CN116980856B - Intelligent subway transponder control data transmission system and method based on Internet of things - Google Patents

Intelligent subway transponder control data transmission system and method based on Internet of things Download PDF

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CN116980856B
CN116980856B CN202311220998.1A CN202311220998A CN116980856B CN 116980856 B CN116980856 B CN 116980856B CN 202311220998 A CN202311220998 A CN 202311220998A CN 116980856 B CN116980856 B CN 116980856B
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transponder
transmission behavior
data
matrix
control
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CN116980856A (en
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俞太亮
卞能建
孙磊磊
潘冠俊
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Changzhou Metro Group Co ltd Operation Branch
Changzhou Ruihao Rail Transit Technology Co ltd
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Changzhou Metro Group Co ltd Operation Branch
Changzhou Ruihao Rail Transit Technology Co ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
    • H04W4/42—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for mass transport vehicles, e.g. buses, trains or aircraft
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00—Data switching networks
    • H04L12/02—Details
    • H04L12/06—Answer-back mechanisms or circuits
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
    • H04W12/03—Protecting confidentiality, e.g. by encryption
    • H04W12/033—Protecting confidentiality, e.g. by encryption of the user plane, e.g. user's traffic
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
    • H04W12/12—Detection or prevention of fraud
    • H04W12/121—Wireless intrusion detection systems [WIDS]; Wireless intrusion prevention systems [WIPS]
    • H04W12/122—Counter-measures against attacks; Protection against rogue devices
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
    • H04W12/60—Context-dependent security
    • H04W12/61—Time-dependent
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
    • H04W12/60—Context-dependent security
    • H04W12/68—Gesture-dependent or behaviour-dependent
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/70—Services for machine-to-machine communication [M2M] or machine type communication [MTC]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Abstract

The invention discloses an intelligent subway transponder control data transmission system and method based on the Internet of things, and belongs to the technical field of data management. Constructing a cloud platform of a data control center, comprehensively planning all subway transponders and carrying out uniform data cluster numbering, and storing transponder messages generated by correspondingly contained transponders under different data clusters; establishing a transponder message transmission behavior model matrix, integrating and converting the regional storage space set into the transponder message transmission behavior model matrix, and adding a recording time range label to the transponder message in the regional storage space set; generating a control transmission behavior feature matrix, and comprehensively planning all the control transmission behavior feature matrices; establishing a data cluster iterative screening model, outputting an implicit data cluster set and an explicit data cluster set, and encrypting the implicit data cluster set; furthermore, the data transmission safety of the transponder is ensured, and meanwhile, an attacker is confused by the dominant data cluster at an irregular period, so that the attacker cannot obtain the complete transponder data.

Description

Intelligent subway transponder control data transmission system and method based on Internet of things
Technical Field
The invention relates to the technical field of data management, in particular to an intelligent subway transponder control data transmission system and method based on the Internet of things.
Background
The subway transponder is key equipment in a subway system, is used for ensuring safe intervals and smooth running among trains, plays an important role in a subway signal system, and has the main functions of monitoring and controlling the positions, the speeds, the running states and the like of the trains;
in application publication No. 2018.05.04, application No. 201710983389.X, entitled method and system for data transmission using a ground transponder, an indication to enter an update mode and update data for vehicle operation control data is received from a control unit by a passive ground transponder; modifying the vehicle operation control data in the data storage unit according to the update data, and storing the updated vehicle operation control data in the data storage unit; receiving an indication from the control unit to enter an operational mode; the modulating unit carries out FSK modulation on the vehicle operation control data to obtain modulated vehicle operation control data; receiving a carrier frequency signal from the vehicle-mounted device by using a first antenna unit; converting the energy of the carrier frequency signal into a working power supply of the ground transponder; the ground transponder utilizes the first antenna unit to send the modulated vehicle operation control data to the vehicle-mounted transponder of the vehicle-mounted device; the requirements of vehicle-mounted equipment can be met, effective data information can be accurately and effectively sent, and the running safety of a vehicle can be more effectively ensured;
However, while the above-mentioned patents achieve a true and efficient transmission of data by passive or active ground transponders, the security of the transponder data transmission process is ignored.
Disclosure of Invention
The invention aims to provide an intelligent subway transponder control data transmission system and method based on the Internet of things, so as to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme:
intelligent subway transponder control data transmission system based on thing networking, this system includes: the system comprises a data control center cradle head module, a data model module, a characteristic behavior module and a data analysis module;
the data control center cradle head module is used for constructing a data control center cradle head, comprehensively planning all subway transponders and carrying out uniform data cluster numbering; storing transponder messages generated by transponders correspondingly contained in different data clusters, and generating a regional storage space set;
the data model module is used for establishing a transponder message transmission behavior model matrix, integrating and converting the regional storage space set into the transponder message transmission behavior model matrix; recording transponder messages transmitted by different transponders, respectively filling the transponder messages into corresponding regional storage space sets, and attaching a recording time range label to each transponder message in the regional storage space sets;
The characteristic behavior module generates a control transmission behavior characteristic matrix according to the transponder message transmission behavior model matrix and the time range label; overall controlling transmission behavior feature matrixes and generating a screening sample set;
the data analysis module is used for establishing a data cluster iterative screening model, calculating and controlling the transmission behavior similarity between transmission behavior feature matrixes, outputting an implicit data cluster set and an explicit data cluster set, and encrypting the implicit data cluster set.
Further, the data control center cradle head module further comprises a data cluster dividing unit and a region storage control unit;
the data cluster dividing unit is used for constructing a data control center holder, integrally planning all subway transponders and carrying out unified data cluster numbering, and the data control center holder divides a storage space and correspondingly stores each data cluster, wherein one data cluster correspondingly stores transponder messages generated by at least one subway transponder, the subway transponder has unique transponder coding attribute, and the data cluster numbering and the subway transponder coding group have unique binding relation;
the regional storage control unit is configured to record a data cluster number corresponding to a group of subway transponders as I, store all transponder messages generated under the data cluster I in a storage space of a data control center cradle head, and store all transponder messages stored in the storage space corresponding to the data cluster I to generate a regional storage space set, and record the regional storage space set as I i ={TM i1 ，TM i2 ，...，TM in }, wherein TM i1 ，TM i2 ，...，TM in Respectively representing transponder messages generated by n transponders and transponder message TM, under data cluster i, 1,2 1 ，TM 2 ，...，TM n The order of the control of the n transponders in the regional storage space set is arranged from first to second according to 1, 2.
Further, the data model module further comprises a transmission behavior model unit and an internet of things recording unit;
the transmission behavior model unit is used for establishing a transponder message transmission behavior model matrix, integrating and converting the regional storage space set into the transponder message transmission behavior model matrix, wherein the number of rows of the transponder message transmission behavior model matrix is the number of data clusters, namely the number of regional storage space sets, and the number of columns of the transponder message transmission behavior model matrix is the number of transponders corresponding to the transponder messages stored in the data clusters, namely the number of transponder messages contained in the regional storage space set; marking any matrix element in a transponder message transmission behavior model matrix as TM ij Where j is the number of the transponder, if the matrix element TM at the position of the matrix element of the ith row and jth column ij The matrix element at the position of the matrix element of the ith row and the jth column is set to be 0 element if the matrix element is empty, otherwise, the matrix element at the position of the matrix element of the ith row and the jth column is set to be TM ij ；
The internet of things recording unit is configured to record, in a T-th control period, transponder messages transmitted by each transponder, and fill the transponder messages into corresponding regional storage space sets respectively, and append a record time range tag to each transponder message in the regional storage space sets, where the time range tag includes an upload time range tag and a download time range tag, the upload time range represents a time range in which the transponder transmits the transponder message that is stored in advance or transmitted by the ground electronic unit LEU, and the download time range represents a time range in which the transponder receives the transponder message updated in real time.
Further, the characteristic behavior module further comprises a behavior characteristic matrix unit and a sample set overall unit;
the behavior characteristic matrix unit generates a control transmission behavior characteristic matrix according to the transponder message transmission behavior model matrix and the time range label, and if matrix elements TM are arranged in the transponder message transmission behavior model matrix ij The corresponding time range label is the uploading time range label, and the matrix element TM is made ij =1, if matrix element TM ij The corresponding time range label is the download time range label, and the matrix element TM is made ij If the control signal is not equal to 0, correspondingly converting the transponder message transmission behavior model matrix to generate a control transmission behavior characteristic matrix in a T-th control period, and marking the control transmission behavior characteristic matrix as R (T);
the sample set overall unit is configured to overall all control transmission behavior feature matrices in the category of the first T control periods, and generate a screening sample set, which is denoted as ss= { R (1), R (2),. The term "R (T) }, where R (1), R (2),. The term" R (T) respectively represents the 1 st, 2 nd, the term "T" control transmission behavior feature matrices generated correspondingly for the T control periods.
Further, the data analysis module further comprises a data cluster iterative screening model unit and an encryption transmission unit;
the data cluster iterative screening model unit is used for establishing a data cluster iterative screening model to enable the L-th iterative sample set to be SS L Then the 1 st iteration sample set is SS 1 And SS (x) 1 =ss; let the L iteration output sample set be RS L SS then L+1 =SS L -RS L ；
The L-th iterative screening process is as follows:
at the L-th iteration sample set SS L Optionally two control transmission behavior feature matrices, denoted as R (X) and R (Y), wherein X and Y represent an xth control period and a yth control period, respectively, and the transmission behavior similarity is calculated according to the following specific calculation formula:
P(XY)=NUM[R(X)∩R(Y)]/NUM[R(X)∪R(Y)]
wherein P (XY) represents the transmission behavior similarity between the control transmission behavior feature matrices R (X) and R (Y), NUM [ R (X)/(U) R (Y) ] and NUM [ R (X)/(U) R (Y) ] represent the number of matrix elements contained in the intersection and union between the control transmission behavior feature matrices R (X) and R (Y), respectively;
Presetting a similarity threshold, and marking a control transmission behavior feature matrix R (X) and R (Y) if the transmission behavior similarity is greater than or equal to the similarity threshold;
up to the L-th iteration sample set SS L After transmission behavior similarity calculation is carried out between all control transmission behavior feature matrixes in the system, stopping the L-th iteration, and incorporating all marked control transmission behavior feature matrixes into the L-th iteration output sample set RS L In (a) and (b);
after stopping the L-th iteration, entering the L+1th iteration until the transmission behavior similarity calculation is carried out between all the control transmission behavior feature matrixes in the screening sample set SS, and stopping the operation of the pseudo data cluster iteration screening model;
the encryption transmission unit is used for comprehensively iterating and outputting the sample set RS L Generating a recessive data cluster set, which is marked as YS, and a dominant data cluster set, which is marked as XS=SS-YS; encrypting the implicit data cluster set, and setting the reference authority.
The intelligent subway transponder control data transmission method based on the Internet of things comprises the following steps:
step S100: constructing a data control center cradle head, comprehensively planning all subway transponders and numbering uniform data clusters; storing transponder messages generated by transponders correspondingly contained in different data clusters, and generating a regional storage space set;
Step S200: establishing a transponder message transmission behavior model matrix, integrating and converting the regional storage space set into the transponder message transmission behavior model matrix; recording transponder messages transmitted by different transponders, respectively filling the transponder messages into corresponding regional storage space sets, and attaching a recording time range label to each transponder message in the regional storage space sets;
step S300: generating a control transmission behavior feature matrix according to the transponder message transmission behavior model matrix and the time range label; overall controlling transmission behavior feature matrixes and generating a screening sample set;
step S400: establishing a data cluster iterative screening model, calculating and controlling the similarity of transmission behaviors between transmission behavior feature matrixes, outputting an implicit data cluster set and an explicit data cluster set, and encrypting the implicit data cluster set.
Further, the specific implementation process of the step S100 includes:
step S101: a data control center cradle head is constructed, all subway transponders are organized and unified data cluster numbers are carried out, the data control center cradle head divides a storage space and correspondingly stores each data cluster, wherein one data cluster correspondingly stores transponder messages generated by at least one subway transponder, the subway transponder is provided with unique transponder coding attributes, and the data cluster numbers and a subway transponder coding group are provided with unique binding relations;
Step S102: the method comprises the steps of recording a data cluster number corresponding to a group of subway transponders as I, storing all transponder messages generated under the data cluster I in a storage space of a data control center holder, generating an area storage space set by storing all transponder messages stored in the storage space corresponding to the data cluster I, and recording the area storage space set as I i ={TM i1 ，TM i2 ，...，TM in }, wherein TM i1 ，TM i2 ，...，TM in Respectively representing transponder messages generated by n transponders and transponder message TM, under data cluster i, 1,2 1 ，TM 2 ，...，TM n The rank in the regional storage space set is according to 1,the control sequence of the n transponders is arranged from first to last.
Further, the specific implementation process of the step S200 includes:
step S201: establishing a transponder message transmission behavior model matrix, integrating and converting the regional storage space set into the transponder message transmission behavior model matrix, wherein the number of lines of the transponder message transmission behavior model matrix is the number of data clusters, namely the number of regional storage space sets, and the number of columns of the transponder message transmission behavior model matrix is the number of transponders corresponding to the transponder messages stored in the data clusters, namely the number of transponder messages contained in the regional storage space set; marking any matrix element in a transponder message transmission behavior model matrix as TM ij Where j is the number of the transponder, if the matrix element TM at the position of the matrix element of the ith row and jth column ij The matrix element at the position of the matrix element of the ith row and the jth column is set to be 0 element if the matrix element is empty, otherwise, the matrix element at the position of the matrix element of the ith row and the jth column is set to be TM ij ；
Step S202: and in the T control period, recording the transponder messages transmitted by each transponder, respectively filling the transponder messages into corresponding regional storage space sets, and additionally recording a time range label for each transponder message in the regional storage space sets, wherein the time range label comprises an uploading time range label and a downloading time range label, the uploading time range represents the time range of the transponder to transmit the transponder messages which are stored in advance or transmitted by a ground electronic unit LEU, and the downloading time range represents the time range of the transponder to receive the transponder messages updated in real time.
Further, the implementation process of the step S300 includes:
step S301: generating a control transmission behavior feature matrix according to the transponder message transmission behavior model matrix and the time range label, wherein if matrix elements TM are arranged in the transponder message transmission behavior model matrix ij The corresponding time range label is the uploading time range label, and the matrix element TM is made ij =1, if matrix element TM ij The corresponding time range label is the download time range label, and the matrix element TM is made ij If the control signal is not equal to 0, correspondingly converting the transponder message transmission behavior model matrix to generate a control transmission behavior characteristic matrix in a T-th control period, and marking the control transmission behavior characteristic matrix as R (T);
step S302: and (3) summarizing all control transmission behavior feature matrices in the category of the first T control periods, and generating a screening sample set, wherein the screening sample set is marked as SS= { R (1), R (2),. And R (T) }, wherein R (1), R (2),. And R (T) respectively represent the 1 st, 2 nd and the third control periods correspondingly generate the control transmission behavior feature matrices.
Further, the specific implementation process of the step S400 includes:
step S401: establishing a data cluster iterative screening model to enable the L-th iterative sample set to be SS L Then the 1 st iteration sample set is SS 1 And SS (x) 1 =ss; let the L iteration output sample set be RS L SS then L+1 =SS L -RS L ；
The L-th iterative screening process is as follows:
at the L-th iteration sample set SS L Optionally two control transmission behavior feature matrices, denoted as R (X) and R (Y), wherein X and Y represent an xth control period and a yth control period, respectively, and the transmission behavior similarity is calculated according to the following specific calculation formula:
P(XY)=NUM[R(X)∩R(Y)]/NUM[R(X)∪R(Y)]
Wherein P (XY) represents the transmission behavior similarity between the control transmission behavior feature matrices R (X) and R (Y), NUM [ R (X)/(U) R (Y) ] and NUM [ R (X)/(U) R (Y) ] represent the number of matrix elements contained in the intersection and union between the control transmission behavior feature matrices R (X) and R (Y), respectively;
presetting a similarity threshold, and marking a control transmission behavior feature matrix R (X) and R (Y) if the transmission behavior similarity is greater than or equal to the similarity threshold;
up to the L-th iteration sample set SS L After transmission behavior similarity calculation is carried out between all control transmission behavior feature matrixes in the model, stopping the L-th iteration, and performing special marking on all control transmission behaviorsThe sign matrix is incorporated into the L-th iteration output sample set RS L In (a) and (b);
after stopping the L-th iteration, entering the L+1th iteration until the transmission behavior similarity calculation is carried out between all the control transmission behavior feature matrixes in the screening sample set SS, and stopping the operation of the pseudo data cluster iteration screening model;
step S402: overall iteration output sample set RS L Generating a recessive data cluster set, which is marked as YS, and a dominant data cluster set, which is marked as XS=SS-YS; encrypting the recessive data cluster set, and setting a reference authority;
According to the method, the transmission behavior of the transponder in each control period reflects the subway operation behavior characteristics, the transmitted transponder message in the transponder records various related data of the subway operation, if the data in the transponder is not safely managed, an attacker can obtain various data of the subway operation through attack behaviors, so that various hazard behaviors can be easily made.
Compared with the prior art, the application has the following beneficial effects: in the intelligent subway transponder control data transmission system and method based on the Internet of things, a data control center cradle head is constructed, all subway transponders are comprehensively distributed and are numbered in a unified data cluster, and transponder messages generated by transponders correspondingly contained in different data clusters are stored; establishing a transponder message transmission behavior model matrix, integrating and converting the regional storage space set into the transponder message transmission behavior model matrix, and adding a recording time range label to the transponder message in the regional storage space set; generating a control transmission behavior feature matrix, and comprehensively planning all the control transmission behavior feature matrices; establishing a data cluster iterative screening model, outputting an implicit data cluster set and an explicit data cluster set, and encrypting the implicit data cluster set; furthermore, the data transmission safety of the transponder is ensured, and meanwhile, an attacker is confused by the dominant data cluster at an irregular period, so that the attacker cannot obtain the complete transponder data.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
fig. 1 is a schematic structural diagram of a smart subway transponder control data transmission system based on the internet of things;
FIG. 2 is a schematic diagram of steps of a smart subway transponder control data transmission method based on the Internet of things;
fig. 3 is an example application diagram of the intelligent subway transponder control data transmission method based on the internet of things.
Description of the embodiments
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1-2, the present invention provides the following technical solutions:
referring to fig. 1, in a first embodiment: provided is an intelligent subway transponder control data transmission system based on the Internet of things, which comprises: the system comprises a data control center cradle head module, a data model module, a characteristic behavior module and a data analysis module;
The data control center cradle head module is used for constructing a data control center cradle head, and comprehensively planning all subway transponders and carrying out uniform data cluster numbering; storing transponder messages generated by transponders correspondingly contained in different data clusters, and generating a regional storage space set;
the data control center cradle head module further comprises a data cluster dividing unit and a region storage control unit;
the data cluster dividing unit is used for constructing a data control center holder, integrally planning all subway transponders and carrying out unified data cluster numbering, and the data control center holder divides a storage space and correspondingly stores each data cluster, wherein one data cluster correspondingly stores transponder messages generated by at least one subway transponder, the subway transponder has unique transponder coding attribute, and the data cluster numbering and the subway transponder coding group have unique binding relation;
the regional storage control unit is used for marking the number of the data cluster corresponding to the subway transponder as I, storing all transponder messages generated under the data cluster I in the storage space of the cloud deck of the data control center, generating a regional storage space set by storing all transponder messages stored in the storage space corresponding to the data cluster I, and marking the regional storage space set as I i ={TM i1 ，TM i2 ，...，TM in }, wherein TM i1 ，TM i2 ，...，TM in Respectively representing transponder messages generated by n transponders and transponder message TM, under data cluster i, 1,2 1 ，TM 2 ，...，TM n The order of the bits in the regional storage space set is arranged from first to second according to 1, 2;
the data model module is used for establishing a transponder message transmission behavior model matrix, integrating and converting the regional storage space set into the transponder message transmission behavior model matrix; recording transponder messages transmitted by different transponders, respectively filling the transponder messages into corresponding regional storage space sets, and attaching a recording time range label to each transponder message in the regional storage space sets;
the data model module further comprises a transmission behavior model unit and an Internet of things recording unit;
the transmission behavior model unit is used for establishing a transponder message transmission behavior model matrix, integrating and converting the regional storage space set into the transponder message transmission behavior model matrix, wherein the number of lines of the transponder message transmission behavior model matrix is the number of data clusters, namely the number of regional storage space sets, and the number of columns of the transponder message transmission behavior model matrix is the number of transponders corresponding to the transponder messages stored in the data clusters, namely the number of transponder messages contained in the regional storage space set; marking any matrix element in a transponder message transmission behavior model matrix as TM ij Where j is the number of the transponder, if the matrix element TM at the position of the matrix element of the ith row and jth column ij The matrix element at the position of the matrix element of the ith row and the jth column is set to be 0 element if the matrix element is empty, otherwise, the matrix element at the position of the matrix element of the ith row and the jth column is set to be TM ij ；
The internet of things recording unit is used for recording transponder messages transmitted by each transponder in a T-th control period, respectively filling the transponder messages into corresponding regional storage space sets, and attaching a recording time range label to each transponder message in the regional storage space sets, wherein the time range label comprises an uploading time range label and a downloading time range label, the uploading time range represents the time range of the transponder message transmitted by a pre-stored or ground electronic unit LEU, and the downloading time range represents the time range of the transponder message received by the transponder to be updated in real time;
the characteristic behavior module is used for generating a control transmission behavior characteristic matrix according to the transponder message transmission behavior model matrix and the time range label; overall controlling transmission behavior feature matrixes and generating a screening sample set;
the characteristic behavior module further comprises a behavior characteristic matrix unit and a sample set overall unit;
The behavior characteristic matrix unit generates a control transmission behavior characteristic matrix according to the transponder message transmission behavior model matrix and the time range label, and if matrix elements TM in the transponder message transmission behavior model matrix ij Corresponding time range tagsFor uploading the time range label, the matrix element TM is made ij =1, if matrix element TM ij The corresponding time range label is the download time range label, and the matrix element TM is made ij If the control signal is not equal to 0, correspondingly converting the transponder message transmission behavior model matrix to generate a control transmission behavior characteristic matrix in a T-th control period, and marking the control transmission behavior characteristic matrix as R (T);
the sample set overall unit is used for overall planning all control transmission behavior feature matrixes in the category of the first T control periods and generating a screening sample set, wherein the screening sample set is recorded as SS= { R (1), R (2),. The R (T) }, wherein R (1), R (2),. The R (T) respectively represent the 1 st, the 2 nd and the third control periods, and the T control periods correspond to the generated control transmission behavior feature matrixes;
the data analysis module is used for establishing a data cluster iterative screening model, calculating and controlling the transmission behavior similarity among the transmission behavior feature matrixes, outputting a recessive data cluster set and a dominant data cluster set, and encrypting the recessive data cluster set;
The data analysis module further comprises a data cluster iterative screening model unit and an encryption transmission unit;
the data cluster iterative screening model unit is used for establishing a data cluster iterative screening model to enable the L-th iterative sample set to be SS L Then the 1 st iteration sample set is SS 1 And SS (x) 1 =ss; let the L iteration output sample set be RS L SS then L+1 =SS L -RS L ；
The L-th iterative screening process is as follows:
at the L-th iteration sample set SS L Optionally two control transmission behavior feature matrices, denoted as R (X) and R (Y), wherein X and Y represent an xth control period and a yth control period, respectively, and the transmission behavior similarity is calculated according to the following specific calculation formula:
P(XY)=NUM[R(X)∩R(Y)]/NUM[R(X)∪R(Y)]
wherein P (XY) represents the transmission behavior similarity between the control transmission behavior feature matrices R (X) and R (Y), NUM [ R (X)/(U) R (Y) ] and NUM [ R (X)/(U) R (Y) ] represent the number of matrix elements contained in the intersection and union between the control transmission behavior feature matrices R (X) and R (Y), respectively;
presetting a similarity threshold, and marking a control transmission behavior feature matrix R (X) and R (Y) if the transmission behavior similarity is greater than or equal to the similarity threshold;
up to the L-th iteration sample set SS L After transmission behavior similarity calculation is carried out between all control transmission behavior feature matrixes in the system, stopping the L-th iteration, and incorporating all marked control transmission behavior feature matrixes into the L-th iteration output sample set RS L In (a) and (b);
after stopping the L-th iteration, entering the L+1th iteration until the transmission behavior similarity calculation is carried out between all the control transmission behavior feature matrixes in the screening sample set SS, and stopping the operation of the pseudo data cluster iteration screening model;
an encryption transmission unit for comprehensively outputting the sample set RS by iteration L Generating a recessive data cluster set, which is marked as YS, and a dominant data cluster set, which is marked as XS=SS-YS; encrypting the implicit data cluster set, and setting the reference authority.
Referring to fig. 2, in the second embodiment: the intelligent subway transponder control data transmission method based on the Internet of things comprises the following steps:
constructing a data control center cradle head, comprehensively planning all subway transponders and numbering uniform data clusters; storing transponder messages generated by transponders correspondingly contained in different data clusters, and generating a regional storage space set;
constructing a data control center cradle head, comprehensively planning all subway transponders and carrying out uniform data cluster numbering, wherein the data control center cradle head divides a storage space and correspondingly stores each data cluster, one data cluster correspondingly stores transponder messages generated by at least one subway transponder, the subway transponder has unique transponder coding attribute, and the data cluster numbering and a subway transponder coding group have unique binding relation;
Recording the number of a data cluster corresponding to a group of subway transponders as i, and storing all transponder messages generated under the data cluster i in a storage space of a cloud deck of a data control centerIn the method, all transponder messages stored in a storage space corresponding to a data cluster I are generated into a regional storage space set which is marked as I i ={TM i1 ，TM i2 ，...，TM in }, wherein TM i1 ，TM i2 ，...，TM in Respectively representing transponder messages generated by n transponders and transponder message TM, under data cluster i, 1,2 1 ，TM 2 ，...，TM n The order of the bits in the regional storage space set is arranged from first to second according to 1, 2;
establishing a transponder message transmission behavior model matrix, integrating and converting the regional storage space set into the transponder message transmission behavior model matrix; recording transponder messages transmitted by different transponders, respectively filling the transponder messages into corresponding regional storage space sets, and attaching a recording time range label to each transponder message in the regional storage space sets;
establishing a transponder message transmission behavior model matrix, integrating and converting the regional storage space set into the transponder message transmission behavior model matrix, wherein the number of lines of the transponder message transmission behavior model matrix is the number of data clusters, namely the number of regional storage space sets, and the number of columns of the transponder message transmission behavior model matrix is the number of transponders corresponding to the transponder messages stored in the data clusters, namely the number of transponder messages contained in the regional storage space set; marking any matrix element in a transponder message transmission behavior model matrix as TM ij Where j is the number of the transponder, if the matrix element TM at the position of the matrix element of the ith row and jth column ij The matrix element at the position of the matrix element of the ith row and the jth column is set to be 0 element if the matrix element is empty, otherwise, the matrix element at the position of the matrix element of the ith row and the jth column is set to be TM ij ；
In the T control period, recording transponder messages transmitted by each transponder, respectively filling the transponder messages into corresponding regional storage space sets, and additionally recording a time range label for each transponder message in the regional storage space sets, wherein the time range label comprises an uploading time range label and a downloading time range label, the uploading time range represents the time range of the transponder to transmit the transponder messages which are stored in advance or transmitted by a ground electronic unit LEU, and the downloading time range represents the time range of the transponder to receive the transponder messages updated in real time;
generating a control transmission behavior feature matrix according to the transponder message transmission behavior model matrix and the time range label; overall controlling transmission behavior feature matrixes and generating a screening sample set;
generating a control transmission behavior feature matrix according to the transponder message transmission behavior model matrix and the time range label, wherein if matrix elements TM are arranged in the transponder message transmission behavior model matrix ij The corresponding time range label is the uploading time range label, and the matrix element TM is made ij =1, if matrix element TM ij The corresponding time range label is the download time range label, and the matrix element TM is made ij If the control signal is not equal to 0, correspondingly converting the transponder message transmission behavior model matrix to generate a control transmission behavior characteristic matrix in a T-th control period, and marking the control transmission behavior characteristic matrix as R (T);
the method comprises the steps of summarizing all control transmission behavior feature matrices in the category of the first T control periods, generating a screening sample set, and recording as SS= { R (1), R (2),. The R (T) }, wherein R (1), R (2),. The R (T) respectively represents the 1 st, 2 nd, the R (T) and the T control periods correspondingly generate the control transmission behavior feature matrices;
establishing a data cluster iterative screening model, calculating and controlling the similarity of transmission behaviors between transmission behavior feature matrixes, outputting a recessive data cluster set and a dominant data cluster set, and encrypting the recessive data cluster set;
establishing a data cluster iterative screening model to enable the L-th iterative sample set to be SS L Then the 1 st iteration sample set is SS 1 And SS (x) 1 =ss; let the L iteration output sample set be RS L SS then L+1 =SS L -RS L ；
The L-th iterative screening process is as follows:
at the L-th iteration sample set SS L Optionally two control transmission actions And the characteristic matrix is marked as R (X) and R (Y), wherein X and Y respectively represent an X-th control period and a Y-th control period, and the similarity of transmission behaviors is calculated according to the following specific calculation formula:
P(XY)=NUM[R(X)∩R(Y)]/NUM[R(X)∪R(Y)]
wherein P (XY) represents the transmission behavior similarity between the control transmission behavior feature matrices R (X) and R (Y), NUM [ R (X)/(U) R (Y) ] and NUM [ R (X)/(U) R (Y) ] represent the number of matrix elements contained in the intersection and union between the control transmission behavior feature matrices R (X) and R (Y), respectively;
presetting a similarity threshold, and marking a control transmission behavior feature matrix R (X) and R (Y) if the transmission behavior similarity is greater than or equal to the similarity threshold;
up to the L-th iteration sample set SS L After transmission behavior similarity calculation is carried out between all control transmission behavior feature matrixes in the system, stopping the L-th iteration, and incorporating all marked control transmission behavior feature matrixes into the L-th iteration output sample set RS L In (a) and (b);
after stopping the L-th iteration, entering the L+1th iteration until the transmission behavior similarity calculation is carried out between all the control transmission behavior feature matrixes in the screening sample set SS, and stopping the operation of the pseudo data cluster iteration screening model;
overall iteration output sample set RS L Generating a recessive data cluster set, which is marked as YS, and a dominant data cluster set, which is marked as XS=SS-YS; encrypting the recessive data cluster set, and setting a reference authority;
referring to fig. 3, the data control center cradle head is connected with an industrial personal computer, and the industrial personal computer is connected with the main control cabinets 1 and 2 through wireless 4G or optical fiber networking communication; the main control cabinet 1 is connected with the regional control cabinets 1 and 2 through CET6 or wireless 4G; the area control cabinets 1 and 2 are connected through CET6 or wireless 4G; the area control cabinet 1 is connected with the elevators 1 and 2 through 2 signal cables, a transponder is integrated in the elevators, and the lifting of the elevators is controlled in a centralized or independent way through a single control box on the elevators; the regional storage space set corresponds to transponder messages generated by transponders in the elevators 1 and 2 in the regional control cabinet 1, and the data cluster 1 records corresponding transponder messages in the regional control cabinet 1.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention and is not intended to limit the present invention, but although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the technical solutions described in the foregoing embodiments, or equivalents may be substituted for some of the technical features thereof. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (4)

1. The intelligent subway transponder control data transmission method based on the Internet of things is characterized by comprising the following steps of:
step S100: constructing a data control center cradle head, comprehensively planning all subway transponders and numbering uniform data clusters; storing transponder messages generated by transponders correspondingly contained in different data clusters, and generating a regional storage space set;
step S200: establishing a transponder message transmission behavior model matrix, integrating and converting the regional storage space set into the transponder message transmission behavior model matrix; recording transponder messages transmitted by different transponders, respectively filling the transponder messages into corresponding regional storage space sets, and attaching a recording time range label to each transponder message in the regional storage space sets;
Step S300: generating a control transmission behavior feature matrix according to the transponder message transmission behavior model matrix and the time range label; overall controlling transmission behavior feature matrixes and generating a screening sample set;
step S400: establishing a data cluster iterative screening model, calculating and controlling the similarity of transmission behaviors between transmission behavior feature matrixes, outputting a recessive data cluster set and a dominant data cluster set, and encrypting the recessive data cluster set;
the specific implementation process of the step S100 includes:
step S101: a data control center cradle head is constructed, all subway transponders are organized and unified data cluster numbers are carried out, the data control center cradle head divides a storage space and correspondingly stores each data cluster, wherein one data cluster correspondingly stores transponder messages generated by at least one subway transponder, the subway transponder is provided with unique transponder coding attributes, and the data cluster numbers and a subway transponder coding group are provided with unique binding relations;
step S102: the method comprises the steps of recording a data cluster number corresponding to a group of subway transponders as I, storing all transponder messages generated under the data cluster I in a storage space of a data control center holder, generating an area storage space set by storing all transponder messages stored in the storage space corresponding to the data cluster I, and recording the area storage space set as I i ={TM i1 ，TM i2 ，...，TM in }, wherein TM i1 ，TM i2 ，...，TM in Respectively representing transponder messages generated by n transponders and transponder message TM, under data cluster i, 1,2 1 ，TM 2 ，...，TM n The order of the bits in the regional storage space set is arranged from first to second according to 1, 2;
the specific implementation process of the step S200 includes:
step S201: establishing a transponder message transmission behavior model matrix, integrating and converting the regional storage space set into the transponder message transmission behavior model matrix, and transmitting the transponder messageThe number of lines of the model matrix is the number of data clusters, namely the number of regional storage space sets, and the number of columns of the transponder message transmission behavior model matrix is the number of transponders for correspondingly storing transponder messages in the data clusters, namely the number of transponder messages contained in the regional storage space sets; marking any matrix element in a transponder message transmission behavior model matrix as TM ij Where j is the number of the transponder, if the matrix element TM at the position of the matrix element of the ith row and jth column ij The matrix element at the position of the matrix element of the ith row and the jth column is set to be 0 element if the matrix element is empty, otherwise, the matrix element at the position of the matrix element of the ith row and the jth column is set to be TM ij ；
Step S202: recording transponder messages transmitted by each transponder in a T control period, respectively filling the transponder messages into corresponding regional storage space sets, and additionally recording a time range label for each transponder message in the regional storage space sets, wherein the time range label comprises an uploading time range label and a downloading time range label, the uploading time range represents the time range of the transponder to transmit the transponder messages which are stored in advance or transmitted by a ground electronic unit LEU, and the downloading time range represents the time range of the transponder to receive the transponder messages updated in real time;
the specific implementation process of the step S300 includes:
step S301: generating a control transmission behavior feature matrix according to the transponder message transmission behavior model matrix and the time range label, wherein if matrix elements TM are arranged in the transponder message transmission behavior model matrix ij The corresponding time range label is the uploading time range label, and the matrix element TM is made ij =1, if matrix element TM ij The corresponding time range label is the download time range label, and the matrix element TM is made ij If the control signal is not equal to 0, correspondingly converting the transponder message transmission behavior model matrix to generate a control transmission behavior characteristic matrix in a T-th control period, and marking the control transmission behavior characteristic matrix as R (T);
Step S302: and (3) summarizing all control transmission behavior feature matrices in the category of the first T control periods, and generating a screening sample set, wherein the screening sample set is marked as SS= { R (1), R (2),. And R (T) }, wherein R (1), R (2),. And R (T) respectively represent the 1 st, 2 nd and the third control periods correspondingly generate the control transmission behavior feature matrices.
2. The intelligent subway transponder control data transmission method based on the internet of things according to claim 1, wherein the specific implementation process of the step S400 includes:
step S401: establishing a data cluster iterative screening model to enable the L-th iterative sample set to be SS L Then the 1 st iteration sample set is SS 1 And SS (x) 1 =ss; let the L iteration output sample set be RS L SS then L+1 =SS L -RS L ；
The L-th iterative screening process is as follows:
at the L-th iteration sample set SS L Optionally two control transmission behavior feature matrices, denoted as R (X) and R (Y), wherein X and Y represent an xth control period and a yth control period, respectively, and the transmission behavior similarity is calculated according to the following specific calculation formula:
P(XY)=NUM[R(X)∩R(Y)]/NUM[R(X)∪R(Y)]
wherein P (XY) represents the transmission behavior similarity between the control transmission behavior feature matrices R (X) and R (Y), NUM [ R (X)/(U) R (Y) ] and NUM [ R (X)/(U) R (Y) ] represent the number of matrix elements contained in the intersection and union between the control transmission behavior feature matrices R (X) and R (Y), respectively;
Presetting a similarity threshold, and marking a control transmission behavior feature matrix R (X) and R (Y) if the transmission behavior similarity is greater than or equal to the similarity threshold;
up to the L-th iteration sample set SS L After transmission behavior similarity calculation is carried out between all control transmission behavior feature matrixes in the system, stopping the L-th iteration, and incorporating all marked control transmission behavior feature matrixes into the L-th iteration output sample set RS L In (a) and (b);
after stopping the L-th iteration, entering the L+1th iteration until the transmission behavior similarity calculation is carried out between all the control transmission behavior feature matrixes in the screening sample set SS, and stopping the operation of the pseudo data cluster iteration screening model;
step S402: overall iteration output sample set RS L Generating a recessive data cluster set, which is marked as YS, and a dominant data cluster set, which is marked as XS=SS-YS; encrypting the implicit data cluster set, and setting the reference authority.
3. Intelligent subway transponder control data transmission system based on thing networking, its characterized in that, the system includes: the system comprises a data control center cradle head module, a data model module, a characteristic behavior module and a data analysis module;
the data control center cradle head module is used for constructing a data control center cradle head, comprehensively planning all subway transponders and carrying out uniform data cluster numbering; storing transponder messages generated by transponders correspondingly contained in different data clusters, and generating a regional storage space set;
The data model module is used for establishing a transponder message transmission behavior model matrix, integrating and converting the regional storage space set into the transponder message transmission behavior model matrix; recording transponder messages transmitted by different transponders, respectively filling the transponder messages into corresponding regional storage space sets, and attaching a recording time range label to each transponder message in the regional storage space sets;
the characteristic behavior module generates a control transmission behavior characteristic matrix according to the transponder message transmission behavior model matrix and the time range label; overall controlling transmission behavior feature matrixes and generating a screening sample set;
the data analysis module is used for establishing a data cluster iterative screening model, calculating and controlling the transmission behavior similarity between transmission behavior feature matrixes, outputting a recessive data cluster set and a dominant data cluster set, and encrypting the recessive data cluster set;
the data control center cradle head module further comprises a data cluster dividing unit and a region storage control unit;
the data cluster dividing unit is used for constructing a data control center holder, integrally planning all subway transponders and carrying out unified data cluster numbering, and the data control center holder divides a storage space and correspondingly stores each data cluster, wherein one data cluster correspondingly stores transponder messages generated by at least one subway transponder, the subway transponder has unique transponder coding attribute, and the data cluster numbering and the subway transponder coding group have unique binding relation;
The regional storage control unit is configured to record a data cluster number corresponding to a group of subway transponders as I, store all transponder messages generated under the data cluster I in a storage space of a data control center cradle head, and store all transponder messages stored in the storage space corresponding to the data cluster I to generate a regional storage space set, and record the regional storage space set as I i ={TM i1 ，TM i2 ，...，TM in }, wherein TM i1 ，TM i2 ，...，TM in Respectively representing transponder messages generated by n transponders and transponder message TM, under data cluster i, 1,2 1 ，TM 2 ，...，TM n The order of the bits in the regional storage space set is arranged from first to second according to 1, 2;
the data model module further comprises a transmission behavior model unit and an Internet of things recording unit;
the transmission behavior model unit is used for establishing a transponder message transmission behavior model matrix, integrating and converting the regional storage space set into the transponder message transmission behavior model matrix, wherein the number of rows of the transponder message transmission behavior model matrix is the number of data clusters, namely the number of regional storage space sets, and the number of columns of the transponder message transmission behavior model matrix is the number of transponders corresponding to the transponder messages stored in the data clusters, namely the number of transponder messages contained in the regional storage space set; marking any matrix element in a transponder message transmission behavior model matrix as TM ij Where j is the number of the transponder, if the matrix element TM at the position of the matrix element of the ith row and jth column ij The matrix element at the position of the matrix element of the ith row and the jth column is set to be 0 element if the matrix element is empty, otherwise, the matrix element at the position of the matrix element of the ith row and the jth column is set to be 0 elementIs TM ij ；
The internet of things recording unit is configured to record, in a T-th control period, transponder messages transmitted by each transponder, respectively fill the transponder messages into corresponding regional storage space sets, and append a record time range tag to each transponder message in the regional storage space sets, where the time range tag includes an uploading time range tag and a downloading time range tag, the uploading time range represents a time range in which the transponder transmits the transponder message that is stored in advance or transmitted by the ground electronic unit LEU, and the downloading time range represents a time range in which the transponder receives the transponder message that is updated in real time;
the characteristic behavior module further comprises a behavior characteristic matrix unit and a sample set overall unit;
the behavior characteristic matrix unit generates a control transmission behavior characteristic matrix according to the transponder message transmission behavior model matrix and the time range label, and if matrix elements TM are arranged in the transponder message transmission behavior model matrix ij The corresponding time range label is the uploading time range label, and the matrix element TM is made ij =1, if matrix element TM ij The corresponding time range label is the download time range label, and the matrix element TM is made ij If the control signal is not equal to 0, correspondingly converting the transponder message transmission behavior model matrix to generate a control transmission behavior characteristic matrix in a T-th control period, and marking the control transmission behavior characteristic matrix as R (T);
the sample set overall unit is configured to overall all control transmission behavior feature matrices in the category of the first T control periods, and generate a screening sample set, which is denoted as ss= { R (1), R (2),. The term "R (T) }, where R (1), R (2),. The term" R (T) respectively represents the 1 st, 2 nd, the term "T" control transmission behavior feature matrices generated correspondingly for the T control periods.
4. The intelligent subway transponder control data transmission system based on the internet of things according to claim 3, wherein: the data analysis module further comprises a data cluster iterative screening model unit and an encryption transmission unit;
the data cluster iteratesA screening model unit for establishing a data cluster iterative screening model to make the L-th iterative sample set be SS L Then the 1 st iteration sample set is SS 1 And SS (x) 1 =ss; let the L iteration output sample set be RS L SS then L+1 =SS L -RS L ；
The L-th iterative screening process is as follows:
at the L-th iteration sample set SS L Optionally two control transmission behavior feature matrices, denoted as R (X) and R (Y), wherein X and Y represent an xth control period and a yth control period, respectively, and the transmission behavior similarity is calculated according to the following specific calculation formula:
P(XY)=NUM[R(X)∩R(Y)]/NUM[R(X)∪R(Y)]
wherein P (XY) represents the transmission behavior similarity between the control transmission behavior feature matrices R (X) and R (Y), NUM [ R (X)/(U) R (Y) ] and NUM [ R (X)/(U) R (Y) ] represent the number of matrix elements contained in the intersection and union between the control transmission behavior feature matrices R (X) and R (Y), respectively;
presetting a similarity threshold, and marking a control transmission behavior feature matrix R (X) and R (Y) if the transmission behavior similarity is greater than or equal to the similarity threshold;
up to the L-th iteration sample set SS L After transmission behavior similarity calculation is carried out between all control transmission behavior feature matrixes in the system, stopping the L-th iteration, and incorporating all marked control transmission behavior feature matrixes into the L-th iteration output sample set RS L In (a) and (b);
after stopping the L-th iteration, entering the L+1th iteration until the transmission behavior similarity calculation is carried out between all the control transmission behavior feature matrixes in the screening sample set SS, and stopping the operation of the pseudo data cluster iteration screening model;
The encryption transmission unit is used for comprehensively iterating and outputting the sample set RS L Generating a recessive data cluster set, which is marked as YS, and a dominant data cluster set, which is marked as XS=SS-YS; encrypting the implicit data cluster set, and setting the reference authority.
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