CN112672353A

CN112672353A - Information analysis method, system and cloud platform based on cloud computing and 5G interconnection

Info

Publication number: CN112672353A
Application number: CN202011512142.8A
Authority: CN
Inventors: 张仕红
Original assignee: Individual
Current assignee: Individual
Priority date: 2020-06-19
Filing date: 2020-06-19
Publication date: 2021-04-16
Also published as: CN111800790A; CN112702737A; CN111800790B

Abstract

The embodiment of the disclosure provides an information analysis method, an information analysis system and a cloud platform based on cloud computing and 5G interconnection, wherein verification result information of each information verification terminal in a target verification service interval is obtained, and application scene parameter data of each information verification terminal in the target verification service interval is obtained from each information verification terminal, so that configuration updating content between an application scene configuration node and an original configuration node in the target verification service interval and scene area classification of the application scene configuration node are specifically considered, data analysis is performed on corresponding verification result information by combining the application scene parameter data of each information verification terminal, uncertainty of application scene configuration processes of different information verification terminals is effectively adapted, and verification self-adaptive analysis accuracy is improved.

Description

Information analysis method, system and cloud platform based on cloud computing and 5G interconnection

Technical Field

The disclosure relates to the technical field of big data and verification self-adaption, in particular to an information analysis method, an information analysis system and a cloud platform based on cloud computing and 5G interconnection.

Background

With the rapid development of 5G and Internet of things technologies, image information safety verification is performed through various information verification terminals, and the method is an important application scene of a man-machine cooperation cloud platform. In the prior art, real-time verification object data or historical verification object data of a human-computer collaborative cloud platform are generally analyzed singly so as to judge whether a verification self-adaptive abnormity exists in the human-computer collaborative cloud platform. However, the inventor of the present invention finds that, in the verification process, there often exists uncertainty of the configuration process of the application scenario (e.g., different security verification scenarios), that is, for different verification processes, the configuration situations of the application scenario may be different, so that the accuracy of the verification adaptive analysis of the conventional scheme may be low.

Disclosure of Invention

In order to overcome at least the above disadvantages in the prior art, the present disclosure aims to provide an information analysis method, system and cloud platform based on cloud computing and 5G interconnection, which perform data analysis on corresponding verification result information by combining application scenario parameter data of each information verification terminal, thereby effectively adapting to uncertainty of an application scenario configuration process of different information verification terminals, and improving verification adaptive analysis accuracy.

In a first aspect, the present disclosure provides an information analysis method based on cloud computing and 5G interconnection, which is applied to a human-computer cooperation cloud platform, where the human-computer cooperation cloud platform is in communication connection with a plurality of information verification terminals, and the method includes:

acquiring verification result information of each information verification terminal in a target verification service interval, and acquiring application scene parameter data of each information verification terminal in the target verification service interval from each information verification terminal, wherein the application scene parameter data comprises configuration update contents between an application scene configuration node and an original configuration node in the target verification service interval and scene area classification of the application scene configuration node;

and performing data analysis on the verification result information according to the application scene parameter data to obtain a verification self-adaption result of each information verification terminal.

In a possible implementation manner of the first aspect, the step of performing data analysis on the verification result information according to the application scenario parameter data to obtain a verification adaptive result of each information verification terminal includes:

determining a target scene verification source of each application scene configuration node corresponding to the verification result information according to configuration updating content between the application scene configuration nodes and the original configuration nodes;

and according to the scene area classification of each application scene configuration node, performing data analysis on a target scene verification source of the verification result information corresponding to each application scene configuration node to obtain a verification self-adaptive result of each information verification terminal.

In a possible implementation manner of the first aspect, the step of determining, according to configuration update content between the application scenario configuration node and an original configuration node, that the verification result information corresponds to a target scenario verification source of each application scenario configuration node includes:

respectively detecting a first scene pointing object of the application scene configuration node in an application scene and a second scene pointing object of a corresponding original configuration node in the application scene, wherein the first scene pointing object and the second scene pointing object are respectively used for representing pointing objects corresponding to a source configuration directory when the application scene configuration node and the corresponding original configuration node are configured;

determining configuration update content between the application scene configuration node and an original configuration node according to each first scene pointing object and the corresponding second scene pointing object, wherein the configuration update content comprises at least one configuration update item interval, and each configuration update item interval is used for indicating that an update data segment of an updated condition exists between the application scene configuration node and the original configuration node;

acquiring a digital contract certificate corresponding to each configuration updating project interval from the configuration updating content, and determining an edge service function and an edge access channel of each verification result project in the verification result information according to the digital contract certificate;

and determining a target scene verification source of each application scene configuration node corresponding to the verification result information according to the edge service function and the edge access channel of each verification result item in the verification result information.

In a possible implementation manner of the first aspect, the determining, according to the digital contract certificate, an edge service function and an edge access channel of each verification result item in the verification result information includes:

obtaining individual digital contract verification objects from the digital contract certificate, wherein each digital contract verification object is used to represent a verification object each time a digital contract verification is initiated;

extracting contract verification monitoring variable results of each digital contract verification object and constructing a corresponding contract verification monitoring variable matrix, and processing access generation records of the verification result items according to the contract verification monitoring variable matrix aiming at each verification result item in the verification result information to obtain matching results of a plurality of different contract verification monitoring targets of the contract verification monitoring variable matrix as undetermined edge service functions of the access generation records so as to obtain undetermined edge service functions of each verification result item;

matching the confidence coefficient that each edge service node of the undetermined edge service function is a cooperative sensing node and the cooperative sensing detection information of the edge service node relative to the verification result item of the contract verification monitoring target where the edge service node is located when each edge service node is a cooperative sensing node based on the to-be-determined edge service function of each verification result item;

determining edge service nodes with confidence degrees higher than a preset confidence degree threshold value as cooperative sensing nodes, and determining cooperative sensing detection information of verification result items of contract verification monitoring targets determined by the cooperative sensing nodes based on cooperative access behaviors of the cooperative sensing detection information of each cooperative sensing node relative to the cooperative sensing detection information of the verification result items of the contract verification monitoring targets where the cooperative sensing node is located;

removing the cooperative sensing detection information of the verification result item of the contract verification monitoring target determined more than twice in the cooperative sensing detection information of the verification result item of the contract verification monitoring target determined by each cooperative sensing node to obtain the cooperative sensing detection information of the verification result item of each undetermined contract verification monitoring target;

and determining the edge service function and the edge access channel of each verification result item in the verification result information according to the cooperative sensing detection information of the verification result item of each to-be-determined contract verification monitoring target.

In a possible implementation manner of the first aspect, the step of determining, according to the cooperative sensing detection information of the verification result item of each pending contract verification monitoring target, an edge service function and an edge access channel of each verification result item in the verification result information includes:

inputting the undetermined marginal business function of the access generation record into a target decision classifier, processing a decision cooperative classification label output by the target decision classifier based on cooperative sensing detection information of a verification result item of each undetermined contract verification monitoring target, and generating cooperative access behavior characteristics for representing the trend of the decision cooperative classification label of the undetermined contract verification monitoring target;

determining a combined undetermined contract verification monitoring target of each undetermined contract verification monitoring target in the access generation record based on the cooperative sensing detection information of the verification result item of the undetermined contract verification monitoring target, and calculating the Hamming distance between the cooperative access behavior feature of the undetermined contract verification monitoring target and the cooperative access behavior feature of each corresponding combined undetermined contract verification monitoring target as a correlation value between the undetermined contract verification monitoring target and each corresponding combined undetermined contract verification monitoring target;

taking a combined undetermined contract verification monitoring target with a correlation value smaller than a preset correlation value threshold value with the undetermined contract verification monitoring target as a combined undetermined contract verification monitoring target related to the undetermined contract verification monitoring target, and combining each undetermined contract verification monitoring target with the related combined undetermined contract verification monitoring target into a contract verification monitoring target correlation combination;

determining edge service nodes corresponding to all contract verification monitoring targets in the contract verification monitoring target association combination as edge service functions of each verification result item based on the cooperative sensing detection information of the verification result items of all undetermined contract verification monitoring targets in the contract verification monitoring target association combination;

and acquiring the edge access channel of each verification result item from the determined access information of the edge service function of each verification result item.

In a possible implementation manner of the first aspect, the step of processing the decision-making cooperative classification tag output by the target decision-making classifier based on the cooperative sensing detection information of the verification result item of each pending contract verification monitoring target to generate a cooperative access behavior feature for characterizing a trend of the decision-making cooperative classification tag of the pending contract verification monitoring target includes:

extracting corresponding collaborative access behaviors from decision collaborative classification labels output by the target decision classifier based on collaborative sensing detection information of verification result items of each to-be-determined contract verification monitoring target to obtain collaborative access behavior units, and determining each source path mapping space based on source paths of the collaborative access behaviors included by the collaborative access behavior units, wherein the range covered by each source path mapping space includes the source path of each collaborative access behavior in each collaborative access behavior unit;

for each source path mapping space, merging the cooperative access behavior units of which the source paths including the cooperative access behaviors are located in the source path mapping space into a cooperative access behavior unit set, and for each cooperative access behavior unit in each cooperative access behavior unit set, determining the associated cooperative access behaviors of the cooperative access behaviors included in the cooperative access behavior unit, wherein the associated cooperative access behaviors are the cooperative access behaviors formed after the cooperative access behaviors of the same type in each cooperative access behavior are associated;

determining a common access node between every two associated cooperative access behaviors, and determining the common access node between the determined associated cooperative access behaviors as a key behavior unit between corresponding cooperative access behavior units;

and cooperating a vector set formed by cooperative feature vectors corresponding to key behavior units among the cooperative access behavior units as cooperative access behavior features for representing the trend of the decision cooperative classification label of the to-be-determined contract verification monitoring target.

In a possible implementation manner of the first aspect, the determining, according to the edge service function and the edge access channel of each verification result item in the verification result information, that the verification result information corresponds to the target scenario verification source of each application scenario configuration node includes:

determining a scene verification source of each application scene configuration node corresponding to the verification result information according to the edge service function of each verification result item in the verification result information;

and respectively determining the target scene verification source of each application scene configuration node corresponding to the verification result information from the scene verification sources of each application scene configuration node corresponding to the verification result information according to the verification target area corresponding to the edge access channel of each verification result item in the verification result information.

In a possible implementation manner of the first aspect, the step of performing data analysis on the target scene verification source of the verification result information corresponding to each application scene configuration node according to the scene area classification of each application scene configuration node to obtain the verification adaptive result of each information verification terminal includes:

according to the scene area classification of each application scene configuration node, acquiring a configuration option sequence and each option characterization function of each application scene configuration node, wherein the configuration option sequence is used for recording the configuration options of each application scene configuration node, and the option characterization function is used for characterizing the matching function of each application scene configuration node under different configuration options;

performing data analysis on a target scene verification source of the verification result information corresponding to each application scene configuration node according to the configuration option sequence to obtain a target option representation function under a hot scene configuration data segment corresponding to each application scene configuration node, wherein the hot scene configuration data segment comprises configuration option verification areas in a set quantity range;

and obtaining a verification self-adaptive result of each information verification terminal according to a target option representation function under the hotspot scene configuration data segment corresponding to each application scene configuration node.

In a possible implementation manner of the first aspect, the step of performing data analysis on the target scene verification source of the verification result information corresponding to each application scene configuration node according to the configuration option sequence to obtain the target protocol feature under the hotspot scene configuration data segment corresponding to each application scene configuration node includes:

performing data analysis on a target scene verification source of the verification result information corresponding to each application scene configuration node according to the configuration option sequence, determining feature item association relationship between each option characterization function of each application scene configuration node under the corresponding non-hot scene configuration data segment and each option characterization function under the hot scene configuration data segment corresponding to the application scene configuration node according to the option characterization function and the feature item ratio of each application scene configuration node under the corresponding hot scene configuration data segment under the condition that the target scene verification source of each application scene configuration node contains the hot scene configuration data segment, and transferring the option characterization function of each application scene configuration node under the corresponding non-hot scene configuration data segment and the option characterization function under the hot scene configuration data segment corresponding to the application scene configuration node to an option characterization function with strong feature item association relationship And moving to a hot spot scene configuration data segment corresponding to the application scene configuration node, wherein the strong association relationship of the feature items is used for representing the association relationship corresponding to the condition that the mutual verification ratio between the feature items is greater than a set ratio threshold value.

In a possible implementation manner of the first aspect, the step of obtaining a verification adaptive result of each information verification terminal according to a target option characterization function under the hotspot scene configuration data segment corresponding to each application scene configuration node includes:

aiming at each application scene configuration node, establishing a corresponding verification depth distribution map according to the verification repetition degree of each option representation function under a hotspot scene configuration data segment corresponding to the application scene configuration node, wherein the verification depth distribution map is a sub-depth area map, each depth area corresponds to a depth area weight, and each depth area weight has at least one verification repetition degree distribution;

determining a verification interaction thread of each option representation function corresponding to the application scene configuration node, and determining a verification interaction service identifier corresponding to the verification interaction thread of each option representation function;

mapping each verification interactive service identifier to the verification depth distribution map, determining a depth region where each verification interactive service identifier is located, determining a verification interaction confidence coefficient between an option characterization function corresponding to the depth region and the verification interactive service identifier according to the depth region weight of the depth region where each verification interactive service identifier is located, and determining a verification adaptive parameter of the option characterization function corresponding to the verification interactive service identifier based on the verification interaction confidence coefficient;

and obtaining the verification self-adaptive result of each information verification terminal according to all the determined verification self-adaptive parameters.

In a possible implementation manner of the first aspect, the step of obtaining the verification adaptive result of each information verification terminal according to all the determined verification adaptive parameters includes:

performing regular expression matching on all the determined verification adaptive parameters, and determining the proportion of the verification adaptive parameters with a preset rule format in all the verification adaptive parameters, wherein the preset rule format is used for representing that the verification adaptive parameters have specific threat parameters;

judging whether the proportion of the verification adaptive parameters with the preset rule format in all the verification adaptive parameters reaches a set proportion threshold value, wherein the set proportion threshold value is determined according to the number of historical threat states of each information verification terminal;

when the proportion of the verification self-adaptive parameters with the preset rule format in all the verification self-adaptive parameters reaches a set proportion threshold value or not, determining that the corresponding information verification terminal has verification self-adaptive abnormity, otherwise, determining that the information verification terminal does not have verification self-adaptive abnormity; and

when the information verification terminal is determined to have verification self-adaption abnormity, extracting corresponding target verification self-adaption abnormity parameters from verification self-adaption parameters corresponding to the information verification terminal and having a preset rule format, and positioning a first self-adaption updating node corresponding to each self-adaption updating interface from self-adaption objects after extracting self-adaption objects of the target verification self-adaption abnormity parameters;

judging whether a first adaptive update node corresponding to each adaptive update interface in the adaptive object has an associated table entry node relative to a second adaptive update node in the adaptive object, wherein the second adaptive update node is a node except the first adaptive update node in the adaptive object;

if a first adaptive update node corresponding to each adaptive update interface in the adaptive object has an associated table entry node relative to a second adaptive update node in the adaptive object, determining the first adaptive update node corresponding to each adaptive update interface located in the adaptive object as an effective adaptive update node of the adaptive object, otherwise, fusing the first adaptive update node corresponding to each adaptive update interface located in the adaptive object with the second adaptive update node in the adaptive object to obtain the effective adaptive update node of the adaptive object;

for each self-adaptive updating interface, extracting first verification process information of the self-adaptive updating interface in a verification protocol node of the man-machine cooperative cloud platform, and fusing partial nodes in effective self-adaptive updating nodes of the self-adaptive object with the first verification process information to obtain second verification process information;

respectively simulating the first verification process information and the second verification process information in a protocol process corresponding to the verification protocol node to obtain corresponding first verification simulation information and second verification simulation information, judging whether the similarity of the first verification simulation information and the second verification simulation information reaches a preset similarity threshold, starting the self-adaptive updating interface to operate and simulate the second verification process information when the similarity of the first verification simulation information and the second verification simulation information reaches the preset similarity threshold to obtain third verification simulation information corresponding to the second verification process information, extracting an abnormal class label in the third verification simulation information and obtaining an updating strategy corresponding to the self-adaptive updating interface according to the abnormal class label, and when the similarity of the first verification simulation information and the second verification simulation information does not reach the preset threshold, returning to the operation of fusing part of the nodes in the effective self-adaptive updating nodes of the self-adaptive object with the first verification process information to obtain second verification process information.

In a possible implementation manner of the first aspect, the step of obtaining the verification result information of each information verification terminal within the target verification service interval includes:

acquiring an image object label of image acquisition verification information in the process of executing image information acquisition by the information verification terminal, determining a verification image node grid according to an image verification service of the image object label, and acquiring a verification signature behavior sequence and signature connection graph information of each corresponding verification analysis information generated by the verification image node grid in the process of verifying the image acquisition verification information, wherein the image object label is used for representing the verification type of an object to be verified in the process of executing image information acquisition, the image verification service is used for representing a logic service called in the process of image verification aiming at the image object label, the logic service is used for representing the association logic relationship between all verification items and each verification item, and the verification image node grid is used for representing a logic grid formed by taking the verification item as a verification image node, each verification signature behavior in the verification signature behavior sequence is used for representing process information of a digital signature generated in the verification process for each verification item, and the signature connection diagram information is used for representing the connection migration relationship between the digital signatures generated each time;

respectively inputting the verification signature behavior sequence and the signature connection diagram information to a support vector machine classifier obtained through configuration, extracting a first signature verification vector set of each verification analysis information through a first decision boundary of the support vector machine classifier, and extracting a second signature verification vector set of each verification analysis information through a second decision boundary of the support vector machine classifier, wherein the support vector machine classifier is obtained through training based on a training sample;

fusing the first signature verification vector set and the second signature verification vector set through a fusion decision function of the support vector machine classifier to obtain a target signature verification vector set;

and determining a verification extended object of which each verification analysis information corresponds to the image object label according to the target signature verification vector set, respectively generating corresponding extended signature verification information of each verification analysis information according to the verification extended object, and storing a verification result after secondary verification into a secondary verification big data collection library after carrying out secondary verification on the verification analysis information according to the extended signature verification information.

In a second aspect, an embodiment of the present disclosure further provides an information analysis device based on cloud computing and 5G interconnection, which is applied to a human-computer cooperation cloud platform, where the human-computer cooperation cloud platform is in communication connection with a plurality of information verification terminals, and the device includes:

the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring verification result information of each information verification terminal in a target verification service interval and acquiring application scene parameter data of each information verification terminal in the target verification service interval from each information verification terminal, and the application scene parameter data comprises configuration updating content between an application scene configuration node and an original configuration node in the target verification service interval and scene area classification of the application scene configuration node;

and the data analysis module is used for carrying out data analysis on the verification result information according to the application scene parameter data to obtain a verification self-adaptive result of each information verification terminal.

In a third aspect, an embodiment of the present disclosure further provides an information analysis system based on cloud computing and 5G interconnection, where the information analysis system based on cloud computing and 5G interconnection includes a man-machine cooperation cloud platform and a plurality of information verification terminals in communication connection with the man-machine cooperation cloud platform;

the information verification terminal is used for sending verification result information of the man-machine cooperation cloud platform in a target verification service interval;

the man-machine cooperation cloud platform is used for acquiring verification result information of each information verification terminal in a target verification service interval and acquiring application scene parameter data of each information verification terminal in the target verification service interval from each information verification terminal, wherein the application scene parameter data comprises configuration updating content between an application scene configuration node and an original configuration node in the target verification service interval and scene area classification of the application scene configuration node;

and the man-machine cooperation cloud platform is used for carrying out data analysis on the verification result information according to the application scene parameter data to obtain a verification self-adaption result of each information verification terminal.

In a fourth aspect, an embodiment of the present disclosure further provides a human-computer cooperation cloud platform, where the human-computer cooperation cloud platform 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 in communication connection with at least one information verification 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 cloud computing and 5G interconnection-based information parsing method in the first aspect or any one of possible implementation manners in the first aspect.

In a fifth aspect, an embodiment of the present disclosure provides a computer-readable storage medium, where instructions are stored, and when the instructions are executed, the method for information analysis based on cloud computing and 5G interconnection in the first aspect or any one of the possible implementation manners of the first aspect is implemented.

Based on any one of the above aspects, the present disclosure obtains the verification result information of each information verification terminal in the target verification service interval, and obtains the application scene parameter data of each information verification terminal in the target verification service interval from each information verification terminal, thereby specifically considering the configuration update content between the application scene configuration node and the original configuration node in the target verification service interval and the scene area classification of the application scene configuration node, and performing data analysis on the corresponding verification result information by combining the application scene parameter data of each information verification terminal, thereby effectively adapting to the uncertainty of the application scene configuration process of different information verification terminals, and improving the verification adaptive analysis accuracy.

Drawings

To more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present disclosure and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings may be obtained from the drawings without inventive effort.

Fig. 1 is a schematic view of an application scenario of an information analysis system based on cloud computing and 5G interconnection provided in the embodiment of the present disclosure;

fig. 2 is a schematic flowchart of an information analysis method based on cloud computing and 5G interconnection according to an embodiment of the present disclosure;

fig. 3 is a schematic functional module diagram of an information analysis device based on cloud computing and 5G interconnection according to an embodiment of the present disclosure;

fig. 4 is a block diagram schematically illustrating a structure of a human-computer cooperation cloud platform for implementing the information analysis method based on cloud computing and 5G interconnection provided in the embodiment of the present disclosure.

Detailed Description

The present disclosure is described in detail below with reference to the drawings, and the specific operation methods in the following method embodiments can also be applied to the device embodiments or the system embodiments.

Fig. 1 is an interaction schematic diagram of an information parsing system 10 based on cloud computing and 5G interconnection provided in an embodiment of the present disclosure. The information analysis system 10 based on cloud computing and 5G interconnection can comprise a man-machine cooperation cloud platform 100 and an information verification terminal 200 in communication connection with the man-machine cooperation cloud platform 100. The cloud computing and 5G interconnection based information parsing system 10 shown in fig. 1 is only one possible example, and in other possible embodiments, the cloud computing and 5G interconnection based information parsing system 10 may also include only a part of the components shown in fig. 1 or may also include other components.

In this embodiment, the information verification terminal 200 may include a mobile device, a tablet computer, a laptop computer, or the like, or any combination thereof. In some embodiments, the mobile device may include a smart home 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 smart home devices may include control devices of smart electrical devices, smart monitoring devices, smart televisions, smart cameras, 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/or 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, the virtual reality device and/or augmented reality device may include various virtual reality products and the like.

In this embodiment, the human-computer cooperation cloud platform 100 and the information verification terminal 200 in the cloud computing and 5G interconnection based information analysis system 10 may cooperatively execute the cloud computing and 5G interconnection based information analysis method described in the following method embodiment, and the detailed description of the following method embodiment may be referred to in the specific steps of executing the human-computer cooperation cloud platform 100 and the information verification terminal 200.

It should be noted that the human-computer cooperation cloud platform 100 may be a single server or a server cluster, and may be flexibly designed according to actual computing requirements. The human-computer cooperation cloud platform 100 may provide a big data service, such as an image big data service, an order big data service (e.g., an order big data service applied in a blockchain network), and the like, for each information verification terminal 200, which is not particularly limited herein.

In order to solve the technical problem in the foregoing background art, fig. 2 is a schematic flowchart of an information analysis method based on cloud computing and 5G interconnection provided in the embodiment of the present disclosure, and the information analysis method based on cloud computing and 5G interconnection provided in this embodiment may be executed by the human-computer cooperation cloud platform 100 shown in fig. 1, and the information analysis method based on cloud computing and 5G interconnection is described in detail below.

Step S110, obtaining the verification result information of each information verification terminal 200 in the target verification service interval, and obtaining the application scenario parameter data of each information verification terminal 200 in the target verification service interval.

Step S120, performing data analysis on the verification result information according to the application scenario parameter data, to obtain a verification adaptive result of each information verification terminal 200.

In this embodiment, the target verification service interval may be flexibly configured by an operator of the human-computer cooperation cloud platform 100, for example, a verification service tag with different personalized options may be set to form a target verification service interval. On this basis, the application scenario parameter data may include configuration update contents between the application scenario configuration node and the original configuration node within the target verification service interval and a scenario area classification of the application scenario configuration node.

The configuration node refers to a series of nodes that affect image security information verification, such as a scene attribute node, a scene connection port node, a scene output port node, and the like, formed in an application scene, and is not limited specifically herein. As such, an original configuration node may refer to a configuration node in an initial application scenario, while an application scenario configuration node may refer to a subsequently added or changed configuration node.

In addition, the scene area classification may be used to represent a scene source corresponding to the application scene configuration node, for example, an intelligent security scene source, an intelligent card punching scene source, and the like, and is not limited specifically herein.

In this embodiment, the verification result information may record a plurality of different scene verification sources, and the different scene verification sources may be used to record the verification result information of different statistical nodes or statistical projects.

Based on the above steps, in the embodiment, the data analysis is performed on the corresponding verification result information by combining the application scenario parameter data of each information verification terminal 200, so that the uncertainty of the application scenario configuration process of different information verification terminals 200 can be effectively adapted, and the verification adaptive analysis accuracy is improved.

In a possible implementation manner, step S120 may be further implemented by the following sub-steps, which are described in detail below.

And a substep S121, determining a target scene verification source of the verification result information corresponding to each application scene configuration node according to the configuration update content between the application scene configuration node and the original configuration node.

And a substep S122, performing data analysis on the target scene verification source of the verification result information corresponding to each application scene configuration node according to the scene region classification of each application scene configuration node, to obtain a verification adaptive result of each information verification terminal 200.

In addition, a person skilled in the art may also design other possible embodiments to specifically determine that the verification result information corresponds to the target scenario verification source of each application scenario configuration node.

Sub-step S1211, detecting a first scene pointing object of the application scene configuration node in the application scene and a second scene pointing object of the corresponding original configuration node in the application scene, respectively.

It should be noted that the first scene pointing object and the second scene pointing object may be respectively used to represent pointing objects corresponding to the source configuration directory when the application scene configuration node and the corresponding original configuration node are configured. For example, the pointing object may be some configuration update data segment, a configuration level update data segment, or the like.

In sub-step S1212, configuration update content between the application scene configuration node and the original configuration node is determined according to each first scene pointing object and the corresponding second scene pointing object.

It is worth mentioning that the configuration update content may include at least one configuration update project interval, each configuration update project interval being used for indicating an update data segment between the application scenario configuration node and the original configuration node.

For example, if the configuration update content includes a configuration update item interval 1, a configuration update item interval 2, and a configuration update item interval 3, the configuration update item interval 1, the configuration update item interval 2, and the configuration update item interval 3 are used to indicate that there is an update data segment 1, an update data segment 2, and an update data segment 3 between the application scene configuration node and the original configuration node.

And a substep S1213 of obtaining the digital contract certificate corresponding to each configuration update item interval from the configuration update content, and determining the edge service function and the edge access channel of each verification result item in the verification result information according to the digital contract certificate.

And a substep S1214, determining a target scene verification source of each application scene configuration node corresponding to the verification result information according to the edge service function and the edge access channel of each verification result item in the verification result information.

In one possible implementation, in this sub-step S1213, implementation can be based on the following detailed description.

(1) Each digital contract verification object is obtained from a digital contract certificate.

In this embodiment, each digital contract validation object may be used to represent a validation object each time a digital contract validation is initiated, such as a validation modification action, a validation culling action, and so on.

(2) And extracting contract verification monitoring variable results of each digital contract verification object, constructing a corresponding contract verification monitoring variable matrix, and processing access generation records of the verification result items according to the contract verification monitoring variable matrix aiming at each verification result item in the verification result information to obtain matching results of a plurality of different contract verification monitoring targets of the contract verification monitoring variable matrix as undetermined edge service functions of the access generation records so as to obtain the undetermined edge service functions of each verification result item.

(3) And matching the confidence coefficient that each edge service node of the undetermined edge service function is a cooperative sensing node and the cooperative sensing detection information of the verification result item of the edge service node relative to the contract verification monitoring target where the edge service node is located when each edge service node is the cooperative sensing node based on the to-be-determined edge service function of each verification result item.

(4) And determining edge service nodes with the confidence degrees higher than a preset confidence degree threshold value as cooperative sensing nodes, and determining the cooperative sensing detection information of the verification result item of the contract verification monitoring target determined by the cooperative sensing nodes based on the cooperative access behavior of the cooperative sensing detection information of each cooperative sensing node relative to the cooperative sensing detection information of the verification result item of the contract verification monitoring target where the cooperative sensing node is located.

(5) And removing the cooperative sensing detection information of the verification result item of the contract verification monitoring target determined more than twice in the cooperative sensing detection information of the verification result item of the contract verification monitoring target determined by each cooperative sensing node to obtain the cooperative sensing detection information of the verification result item of each undetermined contract verification monitoring target.

(6) And determining the edge service function and the edge access channel of each verification result item in the verification result information according to the cooperative sensing detection information of the verification result item of each to-be-determined contract verification monitoring target.

For example, the pending marginal business function of the access generation record may be input to the target decision classifier, and then the decision-making collaborative classification label output by the target decision classifier is processed based on the collaborative sensing detection information of the verification result item of each pending contract verification monitoring target, so as to generate the collaborative access behavior feature for characterizing the trend of the decision-making collaborative classification label of the pending contract verification monitoring target.

In the foregoing process, as a possible non-limiting example, in this embodiment, the cooperative access behavior unit may be obtained by extracting, based on the cooperative sensing probe information of the verification result item of each to-be-determined contract verification monitoring target, a corresponding cooperative access behavior from the decision cooperative classification tag output by the target decision classifier, and determining, based on the source path of the cooperative access behavior included in the cooperative access behavior unit, a mapping space of each source path.

Wherein, the range covered by each source path mapping space may include the source path of each cooperative access behavior in each cooperative access behavior unit.

And then, for each source path mapping space, merging the cooperative access behavior units, of which the source paths including the cooperative access behaviors are located in the source path mapping space, into a cooperative access behavior unit set, and for each cooperative access behavior unit in each cooperative access behavior unit set, determining an associated cooperative access behavior of the cooperative access behavior included in the cooperative access behavior unit, where the associated cooperative access behavior is a cooperative access behavior formed after the same type of cooperative access behaviors in each cooperative access behavior are associated.

Then, a common access node between every two associated collaborative access behaviors is determined, the common access node between the determined associated collaborative access behaviors is determined as a key behavior unit between corresponding collaborative access behavior units, and a vector set formed by collaborative feature vectors corresponding to the key behavior units between the collaborative access behavior units is used as collaborative access behavior features for representing the decision collaborative classification label trend of the verification monitoring target of the undetermined contract.

Further, the cooperative sensing probe information of the verification result item of the monitoring target may be verified based on the pending contract, determining a combined pending contract validation monitor target for each pending contract validation monitor target in the access production record, and calculating the Hamming distance between the cooperative access behavior characteristics of the undetermined contract verification monitoring targets and the cooperative access behavior characteristics of the corresponding combined undetermined contract verification monitoring targets as the correlation value between the undetermined contract verification monitoring targets and the corresponding combined undetermined contract verification monitoring targets, and the combined undetermined contract verification monitoring target with the correlation value between the combined undetermined contract verification monitoring target and the undetermined contract verification monitoring target being smaller than the preset correlation value threshold is used as the combined undetermined contract verification monitoring target related to the undetermined contract verification monitoring target, and each undetermined contract verification monitoring target and the related combined undetermined contract verification monitoring target are combined to form a contract verification monitoring target correlation combination. Therefore, edge service nodes corresponding to all contract verification monitoring targets in the contract verification monitoring target association combination are determined to serve as edge service functions of each verification result item based on the cooperative sensing detection information of the verification result items of all undetermined contract verification monitoring targets in the contract verification monitoring target association combination, and an edge access channel of each verification result item is obtained from the determined access information of the edge service functions of each verification result item.

In one possible implementation, in this sub-step S1214, implementation can be based on the following detailed description.

(1) And determining a scene verification source of each application scene configuration node corresponding to the verification result information according to the edge service function of each verification result item in the verification result information.

In this embodiment, by determining the edge service function of each verification result item in the verification result information, the edge service function of each application scenario configuration node corresponding to the verification result information can be determined, and thus, the location can be directly located in the scenario verification source of the verification result information corresponding to the edge service function of each application scenario configuration node.

(2) And respectively determining a target scene verification source of the verification result information corresponding to each application scene configuration node from scene verification sources of the verification result information corresponding to each application scene configuration node according to a verification target area corresponding to the edge access channel of each verification result item in the verification result information.

In this embodiment, the corresponding verification target area may be determined based on the edge access channel, that is, for different edge access channels, different verification target areas may be located, so that the target scene verification source of each application scene configuration node corresponding to the verification result information may be further determined from the scene verification source determined in (1) above.

In a possible implementation manner, regarding the sub-step S122, a possible example is further given below to set forth a non-limiting description on a specific implementation thereof.

And a substep S1221, obtaining a configuration option sequence and each option characterization function of each application scene configuration node according to the scene region classification of each application scene configuration node.

In this embodiment, the configuration option sequence may be used to record the configuration options of each application scenario configuration node, and the option characterization function is used to characterize a matching function of each application scenario configuration node under different configuration options. The configuration option may refer to a service program component when the network protocol is verified each time, and may be specifically determined according to a real-time service requirement.

And a substep S1222, performing data analysis on the target scene verification source corresponding to each application scene configuration node in the verification result information according to the configuration option sequence, to obtain a target option characterization function under the hot spot scene configuration data segment corresponding to each application scene configuration node.

In this embodiment, the hotspot scene configuration data segment may include an area verified by a set number range of configuration options.

And a substep S1223, obtaining a verification adaptive result of each information verification terminal 200 according to the target option characterization function under the hotspot scene configuration data segment corresponding to each application scene configuration node.

For example, in sub-step S1222, in this embodiment, data analysis may be specifically performed on the target scene verification source of the verification result information corresponding to each application scene configuration node according to the configuration option sequence, and when it is determined that the target scene verification source of each application scene configuration node includes the hot scene configuration data segment, according to the option characterization function and the feature item ratio of each application scene configuration node in the corresponding hot scene configuration data segment, the feature item association relationship between each option characterization function of each application scene configuration node in the corresponding non-hot scene configuration data segment and each option characterization function in the hot scene configuration data segment corresponding to the application scene configuration node is determined, and the feature item strength of the option characterization function of each application scene configuration node in the corresponding non-hot scene configuration data segment and in the hot scene configuration data segment corresponding to the application scene configuration node is determined And transferring the option representation function of the incidence relation to a hotspot scene configuration data segment corresponding to the application scene configuration node.

The strong association relationship of the feature items can be used for representing the association relationship corresponding to the condition that the mutual verification proportion between the feature items is larger than the set proportion threshold value.

Exemplarily, in the sub-step S1223, it may be implemented based on the following detailed description.

(1) And aiming at each application scene configuration node, establishing a corresponding verification depth distribution graph according to the verification repeatability of each option representation function under the hotspot scene configuration data segment corresponding to the application scene configuration node.

In this embodiment, the verification depth distribution map is an understandable depth-divided region map, each depth region corresponds to a depth region weight, and each depth region weight has at least one verification repetition degree distribution. For example, the verification depth profile may include a depth region a, a depth region B, a depth region C, and a depth region D, and the depth region weights corresponding to the depth region a, the depth region B, the depth region C, and the depth region D are different, that is, the verification repetition degree distributions corresponding to the depth region a, the depth region B, the depth region C, and the depth region D are different.

(2) And determining the verification interaction thread of each option representation function corresponding to the application scene configuration node, and determining the verification interaction service identifier corresponding to the verification interaction thread of each option representation function.

In this embodiment, the verification interactive thread may be understood as an authority thread having a certain verification adaptive problem when accessing the related authority, and may specifically be configured in advance, for example, a mapping relationship between the option characterization function and the verification interactive thread may be configured.

(3) Mapping each verification interactive service identifier to a verification depth distribution map, determining a depth region where each verification interactive service identifier is located, determining a verification interaction confidence coefficient between an option characterization function corresponding to the depth region and the verification interactive service identifier according to the depth region weight of the depth region where each verification interactive service identifier is located, and determining a verification self-adaptive parameter of the option characterization function corresponding to the verification interactive service identifier based on the verification interaction confidence coefficient.

(4) And obtaining the verification self-adaptive result of each information verification terminal 200 according to all the determined verification self-adaptive parameters.

In one possible example, in the description of part (4) of this sub-step S1223, regular expression matching may be performed on all the determined verification adaptive parameters, and a proportion of the verification adaptive parameters in a preset rule format among all the verification adaptive parameters is determined.

In this embodiment, the preset rule format may be used to characterize that the verification adaptive parameter has a specific threat parameter. Where a regular expression is a logical formula operating on a string of characters (including common characters (e.g., letters between a and z) and special characters (called "meta characters")), a "regular string" can be formed by using specific characters defined in advance and a combination of the specific characters, and the "regular string" is used to express a filtering logic on the string of characters.

On this basis, it may be determined whether the proportion of the verification adaptive parameters having the preset rule format among all the verification adaptive parameters reaches a set proportion threshold, and the set proportion threshold is determined according to the number of times of the historical threat state of each information verification terminal 200, for example, a preset mapping relationship between the set proportion threshold and the number of times of the historical threat state of the information verification terminal 200 may be set, and if the number of times of the historical threat state is more, the set proportion threshold is smaller.

Next, when the ratio of the verification adaptive parameters having the preset rule format among all the verification adaptive parameters reaches the set ratio threshold or not, it is determined that the corresponding information verification terminal 200 has verification adaptive abnormality, otherwise it is determined that the information verification terminal 200 has no verification adaptive abnormality.

It should be noted that, when it is determined that the information verification terminal 200 has the verification adaptive anomaly, the embodiment may further extract a corresponding target verification adaptive anomaly parameter from the verification adaptive parameters having the preset rule format corresponding to the information verification terminal 200, and locate a first adaptive update node corresponding to each adaptive update interface from the adaptive object after extracting the adaptive object of the target verification adaptive anomaly parameter, so as to determine whether the first adaptive update node corresponding to each adaptive update interface in the adaptive object has an associated entry node relative to a second adaptive update node in the adaptive object, where the second adaptive update node is a node in the adaptive object except the first adaptive update node.

If the first adaptive update node corresponding to each adaptive update interface in the adaptive object has an associated table entry node relative to the second adaptive update node in the adaptive object, determining the first adaptive update node corresponding to each adaptive update interface located in the adaptive object as an effective adaptive update node of the adaptive object, otherwise, fusing the first adaptive update node corresponding to each adaptive update interface located in the adaptive object with the second adaptive update node in the adaptive object to obtain the effective adaptive update node of the adaptive object.

Then, aiming at each self-adaptive updating interface, extracting first verification process information of the self-adaptive updating interface in a verification protocol node of a server, fusing part of nodes in an effective self-adaptive updating node of a self-adaptive object with the first verification process information to obtain second verification process information, respectively simulating the first verification process information and the second verification process information in a protocol process corresponding to the verification protocol node to obtain corresponding first verification simulation information and second verification simulation information, judging whether the similarity of the first verification simulation information and the second verification simulation information reaches a preset similarity threshold, starting the self-adaptive updating interface to simulate the second verification process information when the similarity of the first verification simulation information and the second verification simulation information reaches the preset similarity threshold, and obtaining third verification simulation information corresponding to the second verification process information, and extracting an abnormal class label in the third verification simulation information, obtaining an updating strategy corresponding to the self-adaptive updating interface according to the abnormal class label, and returning to the operation of fusing part of nodes in the effective self-adaptive updating nodes of the self-adaptive object with the first verification process information to obtain second verification process information when the similarity between the first verification simulation information and the second verification simulation information does not reach a preset threshold value.

In a possible implementation manner, for step S110, in the process of acquiring the verification result information of each information verification terminal 200 in the target verification service interval, in order to ensure the verification accuracy and reliability in the current verification process of executing the image information, the image verification of the complete verification flow is usually performed, so that the pertinence of the verification process is poor, and the verification reliability is not high. Based on this, step S110 may be further realized by the following exemplary sub-steps, which are described in detail below.

Step S111, acquiring an image object tag of the image acquisition verification information in the process of executing image information acquisition by the information verification terminal 200, determining a verification image node grid according to an image verification service of the image object tag, and acquiring a verification signature behavior sequence and signature connection graph information of each corresponding verification analysis information generated by the verification image node grid in the process of verifying the image acquisition verification information.

Step S112, the verification signature behavior sequence and the signature connection graph information are respectively input into the support vector machine classifier obtained through configuration, a first signature verification vector set of each verification analysis information is extracted through a first decision boundary of the support vector machine classifier, and a second signature verification vector set of each verification analysis information is extracted through a second decision boundary of the support vector machine classifier.

And step S113, fusing the first signature verification vector set and the second signature verification vector set through a fusion decision function of the support vector machine classifier to obtain a target signature verification vector set.

Step S114, determining a verification extended object of each verification analysis information corresponding to the image object label according to the target signature verification vector set, respectively generating corresponding extended signature verification information of each verification analysis information according to the verification extended object, performing secondary verification on the verification analysis information according to the extended signature verification information, and storing a verification result after the secondary verification into a secondary verification big data collection library.

In this embodiment, the image object tag is used to indicate a verification type of an object to be verified in the process of performing image information acquisition, and may be, but is not limited to, a secure access verification type, a secure read verification type, an access interaction verification type, and the like.

In this embodiment, the image verification service is used to represent a logic service invoked during image verification for the image object tag, and the logic service is used to represent an associated logic relationship between all verification items and each verification item, for example, when the verification item a, the verification item B, and the verification item C are included, the image verification service may be used to represent a verification relationship between the verification item a, the verification item B, and the verification item C, and a verification relationship between the verification item a, the verification item B, and the verification item C, for example, the verification item a and the verification item C are juxtaposed and located after the verification item B.

In this embodiment, the verification image node grid may be used to represent a logical grid formed by verification items as verification image nodes, and still in the above example, may represent a logical grid formed by verification item a, verification item B, and verification item C according to the logic "verification item a and verification item C are juxtaposed and located after verification item B".

In this embodiment, each verification signature behavior in the verification signature behavior sequence is used to represent process information of a digital signature generated in a verification process for each verification item, for example, an interaction behavior of the digital signature, a test behavior of the digital signature, and the like, and the signature connectivity graph information may be used to represent a connectivity migration relationship between digital signatures generated each time, for example, switching from the interaction behavior of the digital signature to the test behavior of the digital signature.

Based on the above steps, in the embodiment, the information verification terminal 200 is combined to execute the image object tag of the image acquisition verification information in the image information acquisition process, so that a more targeted verification logic can be performed for the image verification service of the image object tag, and a verification extended object is further derived on the basis, so that a more targeted verification is performed by further combining with subsequent extended signature verification information, and thus, the verification reliability is improved.

In a possible implementation manner, for step S111, the signature connectivity graph information may specifically include a signature verification node, a signature flow direction before and after verification, and a signature direction item.

The signature verification node may refer to a time node or an area node when the connected graph is signed, the signature flow directions before and after verification may refer to a signature field before the connected graph is signed and a signature field after the connected graph is signed, and the signature pointing item may refer to a position where the communication node is located when the connected graph is signed.

On this basis, step S112 may be embodied by the following exemplary sub-steps, which are described in detail below.

And a substep S1121, inputting the verification signature behavior sequence to a first decision boundary, and performing feature extraction on the verification signature behavior in the verification signature behavior sequence to obtain corresponding verification signature behavior features.

And a substep S1122 of clustering the verification signature behavior characteristics by using the first decision boundary and the clustering script corresponding to the image verification service to obtain the clustered verification signature behavior characteristics.

And a substep S1123 of extracting a first signature verification vector set of each verification analysis information according to the verification signature behavior characteristics after the clustering processing.

And a substep S1124 of inputting the signature connected graph information to the second decision boundary, and performing feature extraction on the signature connected graph information to obtain signature verification node features, signature pointing item features and signature flow direction features before and after verification.

And in the substep S1125, clustering the signature verification node characteristics, the signature pointing item characteristics and the signature flow direction characteristics before and after verification by using a second decision boundary and a clustering script corresponding to the image verification service to obtain a signature connected graph information matrix.

And a substep S1126 of obtaining verification signature behavior characteristics corresponding to the verification signature behavior sequence, inputting the verification signature behavior characteristics into the signature connection diagram information matrix for characteristic fusion to obtain a fused target characteristic sequence, and extracting a second signature verification vector set of each verification analysis information according to the target characteristic sequence.

In a possible implementation manner, for step S113, in order to improve the fusion efficiency, in this embodiment, feature positions of the first signature verification vector set and the second signature verification vector set, which respectively correspond to one another one by one, are fused through a fusion decision function of the support vector machine classifier to obtain a target signature verification vector set.

In one possible implementation manner, for step S114, in order to accurately determine the verification extension object of the image object tag corresponding to each piece of verification resolution information, the following exemplary sub-steps may be implemented in detail, which are described in detail below.

And a substep S1141 of obtaining digital signature rule information corresponding to the digital signature object acquired by the image information of the associated image object label from the target signature verification vector set, wherein the digital signature rule information is obtained by performing rule identification on the digital signature negotiation information in the target signature verification vector set by adopting a rule identification form matched with the signature type of the corresponding digital signature object.

And a substep S1142 of negotiating and interacting the digital signature rule information sent by each corresponding digital signature object according to the negotiation and interaction mode respectively matched with each rule identification form to obtain corresponding digital signature negotiation information.

In sub-step S1143, negotiation status analysis is performed on each piece of digital signature negotiation information, and a negotiation status parameter corresponding to each digital signature object is determined. The negotiation condition parameter is used for reflecting the frequency degree of image information acquisition of the digital signature object of the associated image object label.

And a substep S1144 of screening the negotiation behavior targets with the largest negotiation times from the negotiation status parameters corresponding to the digital signature objects, and determining the extension confidence degrees corresponding to the digital signature objects according to the association degrees between the negotiation status parameters corresponding to the digital signature objects and the negotiation behavior targets with the largest negotiation times. And the extension confidence degree corresponding to the digital signature object is positively correlated with the corresponding correlation degree.

And a substep S1145 of performing object analysis on the digital signature negotiation information of the digital signature object with the expansion confidence degree greater than the set expansion confidence degree, and obtaining a verification expansion object of the image object label corresponding to each piece of verification analysis information according to the expansion output sequence number in the object analysis result, wherein each expansion output sequence number and each verification expansion object are in one-to-one correspondence.

In a possible implementation manner, still referring to step S114, in the process of generating the extended signature verification information of each corresponding verification analysis information according to the verification extended object, the following sub-steps may be specifically further implemented, which are described in detail below.

And a substep S1146 of obtaining random coding information corresponding to the verification extension object during verification extension, wherein the random coding information includes at least one random coding node.

And a substep S1147 of calculating a coding feature vector corresponding to the random coding information, wherein the coding feature vector represents a coding public key sequence of the random coding information relative to each coding extension type in the virtual extension process.

And a substep S1148, if the coding feature range of the coding feature vector is greater than or equal to the set confidence threshold, calculating a coding feature vector sequence of the random coding information in the formal verification process, where the coding feature vector sequence includes at least one of a target total coding feature vector and a target unit coding feature vector, the target total coding feature vector represents a coding public key sequence of the random coding information corresponding to each coding extension type, and the target unit coding feature vector represents a coding public key sequence of a random coding node corresponding to the most previous unit coding feature vector in the random coding information corresponding to each coding extension type.

And a substep S1149 of determining an extended signature verification object corresponding to the random coding information according to the coding feature vector sequence, and generating extended signature verification information of each corresponding verification analysis information according to the extended signature verification object.

Under the same inventive concept, fig. 3 is a schematic diagram of functional modules of the information analysis device 300 based on cloud computing and 5G interconnection provided in the embodiment of the present disclosure, and this embodiment may divide the functional modules of the information analysis device 300 based on cloud computing and 5G interconnection according to the method embodiment executed by the human-computer cooperation cloud platform 100, that is, the following functional modules corresponding to the information analysis device 300 based on cloud computing and 5G interconnection may be used to execute each method embodiment executed by the human-computer cooperation cloud platform 100. The information analysis apparatus 300 based on cloud computing and 5G interconnection may include an obtaining module 310 and a data analysis module 320, and the functions of the functional modules of the information analysis apparatus 300 based on cloud computing and 5G interconnection are described in detail below.

An obtaining module 310, configured to obtain verification result information of each information verification terminal 200 in a target verification service interval, and obtain application scenario parameter data of each information verification terminal 200 in the target verification service interval from the information verification terminal, where the application scenario parameter data includes configuration update content between an application scenario configuration node and an original configuration node in the target verification service interval and a scenario area classification of the application scenario configuration node. The obtaining module 310 may be configured to perform the step S110, and the detailed implementation of the obtaining module 310 may refer to the detailed description of the step S110.

And the data analysis module 320 is configured to perform data analysis on the verification result information according to the application scenario parameter data to obtain a verification adaptive result of each information verification terminal 200. The data analysis module 320 may be configured to perform the step S120, and the detailed implementation of the data analysis module 320 may refer to the detailed description of the step S120.

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 verified by the processing element; or may be implemented entirely in hardware; part of the modules can also be realized in the form of processing element verification software, and part of the modules can be realized in the form of hardware. For example, the obtaining 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 function of the obtaining module 310 may be verified and executed by a processing element of the apparatus. 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.

For example, the above modules may be one or more integrated circuits configured to implement the above methods, such as: one or more Application Specific Integrated Circuits (ASICs), or one or more microprocessors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs), among others. For another example, when some of the above modules are implemented in the form of a processing element scheduler code, the processing element may be a general purpose processor, such as a Central Processing Unit (CPU) or other processor that can validate the code. As another example, these modules may be integrated together, implemented in the form of a system-on-a-chip (SOC).

Fig. 4 illustrates a hardware structure diagram of the human-computer cooperation cloud platform 100 for implementing the control device according to the embodiment of the present disclosure, and as shown in fig. 4, the human-computer cooperation cloud platform 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 module 310 and the data analysis module 320 included in the cloud computing and 5G interconnection-based information parsing apparatus 300 shown in fig. 3), so that the processor 110 may perform the cloud computing and 5G interconnection-based information parsing method 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 transceiver action of the transceiver 140, so as to transmit and receive data with the aforementioned information verification terminal 200.

For a specific implementation process of the processor 110, reference may be made to the above-mentioned method embodiments executed by the human-computer cooperation cloud platform 100, and implementation principles and technical effects thereof are similar, and details of this embodiment 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, the embodiment of the disclosure also provides a readable storage medium, in which computer execution instructions are stored, and when a processor executes the computer execution instructions, the information analysis method based on cloud computing and 5G interconnection is implemented.

The readable storage medium described above may be implemented by any type of volatile or non-volatile memory device or combination thereof, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk. Readable storage media can be any available media that can be accessed by a general purpose or special purpose computer.

Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present disclosure, and not for limiting the same; while the present disclosure has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present disclosure.

Claims

1. An information analysis method based on cloud computing and 5G interconnection is characterized by being applied to a man-machine cooperation cloud platform, the man-machine cooperation cloud platform is in communication connection with a plurality of information verification terminals, and the information verification terminals are in edge communication with the man-machine cooperation cloud platform through a 5G network provided by Internet of things equipment, and the method comprises the following steps:

performing data analysis on the verification result information according to the application scene parameter data to obtain a verification self-adaptive result of each information verification terminal;

the step of obtaining the verification result information of each information verification terminal in the target verification service interval comprises the following steps:

determining a verification extended object of which each verification analysis information corresponds to the image object label according to the target signature verification vector set, respectively generating corresponding extended signature verification information of each verification analysis information according to the verification extended object, and storing a verification result after secondary verification into a secondary verification big data collection library after carrying out secondary verification on the verification analysis information according to the extended signature verification information;

the image object tag is used for representing the verification type of an object to be verified in the image information acquisition process executed this time, and the verification type comprises a safety access verification type, a safety reading verification type and an access interaction verification type;

the image verification service is used for representing a logic service called in the image verification process aiming at the image object label, and the logic service is used for representing all verification items and the associated logic relation between each verification item;

the verification image node grid is used for representing a logic grid formed by taking verification items as verification image nodes.

2. The information analysis method based on cloud computing and 5G interconnection according to claim 1, wherein the step of performing data analysis on the verification result information according to the application scenario parameter data to obtain a verification adaptive result of each information verification terminal includes:

3. The information parsing method based on cloud computing and 5G interconnection according to claim 2, wherein the step of determining that the verification result information corresponds to the target scene verification source of each application scene configuration node according to the configuration update content between the application scene configuration node and the original configuration node comprises:

4. The information parsing method based on cloud computing and 5G interconnection according to claim 3, wherein the step of determining an edge service function and an edge access channel of each verification result item in the verification result information according to the digital contract certificate comprises:

5. The information analysis method based on cloud computing and 5G interconnection as claimed in claim 4, wherein the step of determining the edge service function and the edge access channel of each verification result item in the verification result information according to the cooperative sensing detection information of the verification result item of each pending contract verification monitoring target comprises:

6. The information analysis method based on cloud computing and 5G interconnection according to claim 3, wherein the step of determining, according to the edge service function and the edge access channel of each verification result item in the verification result information, that the verification result information corresponds to the target scene verification source of each application scene configuration node includes:

7. The information analysis method based on cloud computing and 5G interconnection according to claim 2, wherein the step of performing data analysis on the target scene verification source of the verification result information corresponding to each application scene configuration node according to the scene area classification of each application scene configuration node to obtain the verification adaptive result of each information verification terminal includes:

8. The information analysis method based on cloud computing and 5G interconnection according to claim 1, wherein the step of obtaining the verification adaptive result of each information verification terminal according to the target option characterization function under the hotspot scene configuration data segment corresponding to each application scene configuration node comprises:

9. The information analysis system based on cloud computing and 5G interconnection is characterized by comprising a man-machine cooperation cloud platform and a plurality of information verification terminals in communication connection with the man-machine cooperation cloud platform;

the man-machine cooperation cloud platform is used for carrying out data analysis on the verification result information according to the application scene parameter data to obtain a verification self-adaption result of each information verification terminal;

the method for acquiring the verification result information of each information verification terminal in the target verification service interval by the man-machine cooperation cloud platform comprises the following steps:

10. A man-machine cooperation cloud platform, comprising a processor, a machine-readable storage medium and a network interface, wherein the machine-readable storage medium, the network interface and the processor are connected through a bus system, the network interface is used for being in communication connection with at least one information verification terminal, the machine-readable storage medium is used for storing programs, instructions or codes, and the processor is used for executing the programs, the instructions or the codes in the machine-readable storage medium to execute the cloud computing and 5G interconnection-based information parsing method according to any one of claims 1 to 9.