security protection object will not be limited herein.

Further, the target protection record information can be sent to a configured target safety protection cloud computing model, so that the first protection behavior feature and the second protection behavior feature are extracted from the divided cluster protection record information through the target safety protection cloud computing model, and then the extracted first protection behavior feature and the extracted second protection behavior feature can be spliced to obtain protection behavior splicing features associated with the target protection record information.

It can be understood that, in the embodiment of the present application, after the first protection behavior feature and the second protection behavior feature extracted from each piece of cluster protection record information are subjected to the splicing processing, the accuracy of subsequently classifying the access action of the virtual machine to which each piece of cluster protection record information belongs can be improved. Further, virtual machine access action analysis can be performed on the clustering protection record information according to the protection action splicing characteristics and the target security protection cloud computing model, so that a virtual machine access action analysis result corresponding to the target protection record information is obtained.

It can be understood that, in the embodiment of the present application, the virtual machine access action analysis result may include a virtual machine access action analysis result corresponding to each piece of clustered protection recording information, so that when it is detected that a virtual machine access action analysis result corresponding to clustered protection recording information that satisfies a virtual machine access action monitoring condition exists in the virtual machine access action analysis results, it may be determined that clustered protection recording information that satisfies the virtual machine access action monitoring condition exists in target protection recording information, and thus, it may be indirectly determined that the target security protection object is the target action object.

Therefore, before the tracing test virtual machine access action monitoring is carried out, the target protection record information can be divided into a series of clustering protection record information in advance, and then virtual machine access action analysis can be carried out on each clustering protection record information through the target safety protection cloud computing model, so that the virtual machine access action to which each clustering protection record information belongs can be identified, and the accuracy of virtual machine access action monitoring can be improved. In addition, after the virtual machine access action to which each piece of clustered protection recording information belongs is identified through the target security protection cloud computing model, the virtual machine access action to which each piece of clustered protection recording information belongs can be collectively referred to as a virtual machine access action analysis result corresponding to the target protection recording information, so that when the clustered protection recording information is detected to have the clustered protection recording information meeting the monitoring condition of the virtual machine access action, a target security protection object can be quickly determined to be a target action object carrying excessive protection deviation, and the reliability of a subsequent security protection process can be ensured after targeted updating is performed.

For example, in one possible implementation, for step S1113, the target security protection cloud computing model may include: and a prediction unit. For example, the prediction unit has a function of performing prediction classification on the access action of the virtual machine to which the clustered protection record information in the target protection record information belongs. Therefore, in a possible implementation manner, in the process of analyzing the access action of the virtual machine on the clustering protection record information according to the protection behavior splicing characteristics and the target security protection cloud computing model to obtain the analysis result of the access action of the virtual machine corresponding to the clustering protection record information, the following exemplary substeps can be used for implementation.

And a substep S11131, inputting the splicing characteristics of the protection behaviors into a prediction unit in the target security protection cloud computing model, and determining the association degree between the splicing characteristics of the protection behaviors and the splicing characteristics of the protection behaviors of a plurality of samples in the prediction unit by the prediction unit.

The association degree can be used for representing the confidence degree that the protection behavior splicing characteristics and each sample protection behavior splicing characteristic belong to the same virtual machine access action respectively.

And a substep S11132 of obtaining the sample protection behavior splicing characteristic with the maximum correlation degree with the protection behavior splicing characteristic from the plurality of sample protection behavior splicing characteristics based on the correlation degree, and taking the sample protection behavior splicing characteristic with the maximum correlation degree as the target sample protection behavior splicing characteristic.

And a substep S11133, taking the sample label information corresponding to the target sample protection behavior splicing characteristic as a target virtual machine access action corresponding to the protection behavior splicing characteristic, and determining a virtual machine access action analysis result after classifying the clustered protection record information in the target protection record information based on the target virtual machine access action and the maximum correlation degree associated with the target virtual machine access action.

Based on this, for example, for step S1114, one piece of clustered protection record information corresponds to one virtual machine access action analysis result, and the sample label information corresponding to the splicing features of the multiple sample protection behaviors includes the update class label information. Thus, in a possible implementation manner, in the process of determining the target security protection object as the target action object if the virtual machine access action analysis result indicates that clustered protection record information meeting the virtual machine access action monitoring condition exists in the target protection record information, the following exemplary sub-steps may be implemented.

And a substep S11141, obtaining a virtual machine access action monitoring condition corresponding to the target security protection cloud computing model.

In the substep S11142, if there is a virtual machine access action analysis result in the virtual machine access action analysis result that the target virtual machine access action belongs to the update-class tag information, the clustering protection record information corresponding to the target virtual machine access action is determined as the clustering protection record information satisfying the virtual machine access action monitoring condition.

In the substep S11143, the target security object included in the target security record information is determined as the target action object.

Further, still referring to step S11141, in a process of updating the electronic batch record security service of the cloud computing center based on the target action object and the cluster protection record information corresponding to the target action object and satisfying the virtual machine access action monitoring condition, the following exemplary sub-steps may be implemented.

And a substep S11144, extracting an interception environment component corresponding to each target dynamic protection interface in the clustering protection record information which is corresponding to the target action object and meets the monitoring condition of the virtual machine access action, and extracting an interception penetration injection code of the interception environment component in parallel while acquiring an original application program layer list associated with the interception operation of the interception environment component from an environment component enabling file of the interception environment component.

And a substep S11145 of determining interception rule distribution information for performing simulation analysis on the original application program layer list based on the extracted interception penetration injection code, extracting interception rule dependent factor parameters of a plurality of interception rule dependent factor nodes to be used and dependent factor combination information among different interception rule dependent factor nodes from the interception rule distribution information, and performing source tracing test processing on the plurality of interception rule dependent factor nodes to be used according to the interception rule dependent factor parameters and the dependent factor combination information to obtain at least two target interception rule dependent operation objects.

The running environment interval of the interception rule dependent factor parameter of the target interception rule dependent on the operation object is positioned in the set interval, and different target interception rules depend on the dependent factor between the operation objects and the difference of the information is not matched with the set value.

And a substep S11146, performing simulation analysis on the original application program layer list by depending on the operation object through the target interception rule to obtain a candidate safety protection item list.

And a substep S11147, determining rule base updating distribution of the candidate safety protection item list according to the target interception penetration injection code determined from the preset interception environment running record of the trusted test platform, and determining rule base expansion distribution of the candidate safety protection item list according to the service label in the determined candidate safety protection item list.

And a substep S11148, performing trusted dynamic protection interface extraction on the candidate safety protection item list based on the rule base updating distribution and the rule base expansion distribution to obtain a trusted dynamic protection interface set.

And a substep S11144, updating the electronic batch record security service of the cloud computing center based on the trusted dynamic protection interface set.

Illustratively, for example, in one possible implementation, the target security protection cloud computing model provided in this embodiment is configured to obtain by:

(1) configuration sample information associated with the sample object and sample label information of the configuration sample information are obtained.

For example, the configuration sample information includes first sample information and second sample information for configuring the initial security protection cloud computing model. Sample label information configuring the sample information includes: the non-update label information corresponding to the first sample information and the update label information corresponding to the second sample information.

(2) And clustering the configuration sample information to obtain clustering performance sample data corresponding to the configuration sample information.

(3) Extracting a first sample characteristic and a second sample characteristic from clustering performance sample data through an initial safety protection cloud computing model, and performing characteristic splicing processing on the first sample characteristic and the second sample characteristic to obtain a sample splicing processing characteristic associated with configuration sample information.

(4) And configuring the initial security protection cloud computing model based on the sample splicing processing characteristics, the non-updating type label information and the updating type label information, and determining the configured initial security protection cloud computing model as a target security protection cloud computing model for predicting a target object in a target image.

Illustratively, for example, in (1), in the process of obtaining the configuration sample information associated with the sample object and the sample label information of the configuration sample information, first, initial test protection record information containing the sample object may be obtained, the initial test protection record information is used as first sample information for configuring the initial security protection cloud computing model, and the label information of the first sample information is determined as non-update type label information.

And then, acquiring an object identification model having an incidence relation with the initial security protection cloud computing model, and determining updated test protection record information associated with the initial test protection record information through the object identification model. And then, based on the updated test protection record information and the initial test protection record information, generating superposition test protection record information containing the updated test protection record information, taking the superposition test protection record information as second sample information for configuring the initial security protection cloud computing model, and determining label information of the second sample information as update-type label information.

Thus, the first sample information and the second sample information can be determined as the configured sample information, and the non-update-class tag information and the update-class tag information can be used as the sample tag information of the configured sample information.

Fig. 3 is a schematic functional module diagram of a data recovery processing device 300 based on a block chain and cloud computing according to an embodiment of the present disclosure, and this embodiment may divide the functional modules of the data recovery processing device 300 based on the block chain and cloud computing according to a method embodiment executed by the cloud computing center 100, that is, the following functional modules corresponding to the data recovery processing device 300 based on the block chain and cloud computing may be used to execute each method embodiment executed by the cloud computing center 100. The data recovery processing apparatus 300 based on blockchain and cloud computing may include an acquisition parsing module 310, a determination module 320, a matching module 330, and a data recovery module 340, where functions of the functional modules of the data recovery processing apparatus 300 based on blockchain and cloud computing are described in detail below.

The obtaining and analyzing module 310 is configured to obtain a security protection parameter corresponding to each set security protection item, analyze an access request parameter of the target record financial transaction based on the security protection parameter, and obtain a corresponding access service object after security protection is passed. The obtaining and analyzing module 310 may be configured to execute the step S110, and the detailed implementation of the obtaining and analyzing module 310 may refer to the detailed description of the step S110.

A determining module 320, configured to obtain a corresponding object to be restored based on the access service object, and determine a pre-restoration information chain of multiple restoration service table entries based on the object to be restored. The determining module 320 may be configured to perform the step S120, and the detailed implementation of the determining module 320 may refer to the detailed description of the step S120.

A matching module 330, configured to input the pre-recovery information chain into multiple channel units in a block chain recovery channel, respectively, and perform at least one recovery node matching through the channel units to obtain at least one recovery node unit; wherein at least one recovery node matching by the channel units is performed based on an associated recovery object that fuses recovery node units extracted from other channel units of the plurality of channel units. The matching module 330 may be configured to perform the step S130, and the detailed implementation of the matching module 330 may refer to the detailed description of the step S130.

The data recovery module 340 is configured to cluster the multiple recovery node units output by the multiple channel units to obtain a cluster recovery node unit, obtain a recovery queue result of the object to be recovered under the access request parameter based on the cluster recovery node unit, and perform data recovery based on the recovery queue result of the object to be recovered under the access request parameter. The data recovery module 340 may be configured to perform the step S140, and the detailed implementation manner of the data recovery module 340 may refer to the detailed description of the step S140.

It should be noted that the division of the modules of the above apparatus is only a logical division, and the actual implementation may be wholly or partially integrated into one physical entity, or may be physically separated. And these modules may all be implemented in software invoked by a processing element. Or may be implemented entirely in hardware. And part of the modules can be realized in the form of calling software by the processing element, and part of the modules can be realized in the form of hardware. For example, the acquisition and analysis module 310 may be a processing element separately set up, or may be implemented by being integrated into a chip of the apparatus, or may be stored in a memory of the apparatus in the form of program code, and the processing element of the apparatus calls and executes the functions of the acquisition and analysis module 310. Other modules are implemented similarly. In addition, all or part of the modules can be integrated together or can be independently realized. The processing element described herein may be an integrated circuit having signal processing capabilities. In implementation, each step of the above method or each module above may be implemented by an integrated logic circuit of hardware in a processor element or an instruction in the form of software.

Fig. 4 is a schematic diagram illustrating a hardware structure of a cloud computing center 100 for implementing the above data recovery processing method based on blockchain and cloud computing according to an embodiment of the present disclosure, and as shown in fig. 4, the cloud computing center 100 may include a processor 110, a machine-readable storage medium 120, a bus 130, and a transceiver 140.

In a specific implementation process, at least one processor 110 executes computer-executable instructions stored in the machine-readable storage medium 120 (for example, the acquisition parsing module 310, the determining module 320, the matching module 330, and the data recovery module 340 included in the data recovery processing apparatus 300 based on blockchain and cloud computing shown in fig. 3), so that the processor 110 may execute the data recovery processing method based on blockchain and cloud computing according to the above method embodiment, where the processor 110, the machine-readable storage medium 120, and the transceiver 140 are connected through the bus 130, and the processor 110 may be configured to control the transceiving action of the transceiver 140, so as to perform data transceiving with the electronic batch recording terminal 200.

For a specific implementation process of the processor 110, reference may be made to the above-mentioned method embodiments executed by the cloud computing center 100, and implementation principles and technical effects are similar, which are not described herein again.

In the embodiment shown in fig. 4, it should be understood that the Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor, or in a combination of the hardware and software modules within the processor.

The machine-readable storage medium 120 may comprise high-speed RAM memory and may also include non-volatile storage NVM, such as at least one disk memory.

The bus 130 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus 130 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, the buses in the figures of the present application are not limited to only one bus or one type of bus.

In addition, an embodiment of the present application further provides a readable storage medium, where a computer executing instruction is stored in the readable storage medium, and when a processor executes the computer executing instruction, the data recovery processing method based on the block chain and cloud computing is implemented as above.

The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.

Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing detailed disclosure is to be regarded as illustrative only and not as limiting the present specification. Various modifications, improvements and adaptations to the present description may occur to those skilled in the art, although not explicitly described herein. Such modifications, improvements and adaptations are proposed in the present specification and thus fall within the spirit and scope of the exemplary embodiments of the present specification.

Also, the description uses specific words to describe embodiments of the description. Reference to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic described in connection with at least one embodiment of the specification. Therefore, it is emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, some features, structures, or characteristics of one or more embodiments of the specification may be combined as appropriate.

Moreover, those skilled in the art will appreciate that aspects of the present description may be illustrated and described in terms of several patentable species or contexts, including any new and useful combination of processes, machines, manufacture, or materials, or any new and useful improvement thereof. Accordingly, aspects of this description may be performed entirely by hardware, entirely by software (including firmware, resident software, micro-code, etc.), or by a combination of hardware and software. The above hardware or software may be referred to as "data block," module, "" engine, "" unit, "" component, "or" system. Furthermore, aspects of the present description may be represented as a computer product, including computer readable program code, embodied in one or more computer readable media.

The computer storage medium may comprise a propagated data signal with the computer program code embodied therewith, for example, on baseband or as part of a carrier wave. The propagated signal may take any of a variety of forms, including electromagnetic, optical, etc., or any suitable combination. A computer storage medium may be any computer-readable medium that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, or device. Program code located on a computer storage medium may be propagated over any suitable medium, including radio, cable, fiber optic cable, RF, or the like, or any combination of the preceding.

Computer program code required for the operation of various portions of this specification may be written in any one or more programming languages, including an object oriented programming language such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C + +, C #, VB.NET, Python, and the like, a conventional programming language such as C, VisualBasic, Fortran2003, Perl, COBOL2002, PHP, ABAP, a dynamic programming language such as Python, Ruby, and Groovy, or other programming languages, and the like. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any network format, such as a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet), or in a cloud computing environment, or as a service, such as a software as a service (SaaS).

Additionally, the order in which the elements and sequences are processed, the use of alphanumeric characters, or the use of other designations in this specification is not intended to limit the order of the processes and methods in this specification, unless otherwise specified in the claims. While various presently contemplated embodiments of the invention have been discussed in the foregoing disclosure by way of example, it is to be understood that such detail is solely for that purpose and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover all modifications and equivalent arrangements that are within the spirit and scope of the embodiments herein. For example, although the system components described above may be implemented by hardware devices, they may also be implemented by software-only solutions, such as installing the described system on an existing server or mobile device.

Similarly, it should be noted that in the preceding description of embodiments of the present specification, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the embodiments. This method of disclosure, however, is not intended to imply that more features than are expressly recited in a claim. Indeed, the embodiments may be characterized as having less than all of the features of a single embodiment disclosed above.

Finally, it should be understood that the examples in this specification are only intended to illustrate the principles of the examples in this specification. Other variations are also possible within the scope of this description. Thus, by way of example, and not limitation, alternative configurations of the embodiments of the specification can be considered consistent with the teachings of the specification. Accordingly, the embodiments of the present description are not limited to only those embodiments explicitly described and depicted herein.

Claims

1. A data recovery processing method based on a block chain and cloud computing is characterized by being applied to a cloud computing center, wherein the cloud computing center is in communication connection with a plurality of electronic batch recording terminals, and the method comprises the following steps:

clustering a plurality of recovery node units output by the plurality of channel units to obtain a cluster recovery node unit, obtaining a recovery queue result of the object to be recovered under the access request parameter based on the cluster recovery node unit, and performing data recovery based on the recovery queue result of the object to be recovered under the access request parameter;

the recovery queue result of the object to be recovered under the access request parameter is used for representing a recovery instruction running set of the object to be recovered in a subsequent data recovery process, specifically a recovery control instruction for controlling a flow direction relation of a recovery data node in the data recovery process, so as to execute the computer program according to an execution sequence of the recovery control instruction, thereby performing data recovery.

2. The data recovery processing method based on blockchain and cloud computing according to claim 1, wherein the method further comprises:

taking one of the plurality of channel units as a target channel unit;

wherein the method further comprises:

3. The data recovery processing method based on the block chain and the cloud computing according to claim 1, wherein the step of inputting the pre-recovery information chain into a plurality of channel units in a block chain recovery channel respectively, and performing at least one recovery node matching through the channel units to obtain at least one recovery node unit comprises:

4. The data recovery processing method based on block chain and cloud computing according to claim 1, wherein the step of determining a pre-recovery information chain of a plurality of recovery service table entries based on the object to be recovered comprises:

5. The data recovery processing method based on the block chain and cloud computing according to claim 1, wherein the pre-recovery information chain at least includes a first pre-recovery information chain, a second pre-recovery information chain, and a third pre-recovery information chain, and the block chain recovery channel includes a first channel unit, a second channel unit, and a third channel unit, wherein the first pre-recovery information chain, the second pre-recovery information chain, and the third pre-recovery information chain respectively correspond to the pre-recovery information chains of the logic failure data, the hardware failure data, and the RAID data of the disk array, and the first channel unit, the second channel unit, and the third channel unit respectively correspond to the channel units of the logic failure data, the hardware failure data, and the RAID data of the disk array;

6. The data recovery processing method based on the block chain and the cloud computing according to any one of claims 1 to 5, wherein the step of obtaining the recovery queue result of the object to be recovered under the access request parameter based on the cluster recovery node unit includes:

determining a recovery model corresponding to the access request parameter;

7. The data recovery processing method based on the blockchain and cloud computing according to claim 6, wherein the step of obtaining the corresponding object to be recovered based on the access service object includes:

8. The data recovery processing method based on the blockchain and cloud computing according to claim 1, wherein the step of clustering the recovery node units output by the channel units to obtain a cluster recovery node unit comprises:

9. The data recovery processing method based on the blockchain and the cloud computing according to any one of claims 1 to 5, wherein the step of obtaining a security protection parameter corresponding to each set security protection item, analyzing an access request parameter of a target record financial service based on the security protection parameter, and obtaining a corresponding access service object after security protection is passed includes:

10. A cloud computing center, characterized in that the cloud computing center comprises a processor, a machine-readable storage medium, and a network interface, the machine-readable storage medium, the network interface, and the processor are connected through a bus system, the network interface is used for being connected with at least one electronic batch recording terminal in a communication manner, the machine-readable storage medium is used for storing programs, instructions, or codes, and the processor is used for executing the programs, instructions, or codes in the machine-readable storage medium to execute the data recovery processing method based on blockchain and cloud computing according to any one of claims 1 to 9.