A data security communication method based on a smart meter

Abstract

The application discloses a kind of based on smart meter data security communication method, it is related to communication control technical field, including: obtaining the basic data information of smart meter, preliminary check is carried out, and generate pending queue;According to the basic data information, each smart meter is divided into degree of classification, and setting same row mechanism is verified to the smart meter in pending queue, and generate interim queue;According to the degree of classification of different smart meters in the interim queue, set difference verification, and the smart meter that is verified is added to end queue;The data information corresponding to the smart meter in end queue is obtained and is parsed, and the meter data after parsing is stored;Through multistage check and verification mechanism, the authenticity and legality of smart meter data are ensured, the efficiency and flexibility of data processing are improved, the effect of optimizing data processing procedure, improving data processing efficiency and flexibility is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of communication control, and in particular to a data security communication method based on a smart meter. BACKGROUND

[0002] At present, the data storage security of a smart meter is a problem to be solved. After the smart meter monitors the user's power consumption data, the data needs to be transmitted to a meter data receiving platform for data analysis and storage. However, the data security of the meter data receiving platform is more based on the legality of the data source. When judging the legality of the data source, the traditional method is to first analyze the data, then extract the data source information, and if the data source information is consistent with the pre-stored data, it is considered that the data source is legal. However, if the data is analyzed first, if the data received by the meter data receiving platform is set with a monitoring program, once the data is analyzed first, it may be forced to analyze the monitoring program or illegal intrusion data, resulting in that the security of the meter data receiving platform cannot be guaranteed, and it may also lead to the leakage of the data stored in the meter data receiving platform.

[0003] The Chinese invention patent with application number 202410979260.1 provides a communication control method based on smart meter data transmission. Based on the position information and bandwidth threshold information, the corresponding first private key and second private key are obtained, and the third private key is generated. When the meter data receiving platform receives the meter data transmitted by the smart meter, the first public key, the second public key and the third public key are called in turn, and whether to analyze the received meter data is judged according to the first private key, the second private key and the third private key in turn, so as to ensure the security of analyzing the smart meter data.

[0004] However, in the existing patent technology, three times of comparison verification are set to improve the security, but at the same time, the complexity of data processing is increased, the data processing time is increased, the data processing efficiency is reduced, and the use of fixed verification level to deal with all meter data leads to reduced flexibility and resource waste. SUMMARY

[0005] The present application provides a data security communication method based on a smart meter, which solves the problem of reduced data processing efficiency and flexibility in the prior art, and achieves the technical effect of improving data processing efficiency and flexibility.

[0006] The present application provides a data security communication method based on a smart meter, which includes:

[0007] S100: Obtain the basic data information, location information and bandwidth threshold information of the smart meter, perform preliminary verification and check, and generate a to-be-processed queue; according to the basic data information, divide the level of each smart meter, set the same row mechanism to check the smart meter in the to-be-processed queue, and generate a medium-term queue;

[0008] S200: According to the level of different smart meters in the medium-term queue, set up a difference verification, and add the smart meters that pass the verification to the final queue;

[0009] S300: Obtain the data information corresponding to the smart meter in the final queue and perform analysis, store the analyzed meter data; real-time monitor steps S100 and S200, timely alarm the abnormal conditions, and generate an abnormal report information.

[0010] Further, the basic data information includes the unique code, historical data record and data importance of the smart meter; the level includes low, medium and high, and the level is dynamically verified and divided according to the basic data information and real-time data information of data transmission.

[0011] Further, the same row mechanism is to send a same row query request to a plurality of storage lists, perform key verification, judge whether there is a permission for analysis and reception, if there is a permission, add to the medium-term queue.

[0012] Further, the check verification is to generate a first private key and a second private key based on the location information and bandwidth threshold information of the smart meter in the to-be-processed queue, generate a corresponding first public key and second public key, generate a third private key of the smart meter based on the first private key and the second private key, and generate a third public key based on the third private key, obtain the real-time bandwidth information when the smart meter transmits data to the meter data receiving platform, generate a fourth private key based on the real-time bandwidth information, and generate a fourth public key based on the fourth private key; call the first public key, the second public key, the third public key and the fourth public key in turn, and judge whether there is a permission for analysis and reception according to the first private key, the second private key, the third private key and the fourth private key in turn.

[0013] Further, the difference verification is to set different key verification methods and verification processes according to different levels, and set different encryption verification methods for smart meters of different levels.

[0014] Further, the to-be-processed queue, the medium-term queue and the final queue respectively refer to the collection of smart meters and corresponding data information that pass the verification at different periods.

[0015] Further, the same mechanism further comprises a cache management strategy, the cache management strategy is obtained by monitoring the query frequency and usage mode of the public key in real time, the frequency degree, the frequency degree threshold is set in advance, the public key with the frequency degree greater than the frequency degree threshold is cached, and the cache area is set based on the level of the smart meter, and the size of the cache area is adjusted according to the real-time monitoring data, and the cache time is adjusted in real time; the cache management strategy further comprises a prefetch mechanism, the prefetch mechanism is based on a basic prediction model to judge the usage trend of the public key, and the public key needed in the future time period is preloaded into the cache.

[0016] Further, the method further comprises S400: setting a dynamic line mechanism, dynamically adjusting the priority of the verification task based on real-time data flow and load condition, sorting the verification task according to the public key query frequency, and dynamically adjusting the verification process combined with the level of the smart meter.

[0017] Further, the method further comprises: S500: monitoring steps S100 and S200 in real time, and generating a stage trust value for the smart meter according to the monitoring data, obtaining a total trust value according to the stage trust value, establishing a trust chain according to the total trust value, generating a trust code based on the trust chain, and directly joining the end queue after the trust code verification is passed.

[0018] Further, the stage trust value is generated according to the data verification process of the smart meter in the initial queue, the middle queue and the end queue, and a trust threshold is set in each stage, if the stage trust value of any stage is lower than the trust threshold, the subsequent trust judgment is cancelled.

[0019] One or more technical solutions provided in the application have at least the following technical effects or advantages:

[0020] Through the multi-level verification and checking mechanism, the authenticity and legality of the smart meter data are ensured, the smart meter data is processed according to the level division and the same mechanism, the efficiency and flexibility of data processing are improved, and the effects of optimizing data processing flow, improving data processing efficiency and flexibility are realized. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1 It is a whole flow schematic diagram of a data security communication method based on a smart meter in the embodiments of the application. DETAILED DESCRIPTION

[0022] For the purpose of facilitating the understanding of the present application, a more complete description of the application will be provided below with reference to the accompanying drawings, in which the preferred embodiments of the present application are given; however, the present application can be realized in many different forms and is not limited to the embodiments described herein; on the contrary, these embodiments are provided for the purpose of making the disclosure of the present application more thorough and comprehensive.

[0023] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs; the terms used herein in the specification of the present application are only for the purpose of describing the specific embodiments and are not intended to limit the present application; the term "and / or" used herein includes any and all combinations of one or more related listed items.

[0024] Embodiment one: as shown, a data security communication method based on a smart meter, the method comprising: Figure 1

[0025] S100: obtaining basic data information, location information and bandwidth threshold information of the smart meter, performing preliminary verification and checking, and generating a to-be-processed queue; dividing the level of each smart meter according to the basic data information, setting a same-row mechanism to check the smart meters in the to-be-processed queue, and generating an interim queue.

[0026] The basic data information includes a unique code, historical data records and data importance of the smart meter; the level includes low, medium and high, and the level is dynamically verified and divided according to the basic data information and real-time data information of data transmission.

[0027] ​In some embodiments, the smart meter transmits the meter data, including basic data information, location information and bandwidth threshold information, to the meter data receiving platform after encryption. After receiving the data, the meter data receiving platform performs preliminary format verification and integrity check, generates a to-be-processed queue, and sets a same-line mechanism to check the smart meter in the to-be-processed queue. The same-line mechanism sends a same-line query request to a plurality of storage lists, performs key verification, judges whether there is a permission to parse and receive, and if there is a permission, joins an intermediate queue. The query request is obtained by acquiring the location information and bandwidth threshold information of the smart meter in the to-be-processed queue, generating a first private key based on the location information, generating a first public key based on the first private key, generating a second private key based on the bandwidth threshold information, generating a second public key based on the second private key, generating a third private key of the smart meter based on the first private key and the second private key, and generating a third public key based on the third private key. Real-time bandwidth information when the smart meter transmits data to the meter data receiving platform is acquired, a fourth private key is generated based on the real-time bandwidth information, and a fourth public key is generated based on the fourth private key. When the meter data receiving platform receives the meter data transmitted by the smart meter, the first public key, the second public key, the third public key and the fourth public key are called in turn, and whether there is a permission to parse and receive is judged according to the first private key, the second private key, the third private key and the fourth private key in turn. If there is a permission, join the intermediate queue.

[0028] In some embodiments, the same-line mechanism uses a parallel processing verification method. The meter data receiving platform simultaneously sends a query request to a plurality of storage lists, queries respectively, each storage list processes the query request in parallel, and returns the query result at the same time. The meter data receiving platform quickly judges the existence of the public key according to the query result. If all public keys exist, prepare the corresponding confirmation instruction. If any public key does not exist, prepare the non-parsing instruction and feed back the abnormal information. Specifically, the thread pool is used to manage the parallel verification task, the number of threads is dynamically adjusted according to the system load, and resource overload is avoided. For frequently queried public keys, a temporary cache is established in some embodiments to reduce the number of repeated queries. At the same time, the timeout time of the query request is set. For the timeout request, automatic retry or marking as abnormal processing is performed.

[0029] In some embodiments, the data transmission real-time data information refers to real-time data generated in the data transmission process, while combining the basic data information to jointly adjust the verification classification level, the basic data information includes the unique code of the smart meter, which is used to identify the smart meter and distinguish the characteristics of the data information; according to the historical data record including the historical security record and the historical abnormal record, specifically including the number of abnormal records, the reason, the solution and the history of being attacked; the data importance refers to the user type, the data sensitivity and the like; the real-time data is the current resource status of the system, such as the current usage rate of the system, the memory occupation rate and the like; the level degree includes low level, middle level and high level, when classifying the level of different smart meters and transmitted data information, on the one hand, it depends on the historical record information to judge, and on the other hand, it is comprehensively judged according to the importance of the current data, the importance of the data is different in different actual scene applications, and the important judgment standard of the data is different, which can be comprehensively judged according to the actual situation combined with the data; the low level refers to the good historical record, for example, the historical abnormal record is less than three times, the data importance is low, and the system CPU usage rate is more than 80% or the memory occupation rate is more than 70%, for the low level data information, the corresponding verification process is simplified, and the verification step is reduced, here the data importance is low is comprehensively judged according to the actual situation and the historical transmission data of the smart meter; the middle level is suitable for the middle standard, and the standard verification process is executed to ensure the data security, for example, the corresponding historical abnormal record is between 3-10 times, the data importance is medium or high, and the system resource status is moderate; the high level is suitable for the case that the historical record is not good, the data is critical or the system resource is sufficient, additional verification steps are increased, for example, the number of historical abnormal records is more than 10 times, the data importance is high, and the system resource status is good; according to the dynamically adjusted verification level, the corresponding confirmation instruction or non-analysis instruction is sent to the smart meter.

[0030] In some embodiments, since the location information of the smart meter is determined as soon as it is installed, the location information can be actively updated by human beings during the normal operation of the smart meter. When the location information of the smart meter is adjusted, the updated location information needs to be actively reported, and the first private key is regenerated, and the first public key corresponding to the first private key is regenerated by using the regenerated first private key. If there is a human uncontrollable location change, the location information of the smart meter is updated periodically according to a pre-set period. That is, the location information of the smart meter is obtained every first specified time, and if an adjustment location instruction is received, the location information of the smart meter is actively obtained after the location of the smart meter is adjusted, and the location information of the smart meter is obtained every second specified time. The first specified time is less than the second specified time. The first specified time should not be too long, and is set according to actual needs, such as 12 hours, 8 hours or 6 hours, etc. The second specified time can be set to be longer than the first specified time, such as 24 hours, 48 hours or 72 hours, etc.

[0031] In some embodiments, since the smart meter is installed and connected to the user power consumption data to be monitored after the installation is completed, if the bandwidth threshold information of the smart meter transmitting data to the meter data receiving platform is fixed, the smart meter can directly monitor when the smart meter is controlled by an illegal intrusion instruction to send high-bandwidth meter data to the meter data receiving platform. Therefore, in this embodiment, the bandwidth threshold information of the smart meter transmitting data to the meter data receiving platform cannot be adjusted after the installation of the smart meter is completed. If it is desired to adjust the number and range of users monitored by the smart meter, a separate authorization instruction is required, which needs to be adjusted offline on site of the smart meter. Remote operation is generally not allowed unless a separate instruction security protection scheme is set to allow remote operation.

[0032] Specifically, for all private keys, they are stored in the smart meter body after being generated, and the public keys are stored in the meter data receiving platform to enable normal communication between the smart meter and the meter data receiving platform. In this embodiment, since the instruction transmission and reception between the smart meter and the meter data receiving platform is required, the first private key, the second private key and the third private key in this embodiment are stored in the first storage list of the smart meter, the first public key is stored in the second storage list of the meter data receiving platform, the second public key is stored in the third storage list of the meter data receiving platform, and the third public key is stored in the fourth storage list of the meter data receiving platform.

[0033] S200: According to the level difference verification of different smart meters in the intermediate queue, the smart meters that pass the verification are added to the final queue.

[0034] The difference verification is set different key verification modes and verification processes according to different levels, and different encryption verification modes are set for smart meters of different levels. Specifically, for low-level smart meters, a simplified verification process is adopted to reduce verification steps and complexity and improve verification speed; for medium-level smart meters, a standard verification process is executed to ensure data security while maintaining verification efficiency; for high-level smart meters, additional verification steps and more stringent verification modes such as multiple encryption and two-way verification are added to ensure high security of data. According to the level of the smart meter, the corresponding verification mode and process are selected for verification, and the smart meter that passes the verification is added to the end queue for subsequent data analysis and storage. In this application, the to-be-processed queue, the intermediate queue and the end queue respectively refer to the collection of smart meters and their corresponding data information that pass the verification at different stages. The end queue includes smart meter basic data information and verification information, including public key, verification time, verification mode and other verification-related information, and also includes keys and parsing rules corresponding to data information of different levels.

[0035] S300: Obtain the data information corresponding to the smart meter in the end queue and perform parsing, and store the parsed meter data; real-time monitor steps S100 and S200, and timely alarm for abnormal conditions and generate abnormal report information.

[0036] The abnormal report information includes information such as the node where the abnormality occurs, the type of abnormality, the time of occurrence, and the related smart meter, and is sent to an alarm terminal or system administrator for subsequent processing.

[0037] In this embodiment, by dividing the level of each smart meter according to the basic data information, the same mechanism is set to check the smart meters in the to-be-processed queue, and different important degrees of smart meters are processed differently through level division; the same mechanism increases the accuracy and reliability of data processing.

[0038] The technical solutions in the above embodiments of the application have at least the following technical effects or advantages:

[0039] The application ensures the authenticity and legality of smart meter data through multi-level verification and checking mechanism, processes smart meter data according to level division and same mechanism, improves the efficiency and flexibility of data processing, and achieves the effects of optimizing data processing flow, improving data processing efficiency and flexibility.

[0040] Embodiment Two: In Embodiment One, level division and same mechanism are set to further improve the efficiency and flexibility of data processing, and this embodiment further improves the above embodiment.

[0041] In order to further improve the data processing efficiency during the legal verification, the public key to be verified is cached by setting a cache area. In the verification process, the meter data receiving platform caches the frequently queried public key information in the local or distributed cache system. In the subsequent verification, it is first checked whether the required public key information exists in the cache. If it exists, it is directly obtained from the cache to avoid database access. If it does not exist, the database is queried and the cache is updated. The database mentioned here is the total storage location of all storage lists in the above embodiments. At the same time, the expired or invalid public key information in the cache needs to be cleaned up regularly to maintain the effectiveness and efficiency of the cache. The present embodiment further improves the above content to further improve the data processing efficiency.

[0042] The same line mechanism also includes a cache management strategy. The cache management strategy is obtained by real-time monitoring of the query frequency and usage mode of the public key, the frequency degree, pre-setting the frequency degree threshold, caching the public key with a frequency degree greater than the frequency degree threshold, and setting the cache area based on the level of the smart meter. At the same time, the size of the cache area is adjusted according to the real-time monitoring data, and the cache time is adjusted in real time.

[0043] The cache management strategy also includes a prefetch mechanism. The prefetch mechanism is based on a basic prediction model to judge the usage trend of the public key, and preloads the public key needed in the future time period into the cache.

[0044] In some embodiments, the cache management strategy refers to a strategy for temporarily storing and managing frequently queried public keys or verification results during the same line mechanism verification of smart meter data in order to improve verification efficiency and reduce the number of repeated queries. The frequency degree is obtained by real-time monitoring of the query frequency and usage mode of the public key. The frequency degree is not only the query frequency, but also a comprehensive value of the query frequency and usage mode. The method of obtaining the comprehensive value can use the weighted summation method. First, normalize the two data to be in the same dimension, and then perform weighted summation to obtain the frequency degree.

[0045] In some embodiments, the usage mode refers to different encryption verification methods. In the above embodiments, different levels of smart meters use different degrees of encryption. For example, low-level smart meters use ordinary encryption, and high-level smart meters use double encryption to further improve encryption security. Different encryption verification methods have different usage modes for public keys. According to different usage modes and specific query frequencies, the frequency degree is obtained. The frequency degree threshold is pre-set according to historical data analysis and system performance requirements. When the frequency degree of a public key exceeds the frequency degree threshold, the public key is considered to be a high-frequency public key and is stored in the cache area for cache management.

[0046] In some embodiments, the cache management strategy sets the cache area according to the level of the smart meter, and also needs to adjust the size of the cache area and the cache time according to real-time monitoring data. For example, for high-frequency public keys, a high-frequency cache area is set to store these public keys and their corresponding data or verification results; a dedicated cache area is set for high-level smart meters to store their commonly used data and verification results, with a longer cache time; a medium-sized cache area is set for medium-level smart meters, with a moderate cache time; a smaller cache area is set for low-level smart meters, with a shorter cache time, or only the latest query result is cached; the specific cache time is set or adjusted according to the actual public key change time frequency. The query frequency and usage mode of the public key are monitored, and when the frequency of a certain public key drops below the frequency threshold, it is moved from the high-frequency cache area to the cache area corresponding to the level, and the size of each cache area and the cache time are dynamically adjusted according to the system load and cache hit rate.

[0047] In this embodiment, when receiving a data request of a smart meter, the smart cache is first queried. If there is no corresponding data in the cache, parallel verification is performed according to the same mechanism, and the verification result is stored in the cache area of the corresponding level. For high-frequency public keys, the high-frequency cache area is queried first to improve query efficiency. Real-time monitoring of key indicators such as cache hit rate, database access times, and system response time is performed, and parameters such as frequency threshold, cache area size, and cache time are adjusted periodically according to the monitoring results to optimize system performance.

[0048] In some embodiments, to further implement an efficient cache replacement strategy, LRU (Least Recently Used) and LFU (Least Frequently Used) strategies are selected for comprehensive use. LRU is a recently least used strategy, if a data has been accessed recently, the probability of future access is also high; on the contrary, the recently least accessed data has a relatively low probability of future access. Therefore, when the cache space is insufficient, the LRU algorithm selects the recently least accessed data for eviction to make room for new data; LFU is a least frequently used strategy, which is different from LRU. LFU algorithm considers the frequency of data access, not the time of recent access. If a data is rarely accessed, the probability of future access is also low; on the contrary, frequently accessed data has a relatively high probability of future access. Therefore, when the cache space is insufficient, the LFU algorithm selects the data with the lowest access frequency for eviction.

[0049] In some embodiments, the cache management strategy further comprises a prefetch mechanism, which is based on a basic prediction model to judge the usage trend of the public key and preloads the public key needed in the future time period into the cache; the basic prediction model is established based on a time series prediction algorithm, specifically: collecting historical query data of the public key, including query time, public key ID, etc., cleaning and preprocessing the data, such as removing outliers and filling missing values, sorting the data according to time series, and dividing into training set and test set; extracting features of the time series, such as timestamp, query frequency, periodicity, etc., which can use sliding window technology to construct features, i.e. using query data in a period of time as input features and the next period of query data as output labels; constructing an LSTM neural network model, including an input layer, an LSTM layer, a fully connected layer and an output layer, the input layer receives time series features, the LSTM layer is used to capture long-term dependencies of time series, the fully connected layer is used to map the output of the LSTM layer to the predicted value, and the output layer outputs the prediction result; using the training set data to train the LSTM model, selecting mean square error as the loss function, using Adam optimization algorithm to optimize the model parameters, and through iterative training, the prediction error of the model on the training set is gradually reduced; using the test set data to evaluate the trained model, calculating prediction accuracy, mean square error and other indicators to evaluate the performance of the model; deploying the trained LSTM model to intelligent cache management for real-time prediction of public key query demand, and according to the prediction result, querying and caching related public keys from the database in advance to reduce future query delay.

[0050] In some embodiments, the future time period is pre-set according to historical data and experimental verification and adjusted in real time, representing a time node at which the used public key will change, and the historical query data of the public key is analyzed according to the basic prediction model to predict the possible query demand in the future period of time; it is easy to understand that the meaning of a period of time and the future time period is consistent, and the specific time range needs to be set according to the actual situation. According to experimental results, the length of the time range should match the time node at which the public key changes significantly.

[0051] In this embodiment, by caching frequently queried public key information, the number of database accesses is reduced, and the query efficiency is significantly improved; the prefetch mechanism is set to further reduce the query delay and improve the response speed of the system; the size and cache time of the cache area are dynamically adjusted, and the cache space is managed individually according to the frequency of the public key and the level of the smart meter, improving the use efficiency of the cache space; LRU and LFU strategies are used comprehensively to realize intelligent cache replacement and avoid waste of cache space.

[0052] The technical solutions in the embodiments of the present application have at least the following technical effects or advantages:

[0053] The present application further improves the data access processing efficiency by setting the cache area and the cache management strategy. The pre-fetch mechanism is set, and the size and the cache time of the cache area are dynamically adjusted, so that the fast verification and the improvement of the cache space utilization efficiency are achieved.

[0054] Embodiment three: The above-mentioned embodiments further improve the data access processing efficiency by setting the cache area and the cache management strategy. The present embodiment is further improved on the basis of the above-mentioned content.

[0055] The method further includes S400: setting a dynamic thread mechanism, dynamically adjusting the priority of the verification task based on real-time data traffic and load conditions, sorting the verification task according to the public key query frequency, and dynamically adjusting the verification process in combination with the level of the smart meter.

[0056] In some embodiments, the priority of the verification task is dynamically adjusted based on real-time data traffic and system load. The priority of the verification task is determined according to real-time data traffic, system load, public key query frequency, and the level of the smart meter, and is used to determine which verification task should be processed first. When the data traffic is large or the system load is high, the key task is processed first, such as the data verification of the high-level smart meter, to ensure the safety and timeliness of the data. The verification task is sorted according to the public key query frequency. The verification task corresponding to the high-frequency public key is processed first to reduce the number of database accesses and improve the query efficiency. The verification process is dynamically adjusted in combination with the level of the smart meter, specifically including: first determining the level of the smart meter to be verified, setting a basic verification process for all meters according to the level, including necessary verification steps and verification methods, simplifying the verification process for low-level smart meters, and increasing additional verification steps and more stringent verification methods for high-level smart meters. The complexity and strictness of the verification process are dynamically adjusted according to the system load and real-time demand.

[0057] In some embodiments, when receiving a data request of a smart meter, the priority and order of the verification task are first determined according to the dynamic thread mechanism. For tasks with high priority, such as verification corresponding to high-frequency public keys or data verification of high-level smart meters, system resources are preferentially allocated for processing. For tasks with low priority, such as data verification of low-level smart meters or query of low-frequency public keys, processing can be delayed or combined to reduce the occupation of system resources.

[0058] In some embodiments, the execution of the verification task and the system performance indicators such as verification speed, cache hit rate, database access times, etc. are monitored in real time, and according to the monitoring results, the parameters of the dynamic thread construction mechanism are dynamically adjusted, such as priority threshold, task sorting rules, etc. to optimize the system performance. The priority threshold is a limit value for dividing tasks of different priorities, and one or more priority thresholds are set according to the system load, data traffic and the importance of the verification task to distinguish high-priority and low-priority tasks. The task sorting rule is a rule for determining the processing order of the verification task, and the task sorting rule is set according to factors such as public key query frequency, smart meter level, data importance, etc. such as sorting by priority from high to low, sorting by public key query frequency from high to low, etc.

[0059] In some embodiments, the dynamic thread construction mechanism is combined with the cache management strategy to improve data processing efficiency. The cache management strategy provides data support for the dynamic thread construction mechanism in terms of public key query frequency, and the data reflecting the frequency of different public keys being queried are obtained from the cache management strategy. According to the public key query frequency data, a higher priority is set for the corresponding verification task to ensure that the verification task corresponding to the high-frequency public key is processed first. The dynamic thread construction mechanism processes the verification task corresponding to the high-frequency public key first according to the data. Meanwhile, the dynamic thread construction mechanism can also predict and process the verification task corresponding to the public key that may be needed in the future according to the prefetch mechanism in the cache management strategy, further reducing the query delay. The cache management strategy and the dynamic thread construction mechanism share data such as public key query frequency and verification task processing status, and work together according to the execution of the cache management strategy and the system performance monitoring results to dynamically adjust the parameters of the dynamic thread construction mechanism to optimize the overall system performance.

[0060] The technical solutions in the embodiments of the present application have at least the following technical effects or advantages:

[0061] The present application effectively improves the efficiency and speed of data processing by dynamically adjusting the priority and order of the verification task and simplifying or increasing the verification steps, preferentially processes critical and high-frequency tasks, delays or combines the processing of low-priority tasks, reduces the occupation and waste of system resources, and achieves the effect of dynamically adjusting the task order, further improving the data processing efficiency.

[0062] Embodiment Four: The present embodiment is further improved on the basis of the above-mentioned embodiments.

[0063] The method further comprises: S500, monitoring steps S100 and S200 in real time, generating a stage trust value for the smart meter according to the monitoring data, obtaining a total trust value according to the stage trust value, establishing a trust chain according to the total trust value, generating a trust code based on the trust chain, and directly adding the smart meter to the end queue after the trust code is verified.

[0064] In some embodiments, the stage trust value is generated according to the data verification process in the initial queue, the middle queue, and the end queue, and a trust threshold is set in each stage. If the stage trust value of any stage is lower than the trust threshold, the subsequent trust judgment is cancelled. The generation of the stage trust value is as follows: the smart meter code is obtained, the historical data record of the meter is queried, the data accuracy, abnormal frequency and other indicators are analyzed, an initial trust value (such as a value between 0 and 1) is assigned to the meter according to the historical performance, the smart meter code and the initial trust value are stored in the trust value database, the state of the data in the transmission and processing process is monitored in real time, such as transmission delay, data integrity, etc., the initial trust value is adjusted according to the data monitoring result, such as data performance stability, the trust value can be appropriately improved; if an abnormality occurs, the trust value is reduced, a fixed floating value is set, for example, 0.05, the fixed floating value is used as the minimum unit for adjusting the trust value, the stage trust value is determined according to the verification result and the trust threshold of the end queue; and the total trust value is calculated according to the three stage trust values.

[0065] In some embodiments, the total trust values generated for all smart meters are sorted in descending order, and the smart meters corresponding to the total trust values above the median are selected to generate a trust chain. Here, the selection can be set according to actual conditions, or a threshold or a fixed selection ratio can be set for selection. The three stage trust values corresponding to the finally selected smart meters are concatenated in order to form a trust chain, the trust chain is stored in a trust chain database and associated with the smart meter code, the trust chain is hashed or otherwise encrypted to generate a trust code, and the trust code is stored in a trust code database in association with the smart meter code. The trust chain and the trust code generated for each smart meter are different. The trust chain forms a trust transmission mechanism by concatenating the trust values of different stages, ensuring that the trust degree of the data can be continuously transmitted in the entire processing and interaction process. The trust chain can trace the trust source of the data, and in the case of failed trust code verification, the problem can be quickly located and solved through the trust chain. The trust code is a unique identifier obtained by hashing or otherwise encrypting the trust chain. By verifying the trust code, the trust degree of the data can be quickly confirmed without the need to recalculate or verify the entire trust chain

[0066] In some embodiments, when receiving the meter data request, first query the trust code database, recalculate the hash value of the trust chain of the requested data or perform decryption processing, and compare with the stored trust code. If the trust codes are consistent, the data is legal and is directly added to the end queue for parsing. If the trust codes are inconsistent, it is rejected.

[0067] In some embodiments, a time limit is set for each trust code, which should be set according to the characteristics of the data and the application scenario. For frequently changing or important data, the trust period can be set shorter; otherwise, it can be set longer, preferably between 2 days and 7 days, and the specific period needs to be adjusted according to the actual situation. When detecting abnormal or tampering signs, the trust value should be updated immediately and the trust chain should be regenerated. The data should be audited regularly, and the trust value should be updated according to the audit results. The audit period is set according to the trust time limit, such as a month, the audit period can be set to half a month or a month.

[0068] The technical solutions in the embodiments of the present application have at least the following technical effects or advantages:

[0069] The present application realizes fast trust verification by real-time monitoring and stage trust value generation, building a trust chain, generating a trust code, and further improving the data processing speed. The trust chain records the trust degree change of the data in the whole processing process, which is convenient for tracing the trust source of the data and realizing the effect of quickly positioning the fault problem.

[0070] The above only describes the preferred embodiments of the present application and is not used to limit the present application. For those skilled in the art, the present application can have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A data security communication method based on a smart meter, characterized in that: The method comprises: S100: Obtain basic data information, location information, and bandwidth threshold information of smart meters, perform preliminary verification and check, and generate a queue to be processed; classify each smart meter according to the basic data information, establish a peer mechanism to verify and check the smart meters in the queue to be processed, and generate a mid-term queue; S200: setting difference verification according to the levels of different smart meters in the mid-term queue, and adding the smart meters that pass the verification to the final queue; S300: Obtain and parse the data corresponding to the smart meters in the last queue, and store the parsed meter data; monitor steps S100 and S200 in real time, issue timely warnings for any abnormal conditions that occur, and generate abnormality report information; S400: Set up a dynamic line structure mechanism to dynamically adjust the priority of verification tasks based on real-time data flow and load conditions, sort verification tasks according to the frequency of public key queries, and dynamically adjust the verification process based on the level of smart meters; S500: Monitor steps S100 and S200 in real time, and generate a stage trust value for the smart meter based on the monitored data. Calculate a total trust value based on the stage trust value, establish a trust chain based on the total trust value, generate a trust code based on the trust chain, and directly add the smart meter to the last queue after the trust code is verified. The verification and inspection is to generate a first private key and a second private key based on the location information and bandwidth threshold information of the smart meter in the queue to be processed, and generate corresponding first and second public keys, generate a third private key of the smart meter based on the first private key and the second private key, and generate a third public key based on the third private key, obtain real-time bandwidth information when the smart meter transmits data to the meter data receiving platform, generate a fourth private key based on the real-time bandwidth information, and generate a fourth public key based on the fourth private key; call the first public key, the second public key, the third public key and the fourth public key in sequence, and determine whether there is permission for parsing and receiving based on the first private key, the second private key, the third private key and the fourth private key in sequence.

2. A data security communication method based on a smart meter according to claim 1, characterized in that: The basic data information includes the unique code of the smart meter, historical data records, and data importance; the level includes low level, medium level and high level, and the levels are divided according to dynamic verification based on the basic data information and real-time data information of data transmission.

3. The data security communication method based on a smart meter according to claim 1, characterized in that: The peer mechanism is to send peer query requests to multiple storage lists, perform key verification, and determine whether there is permission to perform parsing and receiving. If there is permission, it will be added to the mid-term queue.

4. The data security communication method based on a smart meter according to claim 1, characterized in that: The difference verification is to set different key verification methods and verification processes according to different levels, and set different encryption verification methods corresponding to different levels of smart meters.

5. The data security communication method based on a smart meter according to claim 1, characterized in that: The pending queue, mid-term queue and final queue refer to sets of smart meters that have passed verification at different times and their corresponding data information respectively.

6. The data security communication method based on a smart meter according to claim 1, characterized in that: The stage trust value is generated based on the data verification process of the smart meter in the initial queue, mid-term queue and final queue. A trust threshold is pre-set in each stage. If the stage trust value of any stage is lower than the trust threshold, the subsequent trust judgment is cancelled.

7. The data security communication method based on a smart meter according to claim 1, characterized in that: The peer mechanism also includes a cache management strategy, and sets cache areas based on the level of the smart meter, adjusts the size of the cache area according to the real-time monitoring data, and adjusts the cache time in real time; the cache management strategy also includes a pre-fetch mechanism, which judges the usage trend of the public key based on the basic prediction model, and pre-loads the public keys required in the future time period into the cache.

Images