CN111954209A - Information processing method and device for improving security of wireless sensor node - Google Patents
Information processing method and device for improving security of wireless sensor node Download PDFInfo
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Abstract
The invention discloses an information processing method and an information processing device for improving the security of a wireless sensor node, wherein the method comprises the following steps: acquiring first clustering instruction information; acquiring a plurality of cluster nodes according to the first cluster instruction information; classifying the cluster nodes according to the direct neighbor node quantity information of the cluster nodes to obtain first-level cluster node information, second-level cluster node information and up to N-level cluster node information; generating a first verification code according to the primary cluster node information, wherein the first verification code corresponds to the primary cluster node information one to one; by analogy, generating an Nth verification code according to the N-level cluster node information and the (N-1) th verification code, wherein N is a natural number greater than 1; and respectively copying and storing the cluster nodes and the verification codes of all levels on M devices, wherein M is a natural number greater than 1. The method solves the problems that the positioning algorithm system in the prior art is very fragile in safety and the like, and achieves the technical effect of greatly improving the stability and safety of the network node.
Description
Technical Field
The invention relates to the technical field of information processing of node security of a sensor, in particular to an information processing method and device for improving the node security of a wireless sensor.
Background
The wireless sensor network is widely applied to the fields of military, environment, industry, agricultural monitoring and the like due to the advantages of low consumption, self-assembly, good fault tolerance, easiness in large-scale deployment and the like. The method has the characteristics of limited network resources, openness deployment, unattended operation and the like, so that potential safety hazards exist in the node positioning process, and the positioning safety has important significance in the application of the wireless sensor network.
However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the inventors of the present application find that the above-mentioned technology has at least the following technical problems:
the information processing safety of the wireless sensor node is very fragile, the stability is low, and a general optimal node positioning algorithm system does not exist at present.
Disclosure of Invention
The embodiment of the application provides an information processing method and an information processing device for improving the security of a wireless sensor node, solves the problems that the security of a positioning algorithm system is very weak and the like in the prior art, and achieves the technical effect of greatly improving the stability and the security of a network node.
The embodiment of the application provides an information processing method and device for improving the safety of a wireless sensor node, wherein the method comprises the following steps: acquiring first clustering instruction information; acquiring a plurality of cluster nodes according to the first cluster instruction information; classifying the plurality of cluster nodes according to the direct neighbor node quantity information of the cluster nodes to obtain first-level cluster node information and second-level cluster node information until N-level cluster node information; generating a first verification code according to the primary cluster node information, wherein the first verification code corresponds to the primary cluster node information one to one; generating a second verification code according to the second-level cluster node information and the first verification code; by analogy, generating an Nth verification code according to the N-level cluster node information and the (N-1) th verification code, wherein N is a natural number greater than 1; and respectively copying and storing the cluster nodes and the verification codes of all levels on M devices, wherein M is a natural number greater than 1.
On the other hand, the present application further provides an information processing apparatus for improving security of a wireless sensor node, wherein the apparatus includes: a first obtaining unit configured to obtain first clustering instruction information; a second obtaining unit, configured to obtain a plurality of cluster nodes according to the first clustering instruction information; a third obtaining unit, configured to classify the plurality of cluster nodes according to information about the number of direct neighbor nodes of the cluster node, and obtain first-level cluster node information and second-level cluster node information until N-level cluster node information; a fourth obtaining unit, configured to generate a first verification code according to the primary cluster node information, where the first verification code corresponds to the primary cluster node information one to one; a fifth obtaining unit, configured to generate a second verification code according to the secondary cluster node information and the first verification code; by analogy, generating an Nth verification code according to the N-level cluster node information and the (N-1) th verification code, wherein N is a natural number greater than 1; the first storage unit is used for respectively copying and storing the cluster nodes and the verification codes of all levels on M devices, wherein M is a natural number larger than 1.
In another aspect, an information processing apparatus for improving security of a wireless sensor node is further provided, and includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the method according to any one of claims 1 to 7 when executing the program.
One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
the first verification code is generated according to the first-level cluster node information; generating a second verification code according to the second-level cluster node information and the first verification code; and in the same way, generating an Nth verification code according to the N-level cluster node information and the N-1 th verification code, wherein the N-th cluster node information corresponds to the Nth verification code one by one. The data packet has certain security strength through the generated verification code, and the confidentiality of data is improved; and copying and storing the cluster nodes and the verification codes of all levels on the M devices respectively, thereby improving the security of node information storage. Based on the block chain information processing technology, the problems that the safety of an algorithm system is very weak and the like in the prior art are solved, and the technical effect of greatly improving the stability and the safety of network nodes is achieved.
The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.
Drawings
Fig. 1 is a schematic flowchart of an information processing method for improving security of a wireless sensor node according to an embodiment of the present application;
fig. 2 is a schematic flow chart illustrating chaining of data information blocks in an information processing method for improving security of a wireless sensor node according to an embodiment of the present disclosure;
fig. 3 is a schematic flow chart illustrating clustering performed on nodes in an information processing method for improving security of wireless sensor nodes according to an embodiment of the present application;
fig. 4 is a schematic flowchart illustrating a process of copying storage cluster nodes and identification codes in an information processing method for improving security of wireless sensor nodes according to an embodiment of the present disclosure;
fig. 5 is a schematic flowchart illustrating a process of copying a storage node and an identification code in an information processing method for improving security of a wireless sensor node according to an embodiment of the present disclosure;
fig. 6 is a schematic flowchart of a process of obtaining the training model in an information processing method for improving security of a wireless sensor node according to an embodiment of the present application;
fig. 7 is a schematic flowchart illustrating a process of generating a hash value according to node information in an information processing method for improving security of a wireless sensor node according to an embodiment of the present application;
fig. 8 is a schematic structural diagram of an information processing apparatus for improving security of a wireless sensor node according to an embodiment of the present application;
fig. 9 is a schematic structural diagram of an exemplary electronic device according to an embodiment of the present application.
Description of reference numerals: a first obtaining unit 11, a second obtaining unit 12, a third obtaining unit 13, a fourth obtaining unit 14, a fifth obtaining unit 15, a first storage unit 16, a bus 300, a receiver 301, a processor 302, a transmitter 303, a memory 304, and a bus interface 306.
Detailed Description
The embodiment of the application provides an information processing method and an information processing device for improving the security of a wireless sensor node, solves the problems that the security of a positioning algorithm system is very weak and the like in the prior art, and achieves the technical effect of greatly improving the stability and the security of a network node. Hereinafter, example embodiments of the present application will be described in detail with reference to the accompanying drawings. It should be apparent that the described embodiments are merely some embodiments of the present application and not all embodiments of the present application, and it should be understood that the present application is not limited to the example embodiments described herein.
Summary of the application
The wireless sensor network is widely applied to the fields of military, environment, industry, agricultural monitoring and the like due to the advantages of low consumption, self-assembly, good fault tolerance, easiness in large-scale deployment and the like. The method has the characteristics of limited network resources, openness deployment, unattended operation and the like, so that potential safety hazards exist in the node positioning process, and the positioning safety has important significance in the application of the wireless sensor network. However, the prior art also has the problems that the safety of a positioning algorithm system is very weak, and a general optimal positioning algorithm system does not exist at present.
In view of the above technical problems, the technical solution provided by the present application has the following general idea:
the embodiment of the application provides an information processing method and device for improving the safety of a wireless sensor node, wherein the method comprises the following steps: acquiring first clustering instruction information; acquiring a plurality of cluster nodes according to the first cluster instruction information; classifying the plurality of cluster nodes according to the direct neighbor node quantity information of the cluster nodes to obtain first-level cluster node information and second-level cluster node information until N-level cluster node information; generating a first verification code according to the primary cluster node information, wherein the first verification code corresponds to the primary cluster node information one to one; generating a second verification code according to the second-level cluster node information and the first verification code; by analogy, generating an Nth verification code according to the N-level cluster node information and the (N-1) th verification code, wherein N is a natural number greater than 1; and respectively copying and storing the cluster nodes and the verification codes of all levels on M devices, wherein M is a natural number greater than 1.
Having thus described the general principles of the present application, various non-limiting embodiments thereof will now be described in detail with reference to the accompanying drawings.
Example one
As shown in fig. 1, an embodiment of the present application provides an information processing method and an information processing apparatus for improving security of a wireless sensor node, where the method includes:
step S100: acquiring first clustering instruction information;
specifically, the clustering instruction information is information for guiding each node to generate each cluster, the wireless sensor is composed of a large number of micro sensing nodes deployed in a monitoring area, and the storage, calculation and communication capacities of the nodes are very limited, so that the wireless sensor network is required to be designed with the primary purpose of energy conservation, the load capacity of each node is balanced, and the survival time of the network is prolonged to the maximum extent. And the form of clustering is adopted, so that the energy consumption of the sensor network is uniformly distributed to each node, and the stability of the sensor network is improved.
Step S200: acquiring a plurality of cluster nodes according to the first cluster instruction information;
specifically, a plurality of cluster nodes are obtained from the first clustering instruction information, and the cluster nodes are node information respectively representing one of states of a gateway, a cluster head and cluster members after the cluster is established. Through the establishment of cluster nodes, the sensor network transmits the acquired data to the cluster head in a mode of minimum energy consumption, and the cluster head transmits the mobile phone information to the base station along the optimal path. The life cycle of the sensor network is prolonged, and the stability and the safety of the wireless sensor are improved.
Step S300: classifying the plurality of cluster nodes according to the direct neighbor node quantity information of the cluster nodes to obtain first-level cluster node information and second-level cluster node information until N-level cluster node information;
specifically, each cluster node sends information to surrounding neighbor nodes, and the feedback information obtains the number information of the direct neighbor nodes of the cluster node, where the number of nodes included in the cluster node information of each level is within the same number level, for example, 50 to 60 is a level 60 to 70 is a level; by defining and acquiring the neighbor relation between the nodes, a good network foundation is established for the sensor, the performance of the sensor network is enhanced, and the technical purpose of improving the stability of the sensor is achieved.
Step S400: generating a first verification code according to the primary cluster node information, wherein the first verification code corresponds to the primary cluster node information one to one;
specifically, the first verification code is generated by the primary node information, and the first verification code corresponds to the primary cluster node information one to one; the verification code information is used as main body identification information, the identification information of the main body is used for distinguishing from other main bodies, when the node information data needs to be called, after each latter node receives the data stored by the former node, the data is verified and stored through a common identification mechanism, and each storage unit is connected in series through a Hash technology, so that the node data is not easy to lose and damage, and the technical effect of improving the safety of the wireless sensor network is achieved.
Step S500: generating a second verification code according to the second-level cluster node information and the first verification code; by analogy, generating an Nth verification code according to the N-level cluster node information and the (N-1) th verification code, wherein N is a natural number greater than 1;
specifically, the second verification code is generated by the secondary cluster node information and the first verification code, and the second verification code corresponds to the secondary cluster node information one to one; the Nth verification code is identification information of the N-level cluster node, and data information is enabled to have non-tamper property through an information processing technology based on a block chain, so that the technical purpose of enhancing the security of the sensor network is achieved.
Step S600: and respectively copying and storing the cluster nodes and the verification codes of all levels on M devices, wherein M is a natural number greater than 1.
Specifically, when the training data needs to be called, after each next node receives the data stored by the previous node, the data is verified through a common identification mechanism and then stored, and each storage device is connected in series through a hash technology, so that the training data is not easy to lose and damage, and through a data information processing technology based on a block chain, the safety of data information is improved, and the technical purpose of improving the safety of a sensor is achieved.
As shown in fig. 2, in order to chain the data information blocks, step S500 in this embodiment further includes:
step S501: taking the N-level cluster node information and an N-1 verification code as an Nth block;
step S502: obtaining the recording time of the Nth block, wherein the recording time of the Nth block represents the time required to be recorded by the Nth block;
step S503: obtaining the first equipment with the fastest transport capacity in the M pieces of equipment according to the recording time of the Nth block;
step S504: and sending the recording right of the Nth block to the first equipment.
Specifically, the nth level cluster node information and the nth-1 verification code are partitioned to generate a plurality of blocks, and the mth device node is added to the block chain after identifying the blocks. And the Nth block recording time is the time used for the equipment node to verify through a 'consensus mechanism' based on the obtained Nth verification code information and the Nth-level cluster node information, and to store and add the verification information into the original block after the verification is passed. The shorter the recording time of the Nth block is, the fastest the transport capacity of the Mth equipment node is. The equipment with the fastest transport capacity is selected as the block recording equipment, so that the real-time performance of data interaction under the chain in the block chain is improved, the safe, effective and stable operation of a decentralized block chain system is ensured, and the efficiency of block chain message processing is improved. The stability and the safety of the wireless sensor information processing are promoted.
As shown in fig. 3, in order to cluster the nodes, step S300 in this embodiment of the present application further includes:
step S301: acquiring attribute information of a wireless sensor node;
step S302: acquiring direct neighbor quantity information of the wireless sensor node;
step S303: inputting attribute information of the node and direct neighbor quantity information of the node as input information into a first training model, wherein the first training model is obtained by training a plurality of groups of training data, and each group of training data in the plurality of groups comprises: attribute information of the node, direct neighbor quantity information of the node and identification information for identifying a node clustering level;
step S304: obtaining first output information of the first training model, wherein the first output information comprises clustering grade information of the wireless sensor nodes;
step S305: obtaining a predetermined clustering level threshold:
step S306: judging whether the clustering level information of the nodes reaches the preset clustering level threshold value or not;
step S307: if the clustering level information of the node reaches the preset clustering level threshold, obtaining first clustering instruction information, wherein the first clustering instruction information is used for clustering the node;
step S308: and if the clustering level information of the node does not reach the preset clustering level threshold value, obtaining second clustering instruction information, wherein the second clustering instruction information is used for not clustering the node.
Specifically, attribute information of each node of the wireless sensor is obtained from the output end of the sensor, and direct neighbor quantity information of the wireless sensor node is obtained through data information feedback among the nodes; and inputting the attribute information of the node and the direct neighbor quantity information of the node as input information into a first training model, wherein the training model is obtained by training a plurality of groups of training data, and the process of training the neural network model by the training data is essentially a process of supervised learning. Each set of training data in the plurality of sets of training data comprises: attribute information of the node, direct neighbor quantity information of the node and identification information for identifying a node clustering level; the machine learning model is continuously corrected and optimized through training data, and the accuracy of the machine learning model for processing the data is improved through the process of supervised learning, so that more accurate node clustering grade information is obtained. The clustering grade threshold value is grading index information divided by the number of direct neighbor nodes; and determining the first clustering instruction information and the second clustering instruction information through judgment, thereby further determining whether to cluster the nodes.
As shown in fig. 4, in order to copy, store the node and the identification code, step S304 of this embodiment further includes:
step S3041: obtaining cluster node information of the same level;
step S3042: acquiring a first cluster node, and generating a first identification code according to the first cluster node information, wherein the first identification code is in one-to-one correspondence with the first cluster node information;
step S3043: generating a second identification code according to the second cluster node information and the first identification code; by analogy, a Q & ltth & gt identification code is generated according to the Q & ltth & gt cluster node information and the Q & ltth & gt-1 & lt/th & gt identification code, wherein Q is a natural number greater than 1, and the first cluster node, the second cluster node and the Q & ltth & gt cluster node belong to the same level of cluster node information;
step S3044: and respectively copying and storing all cluster nodes and identification codes on P equipment, wherein P is a natural number greater than 1.
Specifically, the information of the cluster nodes at the same level is obtained from the first output information of the first training model, and the first cluster node is a cluster node at the same level; generating a first identification code according to the first cluster node information, and generating a Q & ltth & gt identification code according to the Q & ltth & gt cluster node information and the Q & ltth & gt-1 & gt identification code by analogy; the Q-th identification code corresponds to Q-th cluster node information one to one, the Q-th verification code is identification information of the Q-th cluster node information, and data information is enabled to be non-tamper-resistant through an information processing technology based on a block chain, so that the technical purpose of enhancing the safety of the sensor node is achieved.
As shown in fig. 5, in order to copy and store the node and the identification code, step S3041 of the present embodiment further includes:
step S30411: according to the first cluster node information, a first node, a second node and a node Y in the first cluster node information are obtained;
step S30412: generating a first identification code according to the first node information, wherein the first identification code is in one-to-one correspondence with the first node information;
step S30413: generating a second identification code according to the second node information and the first identification code; by analogy, generating a Y-th identification code according to the Y-th node information and the Y-1-th identification code, wherein Y is a natural number greater than 1;
step S30414: and respectively copying and storing all the nodes and the identification codes on X equipment, wherein X is a natural number greater than 1.
Specifically, the node Y is a certain node in the node Q, a first identification code is generated according to the first node information, and by analogy, a node Y is generated according to the node Y information and a node Y-1 identification code, wherein the verification code Y corresponds to the node Y information one by one; the Yth verification code is identification information of the Yth node, and data information is enabled to have non-tamper property through an information processing technology based on a block chain, so that the technical purpose of enhancing the security of the wireless sensor node is achieved.
As shown in fig. 6, in order to obtain the supervision data, step S303 in the embodiment of the present application further includes:
step S3031: acquiring first supervision data, wherein the first supervision data is identification information for identifying a node clustering level and is supervision data when attribute information of the node and direct neighbor quantity information of the node are input;
step S3032: and performing supervised learning on the process of inputting the attribute information of the node and the direct neighbor quantity information of the node into the training model by using the first supervision data, so that the output information of the training model reaches a convergence state.
Specifically, the machine model is obtained by training a plurality of sets of training data, and the process of training the neural network model by the training data is essentially a process of supervised learning. The plurality of groups of training data are specifically: attribute information of the node, direct neighbor quantity information of the node and identification information for identifying a node clustering level; the greater the number of direct neighbors of the node, the higher the node clustering level. Verifying the level information of the node clusters output by the machine learning model through the identified node cluster level information, and if the output node cluster level information is consistent with the identified node cluster level information, finishing the supervised learning of the data, and then performing the supervised learning of the next group of data; and if the output node clustering level information is inconsistent with the identified node clustering level information, adjusting the machine learning model by the machine learning model, and performing supervised learning of the next group of data until the machine learning model reaches the expected accuracy. The machine learning model is continuously corrected and optimized through the training data, and the accuracy of the obtained data is improved.
As shown in fig. 7, in order to further improve the security of the data, step S30411 of the present embodiment further includes:
step S304111: generating a first hash value according to the first node information, wherein the first hash value is in one-to-one correspondence with the first node information;
step S304112: generating a second hash value according to the first cluster node information and the first hash value;
step S304113: generating a third hash value according to the first-level cluster node information and the second hash value;
step S304114: and respectively copying and storing the first node, the first cluster node, the first-level cluster node and the hash value on three devices.
Specifically, the first hash value is obtained by hashing the first node information; the second hash value is obtained by hashing the first cluster node information; the third hash value is obtained by hashing the first-level cluster node information; in the hash function, any small change of the original information will hash completely different hash values, so the first, second and third hash values correspond to the original information one by one and are different from each other; when related data needs to be called, after each next node receives data stored by the previous node, the data is verified through a 'consensus mechanism' and then stored, and each storage unit is connected in series through a Hash technology, so that the training data is not easy to lose and damage, and the safety of the wireless sensor node is improved.
To sum up, the information processing method for improving the security of the wireless sensor node provided by the embodiment of the present application has the following technical effects:
1. due to the fact that the mode that the attribute information of the nodes and the direct neighbor quantity information of the nodes are used as input information and input into the training model, and then the training model outputs the clustering grade information of the wireless sensor nodes is adopted, the clustering grade information of the wireless sensor nodes can be obtained more accurately based on the characteristic that the training model can continuously optimize learning and obtain experience to process data more accurately, and the technical purpose of improving the information safety of the wireless sensor nodes is achieved.
2. Due to the adoption of the data information storage method based on the block chain, the data information of each node is stored in blocks, the data storage with large data volume can be met, the reliability of the data storage is improved, the risk that the potential data is integrally damaged in the integral storage mode is avoided, and due to the anti-tampering characteristic of the block chain, any party cannot privately tamper the stored data in the block chain, so that the safety and the stability of the node information of the wireless sensor are effectively improved.
Example two
Based on the same inventive concept as the information processing method for improving the security of the wireless sensor node in the foregoing embodiment, the present invention further provides an information processing apparatus for improving the security of the wireless sensor node, as shown in fig. 8, the apparatus includes:
a first obtaining unit 11, where the first obtaining unit 11 is configured to obtain first clustering instruction information;
a second obtaining unit 12, where the second obtaining unit 12 is configured to obtain a plurality of cluster nodes according to the first cluster instruction information;
a third obtaining unit 13, where the third obtaining unit 13 is configured to classify the plurality of cluster nodes according to information about the number of direct neighbor nodes of the cluster node, and obtain first-level cluster node information and second-level cluster node information until N-level cluster node information;
a fourth obtaining unit 14, where the fourth obtaining unit 14 is configured to generate a first verification code according to the primary cluster node information, where the first verification code corresponds to the primary cluster node information one to one;
a fifth obtaining unit 15, where the fifth obtaining unit 15 is configured to generate a second verification code according to the secondary cluster node information and the first verification code; by analogy, generating an Nth verification code according to the N-level cluster node information and the (N-1) th verification code, wherein N is a natural number greater than 1;
a first storage unit 16, where the first storage unit 16 is configured to respectively store cluster nodes and verification codes of all levels in duplicate on M devices, where M is a natural number greater than 1.
Further, the apparatus further comprises:
a sixth obtaining unit, configured to use the N-level cluster node information and an N-1 th authentication code as an nth block; obtaining the recording time of the Nth block, wherein the recording time of the Nth block represents the time required to be recorded by the Nth block;
a seventh obtaining unit, configured to obtain, according to the nth block recording time, a first device with the fastest transport capacity from among the M devices;
a first sending unit, configured to send the recording right of the nth block to the first device.
Further, the apparatus further comprises:
an eighth obtaining unit, configured to obtain attribute information of the wireless sensor node;
a ninth obtaining unit, configured to obtain direct neighbor number information of the wireless sensor node;
a first input unit, configured to input attribute information of the node and direct neighbor quantity information of the node as input information into a first training model, where the first training model is obtained by training multiple sets of training data, and each set of training data in the multiple sets includes: attribute information of the node, direct neighbor quantity information of the node and identification information for identifying a node clustering level;
a tenth obtaining unit, configured to obtain first output information of the first training model, where the first output information includes clustering level information of the wireless sensor node;
an eleventh obtaining unit configured to obtain a predetermined clustering level threshold:
a first judging unit, configured to judge whether cluster level information of the node reaches the predetermined cluster level threshold;
a twelfth obtaining unit, configured to obtain first clustering instruction information if the clustering level information of the node reaches the predetermined clustering level threshold, where the first clustering instruction information is used to cluster the node;
a thirteenth obtaining unit, configured to obtain second clustering instruction information if the clustering level information of the node does not reach the predetermined clustering level threshold, where the second clustering instruction information is used to not cluster the node.
Further, the apparatus further comprises:
a fourteenth obtaining unit, configured to obtain cluster node information of the same level;
a fifteenth obtaining unit, configured to obtain a first cluster node, and generate a first identifier code according to the first cluster node information, where the first identifier code is in one-to-one correspondence with the first cluster node information; generating a second identification code according to the second cluster node information and the first identification code; by analogy, a Q & ltth & gt identification code is generated according to the Q & ltth & gt cluster node information and the Q & ltth & gt-1 & lt/th & gt identification code, wherein Q is a natural number greater than 1, and the first cluster node, the second cluster node and the Q & ltth & gt cluster node belong to the same level of cluster node information;
and the second storage unit is used for respectively copying and storing all cluster nodes and identification codes on P equipment, wherein P is a natural number greater than 1.
Further, the apparatus further comprises:
a sixteenth obtaining unit, configured to obtain, according to the first cluster node information, a first node, a second node, and a node up to a Y-th node in the first cluster node information;
a seventeenth obtaining unit, configured to generate a first identifier code according to the first node information, where the first identifier code corresponds to the first node information one to one; generating a second identification code according to the second node information and the first identification code; by analogy, generating a Y-th identification code according to the Y-th node information and the Y-1-th identification code, wherein Y is a natural number greater than 1;
and the third storage unit is used for respectively copying and storing all the nodes and the identification codes on X equipment, wherein X is a natural number greater than 1.
Further, the apparatus further comprises:
an eighteenth obtaining unit, configured to obtain first supervision data, where the first supervision data is the identification information used to identify a node clustering level, and is supervision data when attribute information of the node and direct neighbor number information of the node are input;
the first supervision unit is used for carrying out supervised learning on the process of inputting the attribute information of the node and the direct neighbor quantity information of the node into the training model by using the first supervision data so as to enable the output information of the training model to reach a convergence state.
Further, the apparatus further comprises:
a nineteenth obtaining unit, configured to generate a first hash value according to the first node information, where the first hash value is in one-to-one correspondence with the first node information;
a twentieth obtaining unit, configured to generate a second hash value according to the first cluster node information and the first hash value;
a twenty-first obtaining unit, configured to generate a third hash value according to the first-level cluster node information and the second hash value;
and the fourth storage unit is used for respectively copying and storing the first node, the first cluster node, the first-level cluster node and the hash value on three pieces of equipment.
Various changes and specific examples of the information processing method for improving the security of the wireless sensor node in the first embodiment of fig. 1 are also applicable to the information processing apparatus for improving the security of the wireless sensor node in the present embodiment, and through the foregoing detailed description of the information processing method for improving the security of the wireless sensor node, those skilled in the art can clearly know that an implementation method of the information processing apparatus for improving the security of the wireless sensor node in the present embodiment is not described in detail here for the sake of brevity of the description.
Exemplary electronic device
The electronic apparatus of the embodiment of the present application is described below with reference to fig. 9.
Fig. 9 illustrates a schematic structural diagram of an electronic device according to an embodiment of the present application.
Based on the inventive concept of the information processing method for improving the security of the wireless sensor node in the foregoing embodiments, the present invention further provides an information processing apparatus for improving the security of the wireless sensor node, wherein the information processing apparatus has a computer program stored thereon, and the computer program, when executed by a processor, implements the steps of any one of the foregoing information processing methods for improving the security of the wireless sensor node.
Where in fig. 9 a bus architecture (represented by bus 300), bus 300 may include any number of interconnected buses and bridges, bus 300 linking together various circuits including one or more processors, represented by processor 302, and memory, represented by memory 304. The bus 300 may also link together various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface 306 provides an interface between the bus 300 and the receiver 301 and transmitter 303. The receiver 301 and the transmitter 303 may be the same element, i.e., a transceiver, providing a means for communicating with various other apparatus over a transmission medium.
The processor 302 is responsible for managing the bus 300 and general processing, and the memory 304 may be used for storing data used by the processor 302 in performing operations.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (devices), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (9)
1. An information processing method for improving the security of a wireless sensor node, wherein the method comprises the following steps:
acquiring first clustering instruction information;
acquiring a plurality of cluster nodes according to the first cluster instruction information;
classifying the plurality of cluster nodes according to the direct neighbor node quantity information of the cluster nodes to obtain first-level cluster node information and second-level cluster node information until N-level cluster node information;
generating a first verification code according to the primary cluster node information, wherein the first verification code corresponds to the primary cluster node information one to one;
generating a second verification code according to the second-level cluster node information and the first verification code; by analogy, generating an Nth verification code according to the N-level cluster node information and the (N-1) th verification code, wherein N is a natural number greater than 1;
and respectively copying and storing the cluster nodes and the verification codes of all levels on M devices, wherein M is a natural number greater than 1.
2. The method of claim 1, wherein the method comprises:
taking the N-level cluster node information and an N-1 verification code as an Nth block;
obtaining the recording time of the Nth block, wherein the recording time of the Nth block represents the time required to be recorded by the Nth block;
obtaining the first equipment with the fastest transport capacity in the M pieces of equipment according to the recording time of the Nth block;
and sending the recording right of the Nth block to the first equipment.
3. The method of claim 1, wherein the method comprises:
acquiring attribute information of a wireless sensor node;
acquiring direct neighbor quantity information of the wireless sensor node;
inputting attribute information of the node and direct neighbor quantity information of the node as input information into a first training model, wherein the first training model is obtained by training a plurality of groups of training data, and each group of training data in the plurality of groups comprises: attribute information of the node, direct neighbor quantity information of the node and identification information for identifying a node clustering level;
obtaining first output information of the first training model, wherein the first output information comprises clustering grade information of the wireless sensor nodes;
obtaining a predetermined clustering level threshold:
judging whether the clustering level information of the nodes reaches the preset clustering level threshold value or not;
if the clustering level information of the node reaches the preset clustering level threshold, obtaining first clustering instruction information, wherein the first clustering instruction information is used for clustering the node;
and if the clustering level information of the node does not reach the preset clustering level threshold value, obtaining second clustering instruction information, wherein the second clustering instruction information is used for not clustering the node.
4. The method of claim 1, wherein the method comprises:
obtaining cluster node information of the same level;
acquiring a first cluster node, and generating a first identification code according to the first cluster node information, wherein the first identification code is in one-to-one correspondence with the first cluster node information;
generating a second identification code according to the second cluster node information and the first identification code; by analogy, a Q & ltth & gt identification code is generated according to Q & ltth & gt cluster node information and a Q & ltth & gt-1 & lt/th & gt identification code, wherein Q is a natural number greater than 1, and the first cluster node, the second cluster node and the Q & ltth & gt cluster node belong to cluster node information of the same level;
and respectively copying and storing all cluster nodes and identification codes on P equipment, wherein P is a natural number greater than 1.
5. The method of claim 4, wherein the method comprises:
according to the first cluster node information, a first node, a second node and a node Y in the first cluster node information are obtained;
generating a first identification code according to the first node information, wherein the first identification code is in one-to-one correspondence with the first node information;
generating a second identification code according to the second node information and the first identification code; by analogy, generating a Y-th identification code according to the Y-th node information and the Y-1-th identification code, wherein Y is a natural number greater than 1;
and respectively copying and storing all the nodes and the identification codes on X equipment, wherein X is a natural number greater than 1.
6. The method of claim 3, wherein the method comprises:
acquiring first supervision data, wherein the first supervision data is identification information for identifying a node clustering level and is supervision data when attribute information of the node and direct neighbor quantity information of the node are input;
and performing supervised learning on the process of inputting the attribute information of the node and the direct neighbor quantity information of the node into the training model by using the first supervision data, so that the output information of the training model reaches a convergence state.
7. The method of claim 5, wherein the method comprises:
generating a first hash value according to the first node information, wherein the first hash value is in one-to-one correspondence with the first node information;
generating a second hash value according to the first cluster node information and the first hash value;
generating a third hash value according to the first-level cluster node information and the second hash value;
and respectively copying and storing the first node, the first cluster node, the first-level cluster node and the hash value on three devices.
8. An information processing apparatus for improving security of a wireless sensor node, wherein the apparatus comprises:
a first obtaining unit configured to obtain first clustering instruction information;
a second obtaining unit, configured to obtain a plurality of cluster nodes according to the first clustering instruction information;
a third obtaining unit, configured to classify the plurality of cluster nodes according to information about the number of direct neighbor nodes of the cluster node, and obtain first-level cluster node information and second-level cluster node information until N-level cluster node information;
a fourth obtaining unit, configured to generate a first verification code according to the primary cluster node information, where the first verification code corresponds to the primary cluster node information one to one;
a fifth obtaining unit, configured to generate a second verification code according to the secondary cluster node information and the first verification code; by analogy, generating an Nth verification code according to the N-level cluster node information and the (N-1) th verification code, wherein N is a natural number greater than 1;
the first storage unit is used for respectively copying and storing the cluster nodes and the verification codes of all levels on M devices, wherein M is a natural number larger than 1.
9. An information processing apparatus for improving security of a wireless sensor node, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method of any one of claims 1 to 7 when executing the program.
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| CN202010808895.7A CN111954209A (en) | 2020-08-12 | 2020-08-12 | Information processing method and device for improving security of wireless sensor node |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112433139A (en) * | 2020-12-18 | 2021-03-02 | 安徽诚越电子科技有限公司 | Method and device for prolonging cycle life of super capacitor |
| CN112509679A (en) * | 2020-12-04 | 2021-03-16 | 南通市第一人民医院 | Method and system for strengthening hospitalization management of obstetrics and gynecology department |
| CN112738129A (en) * | 2021-01-14 | 2021-04-30 | 北京国联视讯信息技术股份有限公司 | Identity verification and authentication method and system for network user |
| CN112991123A (en) * | 2021-01-22 | 2021-06-18 | 边婷 | Block chain-based information security processing method and system |
| CN112738129B (en) * | 2021-01-14 | 2024-06-28 | 北京国联视讯信息技术股份有限公司 | Identity verification and authentication method and system for network user |
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2020
- 2020-08-12 CN CN202010808895.7A patent/CN111954209A/en not_active Withdrawn
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112509679A (en) * | 2020-12-04 | 2021-03-16 | 南通市第一人民医院 | Method and system for strengthening hospitalization management of obstetrics and gynecology department |
| CN112433139A (en) * | 2020-12-18 | 2021-03-02 | 安徽诚越电子科技有限公司 | Method and device for prolonging cycle life of super capacitor |
| CN112738129A (en) * | 2021-01-14 | 2021-04-30 | 北京国联视讯信息技术股份有限公司 | Identity verification and authentication method and system for network user |
| CN112738129B (en) * | 2021-01-14 | 2024-06-28 | 北京国联视讯信息技术股份有限公司 | Identity verification and authentication method and system for network user |
| CN112991123A (en) * | 2021-01-22 | 2021-06-18 | 边婷 | Block chain-based information security processing method and system |
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