Mine data secure transmission method and system based on block chain

Abstract

The invention relates to the field of data transmission, in particular to a mine data secure transmission method and system based on a block chain, and the method comprises the steps: determining a data type according to a danger coefficient of target mine data and a historical accident emergency rate; determining a data processing state according to the mine data reference value and the node processing reference value; determining a data transmission mode according to the data processing state: determining an analysis mode according to a first-class data proportion and distributing second-class data to the node with the maximum node processing reference value, or determining a processing sequence according to the priority coefficient of each target mine data and selecting the node corresponding to the shortest reference distance for transmission; according to the proportion of the first-class data, determining an analysis mode to combine the first-class data with the same operation link or combine all the first-class data; and determining an encryption method according to whether the target mine data is recorded as the data combination. According to the invention, the dangerous information can be effectively identified and timely transmitted to the node, and the dangerous information transmission efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of data transmission, and in particular to a method and system for secure transmission of mine data based on blockchain. Background Art

[0002] There are a lot of dangerous information hidden in the mine data that may cause accidents. The development of mine informatization construction has led to a surge in the amount of mine data information. Due to the limited node processing capacity, when the amount of data surges, it is impossible to choose a reasonable way to transmit the dangerous information that may cause accidents to the node in time, resulting in the inability to respond to the dangerous information in time, increasing the risk of mine accidents. Therefore, how to effectively identify dangerous information and choose a reasonable way to transmit the dangerous information to the node in time to ensure the efficiency of dangerous information transmission is an urgent problem to be solved by technical personnel in this field.

[0003] Chinese patent publication number CN117879787B discloses a method and system for realizing the secure transmission of mine data based on blockchain, including: arranging a data collection unit of a mine, collecting mine data of the mine through the data collection unit, performing sensitive equivalent replacement on the mine data, and obtaining equivalent mine data; performing homomorphic encryption on the equivalent mine data, obtaining encrypted mine data, and constructing a mine blockchain network of the mine; distributing and storing the encrypted mine data in the corresponding block nodes of the mine blockchain network to obtain a unit blockchain; extracting the data transmission record of the data storage process in the unit blockchain, constructing a transmission transaction tree of the data transmission record, and verifying the transmission transaction tree to obtain verification data; generating a permission smart contract and a secure transmission protocol for the verification data, and executing the data security transmission of the verification data through the permission smart contract and the secure transmission protocol. It can be seen that the above technical solution has the following problems: it is impossible to effectively identify dangerous information, and it is impossible to transmit dangerous information to the node in a timely manner, resulting in poor efficiency in the transmission of dangerous information. Summary of the invention

[0004] To this end, the present invention provides a blockchain-based mine data security transmission method and system to overcome the problem in the prior art that dangerous information cannot be effectively identified and cannot be transmitted to nodes in a timely manner, resulting in poor efficiency in dangerous information transmission.

[0005] To achieve the above purpose, the present invention provides a method for secure transmission of mine data based on blockchain, comprising:

[0006] Determine the data type based on the risk factor of the target mine data and the historical accident rate;

[0007] Determine the data processing status according to the mine data reference value and the node processing reference value;

[0008] Determine the data transmission mode according to the data processing status: determine the analysis mode according to the proportion of the first type of data and distribute the second type of data to the node with the largest node processing reference value, or determine the processing order according to the priority coefficient of each target mine data and select the node corresponding to the shortest reference distance for transmission;

[0009] Determine the analysis method based on the proportion of a type of data, which is to combine the data of the same type of operation links or to combine all the data of the same type;

[0010] When combining the first-class data with the same operation links, the first-class data combination corresponding to each operation link and each second-class data are transmitted to the corresponding node processing node with the largest reference value according to the risk factor;

[0011] When all the first-class data are combined, the second-class data are combined according to the proportion of the same characteristics and the correlation coefficient, and each data combination and the second-class data not recorded as a data combination are transmitted to the corresponding node processing node with the largest reference value according to the risk coefficient;

[0012] The encryption method is determined to be single encryption or double encryption according to whether the target mine data is recorded as a data combination.

[0013] Further, the risk factor is determined based on the regional risk factor and the differential risk factor;

[0014] The relationship between the regional risk factor and the regional coefficient is a positive correlation;

[0015] The relationship between the difference risk coefficient and the difference index is a positive correlation.

[0016] Furthermore, the regional coefficient is determined according to the mining intensity coefficient and the stratum disturbance coefficient, the mining intensity coefficient is positively correlated with the mining intensity, and the stratum disturbance coefficient is positively correlated with the stratum disturbance value;

[0017] The mining intensity is determined based on the ratio of the mining volume to the area of ​​the region;

[0018] The formation disturbance value is determined according to the maximum mining depth, and the relationship between the formation disturbance value and the maximum mining depth is a positive correlation.

[0019] Furthermore, the target mine data types include video data and environmental data, and the determination methods of the difference indexes corresponding to different target mine data types are different;

[0020] For a video data, the difference index is determined according to the abnormal feature proportion, and the relationship between the difference index and the abnormal feature proportion is a positive correlation;

[0021] For a piece of environmental data, the difference index is determined according to the data deviation degree, and the relationship between the difference index and the data deviation degree is a positive correlation.

[0022] Furthermore, under preset conditions, if the proportion of the first category of data is greater than or equal to the preset proportion of the first category of data, the first category of data with the same operation link is combined, and the first category of data combination corresponding to each operation link and each second category of data are recorded as data to be transmitted, and the transmission order of the data to be transmitted is determined according to the risk assessment value, and for a single data to be transmitted, the node with the largest node processing reference value is selected for allocation;

[0023] The preset condition is that the data processing state is that the mine data reference value is greater than or equal to the preset mine data reference value or the node processing reference value is less than the preset node processing reference value.

[0024] Furthermore, under preset conditions, if the proportion of one type of data is less than the preset proportion of one type of data, all the one type of data are combined, and the two types of data are combined according to the proportion of the same characteristics and the correlation coefficient, and each data combination and the two types of data that are not recorded as data combinations are transmitted to the corresponding node according to the risk factor to process the node with the largest reference value.

[0025] Furthermore, a combined analysis is performed on the two types of data based on the proportion of the same features and the correlation coefficient:

[0026] When performing combined analysis on a single second-category data, the second-category data is recorded as the target second-category data, and other data not including the target second-category data is recorded as the reference second-category data.

[0027] If the target second-category data is video data, the video data corresponding to the reference second-category data are combined according to the proportion of the same features, and the video data corresponding to the reference second-category data whose proportion of the same features as the target second-category data is greater than the preset proportion of the same features and the target second-category data are uniformly recorded as one data combination;

[0028] If the target second-category data is environmental data, the environmental data corresponding to the reference second-category data are combined according to the correlation coefficient, and the environmental data corresponding to the reference second-category data whose correlation coefficient with the target second-category data is greater than the preset correlation coefficient and the target second-category data are uniformly recorded as one data combination;

[0029] After the combination analysis of the target second category data is completed, the combination analysis is continued for the reference second category data that is not recorded as a data combination.

[0030] Further, when the data processing state is that the mine data reference value is less than the preset mine data reference value and the node processing reference value is greater than or equal to the preset node processing reference value, the processing order is determined according to the priority coefficient of each target mine data, and the node corresponding to the shortest reference distance is selected for transmission;

[0031] The priority coefficient of the target mine data is positively correlated with the risk assessment value.

[0032] Furthermore, for the target mine data corresponding to the data combination, the encryption method is to encrypt the target mine data once using an encryption algorithm, and to encrypt the mine data ciphertext combination corresponding to each target mine data twice using an encryption algorithm;

[0033] For target mine data that is not recorded as a data combination, the encryption method is to encrypt the target mine data once using an encryption algorithm.

[0034] The present invention also provides a blockchain-based mine data security transmission system, comprising:

[0035] Data acquisition module, used to collect target mine data;

[0036] A data processing module, which is connected to the data acquisition module, is used to determine the data type according to the risk factor of the target mine data and the historical accident rate, and to determine the data processing state according to the mine data reference value and the node processing reference value;

[0037] A data transmission module, connected to the data processing module, for determining a data transmission mode according to a data processing state;

[0038] A combined analysis module, which is connected to the data processing module and the data transmission module, and is used to determine an analysis method according to the proportion of a type of data;

[0039] The data encryption module is connected to the data transmission module and the combination analysis module, and is used to determine whether the encryption method is one-time encryption or two-time encryption according to whether the target mine data is recorded as a data combination.

[0040] Compared with the prior art, the beneficial effect of the present invention lies in that, in the technical scheme of the present invention, the data processing status is determined according to the mine data reference value and the node processing reference value, the processing capacity of the current node is effectively reflected through the mine data reference value and the node processing reference value, and different data transmission methods are adaptively selected according to the data processing status, so that the selection of data transmission method is more in line with the actual working scenario, avoiding the problem that the dangerous information cannot be transmitted to the node in time due to excessive amount of node processing data, thereby ensuring the efficiency of dangerous information transmission.

[0041] Furthermore, the data type is determined according to the hazard coefficient of the target mine data and the historical accident burst rate. The hazard coefficient of the target mine data and the historical accident burst rate can effectively reflect the probability of accidents caused by the target mine data, and then effectively divide the data into Class I and Class II. The proportion of Class I data can effectively reflect the proportion of dangerous information that is currently prone to accidents, and then adaptively select different analysis methods, so that the selection of analysis methods is more in line with the actual application scenarios, avoiding the problem that dangerous information cannot be transmitted to the node in time when the node processing capacity is limited, thereby ensuring the efficiency of dangerous information transmission.

[0042] Furthermore, in the present invention, when the proportion of a type of data is greater than or equal to the proportion of a preset type of data, the type of data with the same operation link is combined, which is beneficial to ensuring the analysis efficiency of the target mine data, and also avoiding the problem of long task waiting time when the node processing capacity is insufficient, thereby transmitting the dangerous information to the node in time, and reflecting the processing capacity of the node through the node processing reference value, and selecting the node with the largest node processing reference value for allocation, thereby avoiding the problem of data transmission delay and long waiting time, thereby improving data processing efficiency.

[0043] Furthermore, in the present invention, when the proportion of one type of data is less than the preset proportion of one type of data, all the data of one type are combined, thereby avoiding the problem of long task waiting time when the node processing capacity is insufficient, and then transmitting the dangerous information to the node in time. By combining the two types of data according to the proportion of the same characteristics and the correlation coefficient, it can be ensured that the data in the data combination has a strong correlation, making the subsequent data analysis more efficient, thereby improving the data processing efficiency.

[0044] Furthermore, in the present invention, when the data processing status is that the mine data reference value is less than the preset mine data reference value and the node processing reference value is greater than or equal to the preset node processing reference value, the processing order is determined according to the priority coefficient of each target mine data, which can ensure that the dangerous information can be transmitted in time, and select the node corresponding to the shortest reference distance for transmission, thereby avoiding the problem of excessive transmission time and improving data processing efficiency.

[0045] Furthermore, in the present invention, the encryption method is determined according to whether the target mine data is recorded as a data combination. Whether the target mine data is recorded as a data combination effectively reflects the characteristics and security requirements of the data, and then different encryption methods are adaptively selected, so that the setting of the encryption method is more in line with the actual application scenario, which can help to flexibly respond to different security requirements, avoid the risk of leakage of target mine data, and thus ensure the security of the target mine data. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1This is a schematic diagram of a method for securely transmitting mining data based on blockchain according to the present invention;

[0047] Figure 2 A flow chart of determining a data transmission mode according to a data processing state according to the present invention;

[0048] Figure 3 This is a flow chart of the present invention for determining an analysis method according to a proportion of a type of data;

[0049] Figure 4 This is a module connection diagram of the blockchain-based mine data security transmission system of the present invention. DETAILED DESCRIPTION

[0050] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0051] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0052] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0053] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0054] See also Figures 1 to 3 As shown, the present invention provides a method for secure transmission of mine data based on blockchain, comprising:

[0055] Determine the data type based on the risk factor of the target mine data and the historical accident rate;

[0056] Determine the data processing status according to the mine data reference value and the node processing reference value;

[0057] Determine the data transmission mode according to the data processing status: determine the analysis mode according to the proportion of the first type of data and distribute the second type of data to the node with the largest node processing reference value, or determine the processing order according to the priority coefficient of each target mine data and select the node corresponding to the shortest reference distance for transmission;

[0058] Determine the analysis method based on the proportion of a type of data, which is to combine the data of the same type of operation links or to combine all the data of the same type;

[0059] When combining the first-class data with the same operation links, the first-class data combination corresponding to each operation link and each second-class data are transmitted to the corresponding node processing node with the largest reference value according to the risk factor;

[0060] When all the first-class data are combined, the second-class data are combined according to the proportion of the same characteristics and the correlation coefficient, and each data combination and the second-class data not recorded as a data combination are transmitted to the corresponding node processing node with the largest reference value according to the risk coefficient;

[0061] The encryption method is determined to be single encryption or double encryption according to whether the target mine data is recorded as a data combination.

[0062] The application scenario of the present invention is the field of mine data transmission. The target mine data types include video data and environmental data. The video data is data collected by a monitoring device, and the environmental data is data collected by sensors such as temperature sensors, dust concentration sensors and pressure sensors. A continuous cyclic monitoring cycle is provided in the present invention. At the end of each monitoring cycle, the data processing unit determines the data status once. The duration of the monitoring cycle can be set according to user needs. The greater the user's demand for the efficiency of dangerous data allocation processing, the shorter the duration of the monitoring cycle. A value of a monitoring cycle is provided, and the monitoring cycle is 1 minute. Each target mine data generated in a single cycle corresponds to a data source. The data source corresponding to the video data is each monitoring device, and the data source corresponding to the environmental data is each sensor.

[0063] The data types in the present invention include:

[0064] Data with a risk factor greater than or equal to a preset risk factor or a historical accident rate greater than or equal to a preset historical accident rate;

[0065] The second type of data refers to the data whose risk factor is less than the preset risk factor and whose historical accident rate is less than the preset historical accident rate.

[0066] For a target mine data, the number of monitoring periods in the historical monitoring period whose risk factor is greater than or equal to the preset risk factor is detected, and the historical accident rate = the number of monitoring periods in which the risk factor is greater than or equal to the preset risk factor / the number of historical monitoring periods, where the historical monitoring period is all the monitoring periods before the current monitoring period, and the number of historical monitoring periods is the number of all monitoring periods before the current monitoring period.

[0067] The values ​​of the preset danger coefficient and the preset historical accident rate can be determined according to the actual application scenario. The greater the user's demand for timely transmission of danger information to the node, the smaller the values ​​of the preset danger coefficient and the preset historical accident rate. A value of a preset danger coefficient and a preset historical accident rate is provided. The method for confirming the preset danger coefficient is to detect the danger coefficient corresponding to the records with the same data source as the target mine data in the historical monitoring period, and record the average value of the danger coefficient that can meet the user's needs as the preset danger coefficient. The preset historical accident rate is 70%.

[0068] The data processing status includes: the mine data reference value is greater than or equal to the preset mine data reference value or the node processing reference value is less than the preset node processing reference value, and the mine data reference value is less than the preset mine data reference value and the node processing reference value is greater than or equal to the preset node processing reference value.

[0069] When the data processing status is that the mine data reference value is greater than or equal to the preset mine data reference value or the node processing reference value is less than the preset node processing reference value, the analysis method is determined according to the proportion of the first type of data and the second type of data is allocated to the node with the largest node processing reference value;

[0070] When the data processing status is that the mine data reference value is less than the preset mine data reference value and the node processing reference value is greater than or equal to the preset node processing reference value, the processing order is determined according to the priority coefficient of each target mine data and the node corresponding to the shortest reference distance is selected for transmission.

[0071] The mine data reference value is the total amount of target mine data generated in a single cycle, in GB. The node processing reference value is the difference between the maximum amount of data that each node can process and the amount of data being processed by each node in a single monitoring cycle, in GB.

[0072] The values ​​of the preset mine data reference value and the preset node processing reference value can be set by the user according to the actual application scenario. The greater the user's demand for the stability of node use, the smaller the value of the preset mine data reference value and the larger the value of the preset node processing reference value. A preset mine data reference value and a preset node processing reference value are provided. The preset data reference value is 30GB. The method for confirming the preset processing reference value is to detect the node processing reference value corresponding to the record with the same mine data reference value in the historical monitoring cycle, and record the average value of the node processing reference value whose processing speed meets the user's requirements as the preset node processing reference value.

[0073] Specifically, the risk factor is determined based on the regional risk factor and the differential risk factor;

[0074] The relationship between the regional risk factor and the regional coefficient is a positive correlation;

[0075] The relationship between the difference risk coefficient and the difference index is a positive correlation.

[0076] Among them, the risk coefficient is positively correlated with the regional risk coefficient and the difference risk coefficient, respectively. An embodiment of the risk coefficient is provided, risk coefficient = regional risk coefficient + difference risk coefficient, regional risk coefficient = regional coefficient × α, difference risk coefficient = difference index × β, α is the risk reference value, α = 0.4, β is the difference reference value, β = 0.6.

[0077] Specifically, the regional coefficient is determined according to the mining intensity coefficient and the stratum disturbance coefficient, the mining intensity coefficient is positively correlated with the mining intensity, and the stratum disturbance coefficient is positively correlated with the stratum disturbance value;

[0078] The mining intensity is determined based on the ratio of the mining volume to the area of ​​the region;

[0079] The formation disturbance value is determined according to the maximum mining depth, and the relationship between the formation disturbance value and the maximum mining depth is a positive correlation.

[0080] Among them, the regional coefficient is positively correlated with the mining intensity coefficient and the formation disturbance coefficient respectively. An embodiment of the regional coefficient is provided, regional coefficient = mining intensity coefficient + formation disturbance coefficient, mining intensity coefficient = mining intensity × mining coefficient, mining coefficient is 0.5, mining intensity = mining volume / regional area, in the present invention, the mining area is divided into several mining areas of the same area, for a single mining area, the area is recorded as the target area, the mining volume is the amount of ore collected in the target area within the current monitoring period, the unit is t, the regional area is the area of ​​the target area, the unit is square meters, the formation disturbance coefficient = formation disturbance value × disturbance coefficient, the disturbance coefficient is 0.5, the formation disturbance value = l nH, H is the maximum mining depth, the maximum mining depth is the maximum depth of mining in the target area within the current monitoring period.

[0081] Specifically, the target mine data types include video data and environmental data, and the methods for determining the difference index corresponding to different target mine data types are different;

[0082] For a video data, the difference index is determined according to the abnormal feature proportion, and the relationship between the difference index and the abnormal feature proportion is a positive correlation;

[0083] For a piece of environmental data, the difference index is determined according to the data deviation degree, and the relationship between the difference index and the data deviation degree is a positive correlation.

[0084] Abnormal feature ratio = number of abnormal video frames / total number of video frames. Video frames with a personnel density greater than the preset personnel density or a device deviation distance greater than the preset device deviation distance or a deviation number reference value greater than the preset deviation number reference value are recorded as abnormal video frames. The number of abnormal video frames is the number of abnormal video frames in a single video data. The total number of video frames is the total number of video frames in a single video data. Personnel density = number of personnel in a single video frame / area of ​​the monitoring area corresponding to the monitoring device. The value of the preset personnel density can be determined according to the actual application scenario. The larger the value of the preset personnel density, the greater the probability that there are safety hazards in the monitoring area. A value of the preset personnel density is provided to detect the personnel density corresponding to the records with the same data source as the current target mine data in the historical monitoring period, and the average value of the personnel density whose safety situation meets user needs is recorded as the preset personnel density.

[0085] The target devices include but are not limited to excavators, tunneling machines, crushers, ball mills, flotation machines, and dryers. The target devices in the video frame can be identified by machine vision and deep learning networks. This is easy for technicians in this field to understand and will not be elaborated here. The device deviation distance is confirmed by identifying each target device in a single video frame, detecting the distance between the position of each target device and the preset area corresponding to the target device, and recording the maximum distance as the device deviation distance. The preset area corresponding to the target device is confirmed by, for a target device, detecting the position of the target device corresponding to the video data that can meet the user's needs in the historical monitoring cycle, and recording the area between the minimum circumscribed circles of each position as the preset area corresponding to the target device; the reference value of the deviation number is the number of target devices whose device deviation distance is greater than the preset device deviation distance.

[0086] The values ​​of the preset equipment deviation distance and the preset deviation quantity reference value can be determined according to the actual application scenario. The larger the values ​​of the preset equipment deviation distance and the preset deviation quantity reference value, the greater the probability that there are safety hazards in the monitoring area. Provide a value of the preset equipment deviation distance and the preset deviation quantity reference value, detect the equipment deviation distance corresponding to the record with the same data source as the current target mine data in the historical monitoring period, and record the average value of the equipment deviation distance whose safety situation meets user requirements as the preset equipment deviation distance. The preset deviation quantity reference value is 3.

[0087] The method for confirming the data deviation degree is to record a single environmental data as the target environmental data, record the historical data corresponding to the target environmental data without any safety accidents as the reference data, calculate the absolute value of the difference between the data average value corresponding to each reference data and the data average value corresponding to the target environmental data, and the average value of each absolute value of the difference is the data deviation degree.

[0088] Specifically, under the preset conditions, if the proportion of Class I data is greater than or equal to the preset proportion of Class I data, the Class I data with the same operation links are combined, and the combination of Class I data corresponding to each operation link and each Class II data are recorded as data to be transmitted. The transmission order of the data to be transmitted is determined according to the risk assessment value. For a single data to be transmitted, the node with the largest node processing reference value is selected for allocation;

[0089] The preset condition is that the data processing state is that the mine data reference value is greater than or equal to the preset mine data reference value or the node processing reference value is less than the preset node processing reference value.

[0090] The proportion of Category I data = the number of Category I data / reference value of mining data. The number of Category I data is the total amount of Category I data in the current monitoring period, in GB;

[0091] The value of the proportion of a preset category of data can be determined by the user according to the actual application scenario. The greater the user's demand for timely transmission of dangerous information to the node, the smaller the value of the proportion of a preset category of data. A value of the proportion of a preset category of data is provided, and the value of the proportion of a preset category of data is 60%.

[0092] The operation links include drilling, blasting, mining, transportation and soil discharge. The operation links in different mining areas may be different. The data of one category of mining areas with the same operation links in the current monitoring period are combined.

[0093] The hazard assessment value is positively correlated with the hazard coefficient and the historical accident rate, respectively. An embodiment of the hazard assessment value is provided, hazard assessment value = hazard coefficient × first coefficient + historical accident rate × second coefficient. It can be understood that the values ​​of the first coefficient and the second coefficient can be learned by the user through a deep learning convolutional neural network for historical records, so as to set the first coefficient and the second coefficient according to the importance of the user to the historical records, wherein the first coefficient + the second coefficient = 1. The values ​​of the first coefficient and the second coefficient are provided, and the first coefficient is 0.5 and the second coefficient is 0.5.

[0094] Specifically, under preset conditions, if the proportion of one type of data is less than the preset proportion of one type of data, all the one type of data will be combined, and the two types of data will be combined according to the proportion of the same characteristics and the correlation coefficient. According to the risk factor, each data combination and the two types of data that are not recorded as data combinations will be transmitted to the corresponding node for processing, and the node with the largest reference value will be transmitted.

[0095] The method for confirming the proportion of the same features is to detect each feature appearing in each video data for two video data. The features include personnel and target devices. The features can be identified by machine vision and deep learning network. This is easy to understand for those skilled in the art and will not be elaborated here. The proportion of the same features = the number of the same features in the two video data / the larger value of the number of features in the two video data;

[0096] For two environmental data, the calculation formula of the correlation coefficient Q is:

[0097]

[0098] The starting data corresponding to a single environmental data is taken as the starting point, and an interval point is set every 1s in time sequence, and the starting point and all interval points are recorded as time points. If the number of time points of two environmental data is different, data preprocessing is required to make the number of time points of the two environmental data the same. The data preprocessing includes: comparing the number of time points of the two environmental data, recording the number of time points corresponding to the environmental data with a smaller number of time points as the reference number of time points, and in the environmental data with a larger number of time points, starting from the first time point, retaining the time points equal to the reference number of time points, deleting the data values ​​corresponding to all time points exceeding the reference number of time points, and recording the environmental data that has undergone data preprocessing as preprocessed environmental data;

[0099] In the calculation formula of the correlation coefficient Q, n is the number of time points in a single preprocessing environment data; x i and i are the data values ​​corresponding to the i-th time point in the two preprocessed environment data, For x i The corresponding average value of the pre-processed environment data, for y i The average value of the corresponding pre-processing environment data, i = 1, 2, 3, ..., n; x i The corresponding average value of the preprocessing environment data The calculation formula is: y i The corresponding average value of the preprocessing environment data The calculation formula is:

[0100] Specifically, a combined analysis is performed on the two types of data based on the proportion of the same features and the correlation coefficient:

[0101] When performing combined analysis on a single second-category data, the second-category data is recorded as the target second-category data, and other data not including the target second-category data is recorded as the reference second-category data.

[0102] If the target second-category data is video data, the video data corresponding to the reference second-category data are combined according to the proportion of the same features, and the video data corresponding to the reference second-category data whose proportion of the same features as the target second-category data is greater than the preset proportion of the same features and the target second-category data are uniformly recorded as one data combination;

[0103] If the target second-category data is environmental data, the environmental data corresponding to the reference second-category data are combined according to the correlation coefficient, and the environmental data corresponding to the reference second-category data whose correlation coefficient with the target second-category data is greater than the preset correlation coefficient and the target second-category data are uniformly recorded as one data combination;

[0104] After the combination analysis of the target second category data is completed, the combination analysis is continued for the reference second category data that is not recorded as a data combination.

[0105] The values ​​of the preset proportion of the same features and the preset correlation coefficient can be determined by the user according to the actual application scenario. The larger the values ​​of the preset proportion of the same features and the preset correlation coefficient are, the greater the correlation between the two types of data in the data combination is. A value of the preset proportion of the same features and the preset correlation coefficient is provided, and the preset proportion of the same features is 70%, and the preset correlation coefficient is 0.8.

[0106] Specifically, when the data processing status is that the mine data reference value is less than the preset mine data reference value and the node processing reference value is greater than or equal to the preset node processing reference value, the processing order is determined according to the priority coefficient of each target mine data, and the node corresponding to the shortest reference distance is selected for transmission;

[0107] The priority coefficient of the target mine data is positively correlated with the risk assessment value.

[0108] The priority coefficient of the target mine data = risk assessment value × η, where η is the assessment coefficient and its value is 0.8. The processing order is from large to small priority coefficients. The target mine data with large priority coefficients are transmitted first, and the target mine data with large risk assessment values ​​are transmitted to the node in a timely manner.

[0109] The shortest reference distance is confirmed by, for a data source, detecting the shortest distance between each node and the data source, and recording the minimum value of the shortest distances as the shortest reference distance.

[0110] Specifically, for the target mine data corresponding to the data combination, the encryption method is to encrypt the target mine data once using an encryption algorithm, and to encrypt the mine data ciphertext combination corresponding to each target mine data twice using an encryption algorithm;

[0111] For target mine data that is not recorded as a data combination, the encryption method is to encrypt the target mine data once using an encryption algorithm.

[0112] The encryption algorithm may be, but is not limited to, AES, RSA or ECC. The encryption algorithms used for the primary encryption and the secondary encryption may be the same or different, and the user may select them according to the encryption requirements. The mining data ciphertext combination is a combination of ciphertexts formed after the target mining data is encrypted once using an encryption algorithm.

[0113] See also Figure 4 As shown, it is a module connection diagram of the blockchain-based mine data security transmission system of the present invention. The present invention also provides a blockchain-based mine data security transmission system, including:

[0114] Data acquisition module, used to collect target mine data;

[0115] A data processing module, which is connected to the data acquisition module, is used to determine the data type according to the risk factor of the target mine data and the historical accident rate, and to determine the data processing state according to the mine data reference value and the node processing reference value;

[0116] A data transmission module, connected to the data processing module, for determining a data transmission mode according to a data processing state;

[0117] A combined analysis module, which is connected to the data processing module and the data transmission module, and is used to determine an analysis method according to the proportion of a type of data;

[0118] The data encryption module is connected to the data transmission module and the combination analysis module, and is used to determine whether the encryption method is one-time encryption or two-time encryption according to whether the target mine data is recorded as a data combination.

[0119] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0120] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for secure transmission of mine data based on blockchain, characterized in that: include: Determine the data type based on the risk factor of the target mine data and the historical accident rate; Determine the data processing status according to the mine data reference value and the node processing reference value; Determine the data transmission mode according to the data processing status: determine the analysis mode according to the proportion of the first type of data and distribute the second type of data to the node with the largest node processing reference value, or determine the processing order according to the priority coefficient of each target mine data and select the node corresponding to the shortest reference distance for transmission; Determine the analysis method based on the proportion of a type of data, which is to combine the data of the same type of operation links or to combine all the data of the same type; When combining the first-class data with the same operation links, the first-class data combination corresponding to each operation link and each second-class data are transmitted to the corresponding node processing node with the largest reference value according to the risk factor; When all the first-class data are combined, the second-class data are combined according to the proportion of the same characteristics and the correlation coefficient, and each data combination and the second-class data not recorded as a data combination are transmitted to the corresponding node processing node with the largest reference value according to the risk coefficient; The encryption method is determined to be single encryption or double encryption according to whether the target mine data is recorded as a data combination.

2. The method for secure transmission of mine data based on blockchain according to claim 1 is characterized in that: The risk factor is determined based on the regional risk factor and the differential risk factor; The relationship between the regional risk factor and the regional coefficient is a positive correlation; The relationship between the difference risk coefficient and the difference index is a positive correlation.

3. The method for secure transmission of mine data based on blockchain according to claim 2 is characterized in that: The regional coefficient is determined according to the mining intensity coefficient and the stratum disturbance coefficient, the mining intensity coefficient is positively correlated with the mining intensity, and the stratum disturbance coefficient is positively correlated with the stratum disturbance value; The mining intensity is determined based on the ratio of the mining volume to the area of ​​the region; The formation disturbance value is determined according to the maximum mining depth, and the relationship between the formation disturbance value and the maximum mining depth is a positive correlation.

4. The method for secure transmission of mine data based on blockchain according to claim 2 is characterized in that: The target mine data types include video data and environmental data, and the methods for determining the difference index corresponding to different target mine data types are different; For a video data, the difference index is determined according to the abnormal feature proportion, and the relationship between the difference index and the abnormal feature proportion is a positive correlation; For a piece of environmental data, the difference index is determined according to the data deviation degree, and the relationship between the difference index and the data deviation degree is a positive correlation.

5. The method for secure transmission of mine data based on blockchain according to claim 4 is characterized in that: Under the preset conditions, if the proportion of Class I data is greater than or equal to the preset proportion of Class I data, the Class I data with the same operation links are combined, and the combination of Class I data corresponding to each operation link and each Class II data are recorded as data to be transmitted. The transmission order of the data to be transmitted is determined according to the risk assessment value. For a single data to be transmitted, the node with the largest node processing reference value is selected for allocation; The preset condition is that the data processing state is that the mine data reference value is greater than or equal to the preset mine data reference value or the node processing reference value is less than the preset node processing reference value.

6. The method for secure transmission of mine data based on blockchain according to claim 5 is characterized in that: Under the preset conditions, if the proportion of one type of data is less than the preset proportion of one type of data, all the one type of data will be combined, and the two types of data will be combined according to the proportion of the same characteristics and the correlation coefficient. According to the risk factor, each data combination and the two types of data that are not recorded as data combinations will be transmitted to the corresponding node for processing, and the node with the largest reference value will be transmitted.

7. The method for secure transmission of mine data based on blockchain according to claim 6 is characterized in that: Combined analysis of the two types of data is performed based on the proportion of the same features and the correlation coefficient: When performing combined analysis on a single second-category data, the second-category data is recorded as the target second-category data, and other data not including the target second-category data is recorded as the reference second-category data. If the target second-category data is video data, the video data corresponding to the reference second-category data are combined according to the proportion of the same features, and the video data corresponding to the reference second-category data whose proportion of the same features as the target second-category data is greater than the preset proportion of the same features and the target second-category data are uniformly recorded as one data combination; If the target second-category data is environmental data, the environmental data corresponding to the reference second-category data are combined according to the correlation coefficient, and the environmental data corresponding to the reference second-category data whose correlation coefficient with the target second-category data is greater than the preset correlation coefficient and the target second-category data are uniformly recorded as one data combination; After the combination analysis of the target second-category data is completed, the combination analysis is continued for the reference second-category data that is not recorded as a data combination.

8. The method for secure transmission of mine data based on blockchain according to claim 7 is characterized in that: When the data processing status is that the mine data reference value is less than the preset mine data reference value and the node processing reference value is greater than or equal to the preset node processing reference value, the processing order is determined according to the priority coefficient of each target mine data, and the node corresponding to the shortest reference distance is selected for transmission; The priority coefficient of the target mine data is positively correlated with the risk assessment value.

9. The method for secure transmission of mine data based on blockchain according to claim 8 is characterized in that: For the target mine data corresponding to the data combination, the encryption method is to encrypt the target mine data once using an encryption algorithm, and to encrypt the mine data ciphertext combination corresponding to each target mine data twice using an encryption algorithm; For target mine data that is not recorded as a data combination, the encryption method is to encrypt the target mine data once using an encryption algorithm.

10. A transmission system using the blockchain-based mine data security transmission method according to any one of claims 1 to 9, characterized in that: include: Data acquisition module, used to collect target mine data; A data processing module, which is connected to the data acquisition module, is used to determine the data type according to the risk factor of the target mine data and the historical accident rate, and to determine the data processing state according to the mine data reference value and the node processing reference value; A data transmission module, connected to the data processing module, for determining a data transmission mode according to a data processing state; A combined analysis module, which is connected to the data processing module and the data transmission module, and is used to determine an analysis method according to the proportion of a type of data; The data encryption module is connected to the data transmission module and the combination analysis module, and is used to determine whether the encryption method is one-time encryption or two-time encryption according to whether the target mine data is recorded as a data combination.

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