CN115085941A - Computer data information processing method based on block chain network - Google Patents
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Abstract
The invention discloses a computer data information processing method based on a block chain network, which comprises the following steps: (S1) issuing the network data information, outputting and transferring the network data information to the next application device; (S2) controlling data transmission through the network data interactive communication interface in the internet data communication system; (S3) connecting the node devices by block chain links connected in a chain, and communicating with each other by a block chain network; (S4) receiving, by the blockchain network node, data information sent by the network data sending terminal, for implementing calculation of the network data information; (S5) outputting the calculated network data information to meet the user' S demand. The invention can realize the decentralization, traceability and non-tampering of network data information by applying the blockchain network, and realizes the encryption and processing capabilities of the network data information through an encryption algorithm and an improved C4.5 decision tree algorithm model.
Description
Technical Field
The invention relates to the technical field of internet, in particular to a computer data information processing method based on a block chain network.
Background
With the continuous development of internet information technology, computers are widely used in different fields. Under the promotion of the development of digitalization, informatization and networking, especially the development of information globalization, the construction and wide application of a network information platform is promoted, and network data information is developed explosively, so that the current network data information has the problems of large data volume of a characteristic book, low processing efficiency, unsafe data in the interaction process, easy data leakage, data falsification and the like, and the safety performance is low in the interaction process of the network data information and the data information after the network data information is processed.
Disclosure of Invention
Aiming at the technical defects, the invention discloses a computer data information processing method based on a block chain network, which realizes the interaction of data information by applying the block chain network, improves the data information interaction capability, and adopts the following technical scheme in order to realize the technical effect:
a computer data information processing method based on a block chain network comprises the following steps:
(S1) issuing the network data information, outputting and transferring the network data information to the next application device;
in the step, when the network data information is sent out, the network data information is marked with data information compatible with the block chain network, and the tracking in the network data information transmission process is realized by marking a timestamp or a network data information identifier on the data information;
(S2) controlling data transmission through the network data interactive communication interface in the internet data communication system;
in the step, network data information transmission is realized by controlling the network data information nodes during data transmission control, and network data information node information interaction is synchronously realized in the data transmission control process;
(S3) connecting the node devices through the block chain nodes connected in a chain manner, and communicating with each other through the block chain network, so that the sent network data information can be interacted and transmitted through the block chain network;
in the step, the encryption of the data information of the block link point is realized through a symmetric encryption algorithm; the decryption of the data information of the block chain link point is realized by a symmetrical decryption method, and further the primary encryption of the data information of the block chain link point is realized;
encrypting data information through a public key of a receiver, then generating a data ciphertext, when receiving data, firstly calculating an abstract of transmitted data by using a hash function in a block chain, and then digitally signing the abstract through a private key; the data sender simultaneously sends a data ciphertext and a signature, and the receiver decrypts the data through a public key so as to realize encryption and decryption calculation of internet data information;
in the step, the second-level encryption of the data information of the block chain link point is realized through an elliptic curve equation;
(S4) receiving data information sent by a network data sending terminal through the block chain network node to realize the calculation of the network data information;
in the step, the processing of the network data information is realized through an improved C4.5 decision tree algorithm model, wherein the improved C4.5 decision tree algorithm model comprises a drosophila optimization algorithm model, so that the classification capability of the network data information is improved;
(S5) outputting the calculated network data information to meet the user' S demand.
As a further technical solution of the present invention; the improved C4.5 decision tree algorithm model is a classification algorithm model fused with a drosophila optimization algorithm model.
As a further technical solution of the present invention; the improved C4.5 decision tree algorithm model is carried out by the following steps:
(1) extracting data information from network data nodes, the network data information set being recorded asDividing network data information intoA classification module, thenIs provided withAn attribute tag, defineFor each set of the attribute tags, a set of attributes,(ii) a Suppose thatIs aThe expected values required for a fixed sample classification for the network data samples in (1) are:
(2) constructing a drosophila optimization algorithm model, realizing global optimization retrieval to improve the network data classification retrieval capability,
(3) and (3) carrying out data classification on the network data information set S through the network data nodes retrieved by the drosophila optimization algorithm model, and recording classified subset information as:
(4) calculating information gain for the retrieved network data node data information, and subtracting the currently received data information from the input data node data information, then:
(5) the information gain ratio of the information gain calculation attribute a is calculated by calculating the information gain for the retrieved network data node data information, and is written as:
the data information of the network data node is classified as:
through continuous data calculation, willAnd if the data set is independently represented, outputting the data information classification attribute of the network data node.
As a further technical solution of the present invention; the construction method of the drosophila optimization algorithm model comprises the following steps:
(A) randomly initializing the fruit fly group position, namely the position of network node data information in the Internet; the positions are defined as follows:
(B) giving the fruit fly individual a random direction and distance for searching network node data information by using smell;
(C) since the position of the network node data information can not be obtained, the distance between the network node data information source point and the network node data information source point is estimated firstlyThen, the taste concentration judgment value is calculatedThe value is the inverse of the distance,
(D) taste concentration determination valueSubstituting into taste concentration determination function to obtain taste concentration of individual fruit fly position;
(E) Finding out the fruit flies with the highest taste concentration in the fruit fly population;
(F) keeping the optimal taste concentration value and the x, y coordinates, and enabling the fruit fly colony to fly to the position by using vision;
(G) and (4) entering iterative optimization, repeatedly executing the steps B-E, judging whether the taste concentration is superior to the previous taste concentration, and executing the step F if the taste concentration is superior to the previous taste concentration.
As a further technical solution of the present invention; the drosophila optimization algorithm model realizes network data information definition recognition by constructing a logical chaotic mapping theoretical model, wherein the logical chaotic mapping theoretical model is as follows:
n represents the iteration times of the drosophila model for network data node information retrieval in the continuous calculation process, and u is a chaotic control network data node information parameter;
network data node information chaos variable C xi The formula of (1) is:
wherein x (n) i Is the ith chaotic variable C after the chaotic value is changed in the network data node information retrieval process xi (ii) a When C is present xi ∈[0,1]And C xi When the element belongs to {0.34, 0.52 and 0.79}, the improved C4.5 decision tree algorithm model is in a chaotic state; then iterative computation is needed again for stimulation;
in the formula (18), x i ∈[a i ,b i ]Available C xi The following modifications are made by expressions (17) and (18):
wherein x i And the value of the information chaotic variable of the ith network data node is expressed, and the variable is converted into a conventional variable after chaotic mapping transformation.
A computer data information processing system based on a blockchain network, comprising:
a network data transmitting terminal; the system comprises a network data sending terminal, a network data sending terminal and a network data sending terminal, wherein the network data sending terminal is used for sending network data information and outputting and transmitting the network data information to next application equipment;
a communication controller; in the internet data communication system, between the data circuit and the host, the communication interface device for controlling the data transmission;
a block chain network module; the node equipment is connected through block chain link points connected in a chain manner, and are connected and communicated with each other through a block chain network, the block chain network module is sequentially provided with a data layer, a network layer, a consensus layer, an excitation layer and an intelligent contract layer from bottom to top, and the block chain network module is a master-slave block chain structure model; and a data application terminal; the data application terminal is provided with an improved C4.5 decision tree model, and the improved C4.5 decision tree model is provided with a block chain network node;
the output end of the network data sending terminal is connected with the input end of the communication controller, the output end of the communication controller is connected with the input end of the block chain network module, and the output end of the block chain network module is connected with the input end of the data application terminal.
Positive and advantageous effects
According to the invention, the node devices are connected by adopting the block chain nodes connected in a chain manner, so that the convenience in the network data interaction process is improved, the network data information safety capability is improved by applying the block chain network, the decentralized, traceable and non-falsification capabilities of the network data information can be realized, the safety capability in the network data interaction process is improved by an encryption algorithm, the processing capability of the network data information is realized by an improved C4.5 decision tree algorithm model, and the network data information application capability is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the prior art descriptions will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without inventive labor, wherein:
FIG. 1 is a schematic flow diagram of the process of the present invention;
FIG. 2 is a schematic flow chart of the C4.5 algorithm of the present invention;
FIG. 3 is a schematic flow chart of a fruit fly algorithm model according to the present invention;
FIG. 4 is a schematic diagram of data information interaction in a blockchain network according to the present invention;
FIG. 5 is a diagram of an elliptical algorithm function according to the present invention;
FIG. 6 is a schematic view of an iterative calculation of a drosophila optimization algorithm model according to the present invention;
FIG. 7 is a schematic diagram of the system of the present invention;
FIG. 8 is a block chain architecture of the present invention;
FIG. 9 is a block chain node architecture diagram of the present invention;
FIG. 10 is a diagram of a master-slave blockchain architecture according to the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, and it should be understood that the embodiments described herein are merely for purposes of illustration and explanation, and are not intended to limit the present invention.
As shown in fig. 1, a method for processing computer data information based on a blockchain network includes the following steps:
(S1) issuing the network data information, outputting and transferring the network data information to the next application device;
in the step, when the network data information is sent out, the network data information is marked with data information compatible with the block chain network, and the tracking in the network data information transmission process is realized by marking a timestamp or a network data information identifier on the data information;
(S2) controlling data transmission through the network data interactive communication interface in the internet data communication system;
in the step, network data information transmission is realized by controlling the network data information nodes during data transmission control, and network data information node information interaction is synchronously realized in the data transmission control process;
(S3) connecting the node devices through the block chain nodes connected in a chain manner, and communicating with each other through a block chain network, so that the sent network data information is interacted and transmitted through the block chain network;
in the step, the encryption of the data information of the block link point is realized through a symmetric encryption algorithm; the decryption of the data information of the block chain link point is realized by a symmetrical decryption method, and further the primary encryption of the data information of the block chain link point is realized;
encrypting data information through a public key of a receiver, then generating a data ciphertext, when receiving data, firstly calculating an abstract of transmitted data by using a hash function in a block chain, and then digitally signing the abstract through a private key; the data sender sends the data cipher text and the signature at the same time, and the receiver decrypts the data through the public key, so as to realize encryption and decryption calculation of the internet data information;
in the step, the second-level encryption of the data information of the block link point is realized through an elliptic curve equation;
(S4) receiving, by the blockchain network node, data information sent by the network data sending terminal, for implementing calculation of the network data information;
in the step, the processing of the network data information is realized through an improved C4.5 decision tree algorithm model, wherein the improved C4.5 decision tree algorithm model comprises a drosophila optimization algorithm model, so that the classification capability of the network data information is improved;
(S5) outputting the calculated network data information to satisfy the user' S demand.
According to the invention, the node devices are connected by adopting the block chain nodes connected in a chain manner, so that the convenience in the network data interaction process is improved, the network data information safety capability is improved by applying the block chain network, the decentralized, traceable and non-falsification capabilities of the network data information can be realized, the safety capability in the network data interaction process is improved by an encryption algorithm, the processing capability of the network data information is realized by an improved C4.5 decision tree algorithm model, and the network data information application capability is improved.
In the above steps, as shown in fig. 3, the method for implementing the secondary encryption of the network data information by the elliptic curve equation is as follows:
an elliptic curve function is constructed, and a function equation model is constructed as follows:
in formula (1), there are 3 focal points of the non-vertical line and the curve, and on the non-vertical line, the tangent line intersects the curve at other points, and it is assumed that there are 2 points Q and P, where Q and P intersectThen, there are:
wherein R is substituted withSymmetrical about the X axis. When the point Q is coincident with the point P, assuming that the coincident point is D, the straight line is tangent to the curve,indicated as intersection points. Then there is the formula:
since there are 3 intersections, a =3, the formula can be transformed into:
Q=3P (5)
when performing encryption calculation in a block chain, assuming that a modulus is p, a base point is G, and an ordinal number is n, then:
public key = private key G; (6)
the Q point and the P point represent two different points on the curve, which can be calculated by the following formula:
the encryption of the public key is completed through the algorithm, and when the private key encryption is completed, the data z is encrypted by adopting the private key dA, and the method is adopted: selecting data k, let:then, the following formula is used for calculation:
then, calculating:
if s =0 is obtained after the final calculation, the calculation is re-performed. A data signature (r, s) is then generated, implementing the private keying. The safety of the human resource information is ensured.
In the above embodiment, the improved C4.5 decision tree algorithm model is a classification algorithm model fused with a drosophila optimization algorithm model.
As shown in fig. 2, in the above embodiment, the improved C4.5 decision tree algorithm model is performed by the following steps:
(1) extracting data information from network data nodes, the network data information set being recorded asPartitioning network data information intoA classification module, thenIs provided withAn attribute tag, defineFor each set of the attribute tags, a set of attributes,(ii) a Suppose thatIs aThe expected values required for a fixed sample classification for the network data samples in (1) are:
(2) constructing a drosophila optimization algorithm model, realizing global optimization retrieval to improve the network data classification retrieval capability,
as shown in fig. 4, the drosophila optimization algorithm (FOA) can implement a global optimization search, mainly based on the search of network data information types: the network node or the network data information, the block chain network node and the like are searched to sense the source of the network data information, and the position of the relevant network node data information is sent to search for useful information through sensitive vision, so that the capability and the working efficiency of the data node in classification are improved.
(3) And (3) carrying out data classification on the network data information set S through the network data nodes retrieved by the drosophila optimization algorithm model, and recording classified subset information as:
(4) calculating information gain for the retrieved network data node data information, and subtracting the currently received data information from the input data node data information, then:
(5) the information gain ratio of the attribute a is calculated by calculating the information gain for the retrieved network data node data information, and is referred to as:
the data information of the network data node is classified as:
through continuous data calculation, willAnd if the data set is independently represented, outputting the data information classification attribute of the network data node.
In the specific embodiment, the generated decision tree can be pruned through a C4.5 algorithm, a decision tree model is continuously perfected, and support is provided for subsequent data classification.
In the above embodiment, as shown in fig. 3, the construction method of the drosophila optimization algorithm model is as follows:
(A) randomly initializing the fruit fly group position, namely the position of network node data information in the Internet; the positions are defined as follows:
(B) giving the fruit fly individual a random direction and distance for searching network node data information by using smell;
(C) since the position of the network node data information can not be obtained, the distance between the network node data information source point and the network node data information source point is estimated firstlyThen, the taste concentration judgment value is calculatedThe value is the inverse of the distance,
(D) taste concentration determination valueSubstituting into taste concentration determination function to obtain taste concentration of individual fruit fly position;
(E) Finding out the fruit flies with the highest taste concentration in the fruit fly population;
(F) keeping the optimal taste concentration value and the x, y coordinates, and enabling the fruit fly colony to fly to the position by using vision;
(G) and (4) entering iterative optimization, repeatedly executing the steps B-E, judging whether the taste concentration is superior to the previous taste concentration, and executing the step F if the taste concentration is superior to the previous taste concentration.
In the method, in order to improve the retrieval capability of the network node, a logical chaotic mapping theoretical model is constructed:
n represents the iteration times of the drosophila model for network data node information retrieval in the continuous calculation process, and u is a chaotic control network data node information parameter;
for some values of the network data node information parameter u (where u =4 is 1), the network data node information search system exhibits chaotic behavior.
Network data node information chaos variable C xi The formula of (1) is:
wherein x (n) i Is the ith chaotic variable C after the chaotic value is changed in the network data node information retrieval process xi (ii) a When C is present xi ∈[0,1]And C xi When the element belongs to {0.34, 0.52 and 0.79}, the improved C4.5 decision tree algorithm model is in a chaotic state; then the iterative calculation is needed again for stimulation;
in the formula (30), x i ∈[a i ,b i ]Available C xi The following modifications are made by expressions (4) and (5):
wherein x is i The value of the information chaotic variable of the ith network data node is expressed, and the variable is converted into a conventional variable after chaotic mapping transformation;
in conclusion, the linear decreasing step is very effective for improving the accuracy of the FOA, and meanwhile, the logical chaotic mapping can weaken the sensitivity of the initial network data node information retrieval condition of the optimization solution and improve the stability of the FOA data.
In a particular embodiment, the iteration steps are fixed in the processing of the FOA. That is, the drosophila search the engineering management project data information through fixed steps in the iterative optimization process, and by performing iterative calculations, the drosophila population is closer to the engineering management project data information, i.e., when the iterative steps are fixed, it is difficult to find the location of the engineering management project data information. The project management project data information is processed in the last few iterations. Perhaps some individual fruit flies are further and further away from the project management project data information. The Fruit Fly Optimization Algorithm is based on cooperation and competition behaviors of Fruit Fly populations in foraging processes, and the Fruit Fly Optimization Algorithm (FOA) is a new method for deducing and seeking global Optimization based on the Fruit Fly foraging behaviors.
The Fruit Fly Optimization Algorithm (FOA) is a new method for deriving global Optimization based on the foraging behavior of Fruit flies. The fruit fly is superior to other species in sense perception, particularly in smell sense and vision, the smell organ of the fruit fly can well collect various smells floating in the air, even can smell food sources beyond 40 kilometers, and then the fruit fly can also find the position where the food and a partner gather by using sharp vision after flying close to the position of the food and fly to the direction.
As shown in fig. 7-10, in the above steps, in the data interaction process, the adopted blockchain information management platform is a hyper-hedger Fabric-based modular blockchain solution support platform, the blockchain information management platform includes a blockchain network, a blockchain node and a node server, when data is shared, an RS485 communication module or an RS232 communication module is adopted for data transmission, which needs to be set according to the situation of a user node, and the wireless communication module adopted for data transmission includes a TCP/IP network system, a ZigBee wireless network, a GPRS communication module, a CDMA wireless communication module, a cloud communication module or a bluetooth communication module; the various communication modules are within the range of the blockchain network. The block chain communication efficiency can be improved.
Because the data transmission process is easy to be interfered by the outside, the data encryption unit is arranged in the data interaction process, the data encryption unit can also comprise a DES encryption unit, a 3DES encryption unit, a Blowfish encryption unit, a Twofish encryption unit, an IDEA encryption unit, an RC6 encryption unit, a character string encryption unit or a CAST5 encryption unit and the like, and the confidentiality degree in the bid and tender data interaction process is improved through data encryption. In the interaction process, besides the node equipment, a plurality of communication protocols interacting with the data chain nodes are also arranged, and the communication protocols at least comprise TCP/IP, UDP, IPSec, MODBUS/TCP, OPC, proprietary protocols, PROFIBUS-DP, MPI, PPI, S7, FX series programming port and serial port protocols, Q series serial port 4C protocols, Ethernet 3E protocols, CC-LINK, A series or ohm dragon HostLink protocols [14-15], so that the communication requirements of different monitoring equipment interfaces or communication equipment are met, and the data interaction capacity is improved.
A computer data information processing system based on a blockchain network, comprising:
a network data transmitting terminal; the system comprises a network data sending terminal, a network data sending terminal and a network data sending terminal, wherein the network data sending terminal is used for sending network data information and outputting and transmitting the network data information to next application equipment;
a communication controller; in the internet data communication system, between data circuit and host computer, the communication interface equipment used for controlling data transmission;
a block chain network module; the node equipment is connected through block chain link points connected in a chain manner, and are connected and communicated with each other through a block chain network, the block chain network module is sequentially provided with a data layer, a network layer, a consensus layer, an excitation layer and an intelligent contract layer from bottom to top, and the block chain network module is a master-slave block chain structure model; and a data application terminal; the data application terminal is provided with an improved C4.5 decision tree model, and the improved C4.5 decision tree model is provided with a blockchain network node;
the output end of the network data sending terminal is connected with the input end of the communication controller, the output end of the communication controller is connected with the input end of the block chain network module, and the output end of the block chain network module is connected with the input end of the data application terminal.
In particular embodiments, the communication controller manages data input and output to a host or computer network. It can be a complex foreground mainframe computer interface or simple devices such as multiplexers, bridges and routers. These devices convert the parallel data of the computer into serial data for transmission over the communication lines and perform all necessary control functions, error detection and synchronization. Modern devices also perform data compression, routing, security functions, and collect management information. The main functions of the communication controller are: providing an electrical interface with a data circuit and with a host; assembling the serial bit stream on the data circuit into characters according to the serial-parallel conversion principle, or inversely disassembling the characters into the serial bit stream; the data transmission rate on the circuit is converted from the host transmission rate; the transformation of the transmission code and the internal code of the host; executing transmission control procedure, such as data communication basic control procedure, high-level data link control procedure, etc.; detection and correction of transmission errors, such as vertical horizontal parity, cyclic code checking, etc.
In the above embodiments, the blockchain is referred to as a multi-party co-maintained, decentralized, traceable, and non-falsifiable distributed database, and is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, and an encryption algorithm. Request data in a certain period can be packed into a data block (block) through a cryptographic technology, and the data block is connected into a chain structure for storage according to time sequence by using a Hash fingerprint. A data block is typically composed of two parts, a block header and a block body. The block header usually stores data such as the version number of the system, the hash value of the previous block, the merkle root, and the timestamp, and the block body contains detailed request data. Taking a bitcoin as an example, the block head of the bitcoin also stores data such as random numbers for mining and the like in addition to the above information, and the block body stores specific transaction data.
As shown in fig. 9, the blockchain platform is a hyper-leader Fabric-based modular blockchain solution support platform. The Fabric platform is a union chain architecture, supports an intelligent contract technology, does not depend on tokens in system operation, can support about hundred per second transaction throughput, and basically meets the requirement of cross-institution transaction of Internet data information between union institutions. In addition, Fabric adopts a modular architecture, wherein a consensus algorithm and the like can be used as a pluggable module for internet users to choose. Meanwhile, the method can enable the Internet user to redesign and develop the specific module according to the self requirement, so that the Fabric is selected as a block chain foundation platform of the Internet data information transaction system. The Fabric mainly comprises member service modules (Membership Services), block chain service modules (Blockchain Services) and chain code service modules (Chaincode Services). The member service module mainly provides functions of member registration, identity management, transaction examination and the like, and performs mechanism registration authentication and transaction authentication through a registration certificate issuing mechanism (ECA) and a transaction authentication center (TCA). The block chain service module is mainly responsible for point-to-point communication between nodes, consensus, and the storage of account book data. The chain code service module provides intelligent contract service, provides a safe contract running environment and the like. Meanwhile, the platform realizes asynchronous communication through an Event Stream (Event Stream) between all the components.
As shown in fig. 10, the block link points are connected in a chain manner, that is, the block link points are connected and communicated with each other through a block chain network, and the nodes are connected in a chain manner, so that information interaction between different nodes can be realized. When data sharing is carried out, the alternation and sharing of the internet data are realized through different data nodes.
The data layer utilizes a Merkle tree for data storage, and is structurally connected in a chain manner through blocks. The data structure utilizes digital signature, hash function and asymmetric encryption technology, so that the data interaction has high security performance. The network layer is mainly formed by interweaving a plurality of network nodes, and data communication and connection are realized by using a point-to-point technology through different network nodes, so that the technical weakness that a central server is used in the traditional technology is eliminated, and node equipment in the network can be intercommunicated and interconnected. In a consensus layer in the network, the existence of a consensus mechanism can carry out consistency interaction on data set in the block chain network, and the block chain network has better data consensus capability and data anti-attack capability. The excitation layer can provide excitation measures in the block chain, so that the action of the network node is sufficiently excited in the block chain, and the security verification can be carried out. In the intelligent contract layer, various program algorithms are fully utilized to execute and calculate the relationship between various data in the block chain network.
The master-slave blockchain structure model is provided with blockchain network nodes connected in a closed loop and blockchain devices connected with the blockchain network nodes.
The master-slave block chain structure model can summarize the relation of each industry of the internet service, match the service mode with the industry, simplify the service process, improve the service quality, enable the internet user to obtain the applied service process in the internet service system, enable the internet user to enjoy the flow service system in the service system, make the service mode more systematic and have better experience, and the master-slave block chain structure model is as shown in figure 3
The master-slave block chain structure model mainly forms a service special matching mode, and a circulation system is established through a block chain network to complete service circulation of internet users, internet user demand terminals, electricity selling companies and a power grid. The method comprises the following steps that an internet user side carries out demand butt joint aiming at a microgrid, industry, residents and business respectively, and internet user demand data are transferred to a block chain internet user network; the method comprises the steps that an internet user demand end mainly analyzes the whole internet, network data types, network data IDs, network data safety data information and network data application information in the whole internet are integrated into a block chain network in the network transmission process through internet user demand data, and therefore equipment maintenance, distributed network data analysis, energy-saving design, data transaction, service agency, energy efficiency detection and other data information services are achieved, and network application special application is conducted on internet users who put forward demands; the main service modes are equipment maintenance, energy efficiency detection, service agency, data transaction, energy-saving design and distributed matching mode. The service mode of the master-slave block chain has an important effect on improving the service evaluation of the whole internet, so that a service system can be specially applied according to the requirements of internet users, the matching time is shortened to the maximum degree, meanwhile, a circulating service system has an important effect on enhancing the internet application, the served internet is stored to the maximum degree in the process, the requirements of the internet users are met, and the circulating application of the internet is guaranteed.
Although specific embodiments of the present invention have been described above, it will be understood by those skilled in the art that these specific embodiments are merely illustrative and that various omissions, substitutions and changes in the form of the detail of the methods and systems described above may be made by those skilled in the art without departing from the spirit and scope of the invention. For example, it is within the scope of the present invention to combine the steps of the above-described methods to perform substantially the same function in substantially the same way to achieve substantially the same result. Accordingly, the scope of the invention is to be limited only by the following claims.
Claims (5)
1. A computer data information processing method based on a block chain network is characterized in that: the method comprises the following steps:
(S1) issuing the network data information, outputting and transferring the network data information to the next application device;
in the step, when the network data information is sent out, the network data information is marked with data information compatible with the block chain network, and the tracking in the network data information transmission process is realized by marking a timestamp or a network data information identifier on the data information;
(S2) controlling data transmission through the network data interactive communication interface in the internet data communication system;
in the step, network data information transmission is realized by controlling the network data information nodes during data transmission control, and network data information node information interaction is synchronously realized in the data transmission control process;
(S3) connecting the node devices through the block chain nodes connected in a chain manner, and communicating with each other through a block chain network, so that the sent network data information is interacted and transmitted through the block chain network;
in the step, the encryption of the data information of the block link point is realized through a symmetric encryption algorithm; the decryption of the data information of the block chain link point is realized by a symmetrical decryption method, and further the primary encryption of the data information of the block chain link point is realized;
encrypting data information through a public key of a receiver, then generating a data ciphertext, when receiving data, firstly calculating an abstract of transmitted data by using a hash function in a block chain, and then digitally signing the abstract through a private key; the data sender simultaneously sends a data ciphertext and a signature, and the receiver decrypts the data through a public key so as to realize encryption and decryption calculation of internet data information;
in the step, the second-level encryption of the data information of the block link point is realized through an elliptic curve equation;
(S4) receiving, by the blockchain network node, data information sent by the network data sending terminal, for implementing calculation of the network data information;
in the step, the processing of the network data information is realized through an improved C4.5 decision tree algorithm model, wherein the improved C4.5 decision tree algorithm model comprises a drosophila optimization algorithm model, so that the classification capability of the network data information is improved;
(S5) outputting the calculated network data information to meet the user' S demand.
2. The method for processing computer data information based on blockchain network according to claim 1, wherein: the improved C4.5 decision tree algorithm model is carried out by the following steps:
(1) extracting data information from network data nodes, the network data information set being recorded asDividing network data information intoA classification module, thenIs provided withAn attribute tag, defineFor each of the set of attribute tags,(ii) a Suppose thatIs of the classThe expected values required for a fixed sample classification for the network data samples in (1) are:
(2) constructing a drosophila optimization algorithm model, realizing global optimization retrieval to improve the network data classification retrieval capability,
(3) and (3) carrying out data classification on the network data information set S through the network data nodes retrieved by the drosophila optimization algorithm model, and recording classified subset information as:
(4) calculating information gain for the retrieved network data node data information, and subtracting the currently received data information from the input data node data information, then:
(5) the information gain ratio of the attribute a is calculated by calculating the information gain for the retrieved network data node data information, and is referred to as:
the data information of the network data node is classified as:
3. The method for processing computer data information based on blockchain network according to claim 2, wherein: the construction method of the drosophila optimization algorithm model comprises the following steps:
(A) randomly initializing the fruit fly group position, namely the position of network node data information in the Internet; the positions are defined as follows:
(B) giving the fruit fly individual a random direction and distance for searching network node data information by using smell;
(C) since the position of the network node data information can not be obtained, the estimation is carried out firstlyDistance from the data information source point of the network nodeThen, the taste concentration judgment value is calculatedThe value is the inverse of the distance,
(D) taste concentration determination valueSubstituting into taste concentration determination function to obtain taste concentration of individual fruit fly position;
(E) Finding out the fruit flies with the highest taste concentration in the fruit fly population;
(F) keeping the optimal taste concentration value and the x, y coordinates, and enabling the fruit fly colony to fly to the position by using vision;
(G) and (4) entering iterative optimization, repeatedly executing the steps B-E, judging whether the taste concentration is superior to the previous taste concentration, and executing the step F if the taste concentration is superior to the previous taste concentration.
4. The method for processing computer data information based on blockchain network according to claim 3, wherein: the drosophila optimization algorithm model realizes network data information definition recognition by constructing a logical chaotic mapping theoretical model, wherein the logical chaotic mapping theoretical model is as follows:
n represents the iteration times of the drosophila model for network data node information retrieval in the continuous calculation process, and u is a chaotic control network data node information parameter;
network data node information chaos variable C xi The formula of (1) is:
wherein x (n) i Is the ith chaotic variable C after the chaotic value is changed in the network data node information retrieval process xi (ii) a When C is present xi ∈[0,1]And C xi E {0.34, 0.52, 0.79}, improved C4.5 decision treeThe algorithm model is in a chaotic state; then iterative computation is needed again for stimulation;
in the formula (18), x i ∈[a i ,b i ]Available C xi The following modifications are made by expressions (17) and (18):
wherein x is i And the value of the ith network data node information chaotic variable is represented, and the variable is converted into a conventional variable after chaotic mapping transformation.
5. A computer data information processing system based on a blockchain network, characterized by: the method comprises the following steps:
a network data transmitting terminal; the system comprises a network data sending terminal, a network data sending terminal and a network data sending terminal, wherein the network data sending terminal is used for sending network data information and outputting and transmitting the network data information to next application equipment;
a communication controller; in the internet data communication system, between data circuit and host computer, the communication interface equipment used for controlling data transmission;
a block chain network module; the node equipment is connected through block chain link points connected in a chain manner, and are connected and communicated with each other through a block chain network, the block chain network module is sequentially provided with a data layer, a network layer, a consensus layer, an excitation layer and an intelligent contract layer from bottom to top, and the block chain network module is a master-slave block chain structure model; and
a data application terminal; the data application terminal is provided with an improved C4.5 decision tree model, and the improved C4.5 decision tree model is provided with a blockchain network node;
the output end of the network data sending terminal is connected with the input end of the communication controller, the output end of the communication controller is connected with the input end of the block chain network module, and the output end of the block chain network module is connected with the input end of the data application terminal.
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Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20170324711A1 (en) * | 2016-05-03 | 2017-11-09 | The Real Mccoy, Llc Inc. | Method for establishing, securing and transferring computer readable information using peer-to-peer public and private key cryptography |
CN109739999A (en) * | 2019-01-16 | 2019-05-10 | 福建师范大学 | A kind of efficient drosophila neural network Hash Search WMSN data method |
CN110532329A (en) * | 2019-09-02 | 2019-12-03 | 智慧谷(厦门)物联科技有限公司 | A kind of Intelligent bracelet data processing and sharing method based on block chain technology |
CN113452783A (en) * | 2021-06-28 | 2021-09-28 | 智慧谷(厦门)物联科技有限公司 | Digital PAAS open platform system of block chain cloud architecture and implementation method |
CN114025346A (en) * | 2021-10-12 | 2022-02-08 | 杭州趣链科技有限公司 | Safe and effective data transmission method for data between mobile self-set networks |
CN114666035A (en) * | 2022-05-13 | 2022-06-24 | 深圳市赢向量科技有限公司 | Block chain intelligent contract execution method based on secret communication and operation system |
-
2022
- 2022-07-25 CN CN202210880016.0A patent/CN115085941B/en active Active
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20170324711A1 (en) * | 2016-05-03 | 2017-11-09 | The Real Mccoy, Llc Inc. | Method for establishing, securing and transferring computer readable information using peer-to-peer public and private key cryptography |
CN109739999A (en) * | 2019-01-16 | 2019-05-10 | 福建师范大学 | A kind of efficient drosophila neural network Hash Search WMSN data method |
CN110532329A (en) * | 2019-09-02 | 2019-12-03 | 智慧谷(厦门)物联科技有限公司 | A kind of Intelligent bracelet data processing and sharing method based on block chain technology |
CN113452783A (en) * | 2021-06-28 | 2021-09-28 | 智慧谷(厦门)物联科技有限公司 | Digital PAAS open platform system of block chain cloud architecture and implementation method |
CN114025346A (en) * | 2021-10-12 | 2022-02-08 | 杭州趣链科技有限公司 | Safe and effective data transmission method for data between mobile self-set networks |
CN114666035A (en) * | 2022-05-13 | 2022-06-24 | 深圳市赢向量科技有限公司 | Block chain intelligent contract execution method based on secret communication and operation system |
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