A blockchain device monitoring system based on fully homomorphic encryption technology

Abstract

This invention provides a blockchain device monitoring system based on fully homomorphic encryption technology, belonging to the field of device monitoring technology. It includes: a data acquisition module for collecting target data from the device to be monitored, including operational status data and health status data; a trusted computing module for ensuring the authenticity and immutability of the target data; a homomorphic encryption module for performing fully homomorphic encryption on the target data to obtain a return data packet; a data signing module for using a digital certificate for identity verification and digitally signing the return data packet; a secure storage module for storing the target data and the return data packet; and a data transmission module for transmitting the encrypted and signed return data packet to a smart gateway device. This invention uses fully homomorphic encryption technology to encrypt the device monitoring data, ensuring the security of the data during transmission, storage, and computation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of device monitoring, in particular to a blockchain device monitoring system based on fully homomorphic encryption technology. BACKGROUND

[0002] Intelligent device monitoring is widely used in intelligent manufacturing, smart healthcare, smart city and other Internet of Things scenarios. However, existing device monitoring systems have many challenges in data privacy, authenticity, integrity and reliability. For example, data may be stolen or tampered with during transmission, making it impossible to accurately monitor the running status and health of the device. Therefore, it is an urgent need in the industry to develop a device monitoring system that can ensure data privacy, authenticity, integrity and reliability.

[0003] Blockchain technology has the characteristics of decentralization and tamper resistance, which can effectively solve the authenticity and integrity of data storage. However, the transparency and distributed nature of the blockchain system pose a challenge to the privacy of on-chain data. How to protect the privacy and security of on-chain data while taking advantage of the distributed consensus characteristics of the blockchain to achieve trusted data verification and processing is a problem that needs to be solved in the current blockchain application.

[0004] Therefore, a blockchain device monitoring system based on fully homomorphic encryption technology is proposed. SUMMARY

[0005] The present application provides a blockchain device monitoring system based on fully homomorphic encryption technology, which uses fully homomorphic encryption technology to encrypt device monitoring data, ensuring the security of data during transmission, storage and calculation.

[0006] The present application provides a blockchain device monitoring system based on fully homomorphic encryption technology, which includes:

[0007] Data acquisition terminal, intelligent gateway device, blockchain device, online monitoring platform;

[0008] The to-be-monitored device is electrically connected to the data acquisition terminal, the data acquisition terminal is electrically connected to the intelligent gateway device, the intelligent gateway device is electrically connected to the blockchain device, and the blockchain device is electrically connected to the online monitoring platform.

[0009] The to-be-monitored device is electrically connected to the data acquisition terminal, the data acquisition terminal is electrically connected to the intelligent gateway device, including:

[0010] The data acquisition terminal comprises a data acquisition module, a trusted computing module, a homomorphic encryption module, a data signature module, a secure storage module, and a data transmission module. The data acquisition module is configured to acquire target data of a device to be monitored, wherein the target data comprises running state data of the device to be monitored and health state data of the device to be monitored. The trusted computing module is configured to ensure the authenticity and tamper resistance of the target data. The homomorphic encryption module is configured to perform fully homomorphic encryption on the target data to obtain a return data packet. The data signature module is configured to use a digital certificate for identity identification and perform digital signature on the return data packet. The secure storage module is configured to store the target data and the return data packet. The data transmission module is configured to transmit the return data packet after encryption and signature to the intelligent gateway device.

[0011] Optionally, the intelligent gateway device is electrically connected with the blockchain device, and comprises:

[0012] The intelligent gateway device receives the return data packet and performs signature verification on the return data packet.

[0013] When the intelligent gateway device determines that the signature verification of the return data packet is passed, the return data packet is parsed, and the parsed return data packet is written into the smart contract of the blockchain device.

[0014] Optionally, the intelligent gateway device is electrically connected with the blockchain device, and further comprises:

[0015] When the intelligent gateway device determines that the signature verification of the return data packet is not passed, the return data packet is determined as an illegal data packet, and the return data packet is discarded.

[0016] Optionally, the blockchain device is electrically connected with the online monitoring platform, and comprises:

[0017] The online monitoring platform acquires the return data through the blockchain device.

[0018] The online monitoring platform analyzes the return data to obtain a monitoring analysis result of the device to be monitored.

[0019] The online monitoring platform writes the monitoring analysis result back to the blockchain device.

[0020] Optionally, the online monitoring platform analyzes the return data, and comprises:

[0021] The return data is analyzed through a statistical process control model.

[0022] and / or,

[0023] analyzing the backhaul data by a time series prediction model;

[0024] and / or,

[0025] analyzing the backhaul data by a decision tree model;

[0026] and / or,

[0027] analyzing the backhaul data by a support vector machine;

[0028] and / or,

[0029] analyzing the backhaul data by a deep learning model.

[0030] Optionally, the analyzing the backhaul data by a statistical process control model comprises:

[0031] calculating statistical features of the backhaul data, and constructing a control chart using the statistical features to monitor the stability of the device running state;

[0032] identifying abnormal data points of the backhaul data to realize fault early warning of the device to be monitored.

[0033] Optionally, the analyzing the backhaul data by a decision tree model comprises:

[0034] constructing a decision tree model for classification and regression analysis;

[0035] identifying key factors affecting the device running state;

[0036] adjusting the fault diagnosis and health status evaluation scheme of the device to be monitored in real time according to the analysis result of the decision tree model.

[0037] Optionally, the obtaining the monitoring analysis result of the device to be monitored further comprises:

[0038] fusing different analysis results, and generating the monitoring analysis result of the device to be monitored based on the fusion analysis result.

[0039] Optionally, the method further comprises:

[0040] establishing cross-chain connection with other blockchain platforms to realize cross-chain sharing and collaborative analysis of device monitoring data;

[0041] adopting cross-chain homomorphic encryption technology to ensure data security and privacy protection in the process of cross-chain data interaction.

[0042] Optionally, the method further comprises:

[0043] Deploy lightweight homomorphic encryption algorithm and edge computing model on data acquisition terminal or intelligent gateway device;

[0044] Local homomorphic computation and real-time analysis are performed on equipment monitoring data, reducing data transmission volume and cloud computing pressure;

[0045] The local analysis result is cooperatively fused with the cloud analysis result, improving the accuracy and real-time performance of data analysis.

[0046] The present application uses fully homomorphic encryption technology to encrypt equipment monitoring data, ensuring the security of data during transmission, storage and computation. Even if the data is stolen, it cannot be decrypted. The encrypted equipment monitoring data is stored on the blockchain, and only authorized nodes can decrypt and access the data, effectively protecting data privacy. The blockchain technology has the characteristics of non-tamperability, which can ensure the authenticity and traceability of equipment monitoring data. The system based on blockchain technology has good scalability, which can easily access new equipment nodes and authorized nodes. The online monitoring platform provides various data analysis methods and supports data fusion analysis, which can meet the data analysis needs in different scenarios. Local real-time analysis is performed on the data acquisition terminal or intelligent gateway device, reducing data transmission volume and cloud computing pressure, and improving the real-time performance of data analysis. The local analysis result is cooperatively fused with the cloud analysis result, improving the accuracy of data analysis. Cross-chain connection with other blockchain platforms is supported to realize cross-chain sharing and collaborative analysis of equipment monitoring data. Lightweight homomorphic encryption algorithm and edge computing model are deployed on the data acquisition terminal or intelligent gateway device to realize local homomorphic computation and real-time analysis of equipment monitoring data. BRIEF DESCRIPTION OF DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0048] Figure 1 A structure diagram of a blockchain equipment monitoring system based on fully homomorphic encryption technology is provided for the embodiments of the present application.

[0049] Figure 2 A principle diagram of a data acquisition device is provided for the embodiments of the present application.

[0050] Figure 3 A principle diagram of an intelligent gateway device is provided for the embodiments of the present application.

[0051] Figure 4A schematic diagram of the principle of the online monitoring platform provided for the embodiments of the present description. DETAILED DESCRIPTION

[0052] The following description is provided so as to enable any person skilled in the art to practice the present application. The preferred embodiments described herein are only examples of the present application and the present application is not limited to these preferred embodiments. The present application defined by the claims is not limited to the preferred embodiments described herein, which are presented solely for the purpose of illustration only. The principles of the present application defined by the claims can be applied to other embodiments, variations, modifications, equivalents and other technical solutions without departing from the spirit and scope of the present application.

[0053] The accompanying drawings are included to provide a further understanding of the present application, and are incorporated in and constitute a part of this specification. Figures 1-4 Exemplary embodiments of the present application are described more fully hereinafter with reference to the accompanying drawings. However, the exemplary embodiments can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these exemplary embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the inventive concept to those skilled in the art. Like reference numerals refer to like elements throughout the specification.

[0054] In the case of a specific embodiment, the features, structures, characteristics or other details described do not exclude the possibility of being combined in a suitable manner in one or more other embodiments, in accordance with the technical idea of the present application.

[0055] In the description of the specific embodiments, the features, structures, characteristics or other details described are intended to enable a person skilled in the art to fully understand the embodiments. However, it does not exclude the possibility that one or more of the specific features, structures, characteristics or other details can not be practiced by a person skilled in the art without the specific feature, structure, characteristic or other detail.

[0056] The flowcharts shown in the drawings are only exemplary illustrations and do not necessarily include all contents and operations / steps, nor are they necessarily executed in the order described. For example, some operations / steps can be further broken down, and some operations / steps can be combined or partially combined, so the actual execution order can be changed according to the actual situation.

[0057] The block diagrams shown in the drawings are only functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0058] The term "and / or" or "and / or" includes all combinations of one or more of the associated listed items.

[0059] The embodiment of the present specification provides a blockchain device monitoring system based on a complete homomorphic encryption technology, which comprises:

[0060] a data acquisition terminal, an intelligent gateway device, a blockchain device, and an online monitoring platform.

[0061] The to-be-monitored device is electrically connected with the data acquisition terminal, the data acquisition terminal is electrically connected with the intelligent gateway device, the intelligent gateway device is electrically connected with the blockchain device, and the blockchain device is electrically connected with the online monitoring platform.

[0062] The to-be-monitored device is electrically connected with the data acquisition terminal, and the data acquisition terminal is electrically connected with the intelligent gateway device, comprising:

[0063] The data acquisition terminal comprises a data acquisition module, a trusted computing module, a homomorphic encryption module, a data signature module, a secure storage module, and a data transmission module; the data acquisition module is used for acquiring target data of a to-be-monitored device, wherein the target data comprises running state data of the to-be-monitored device and health state data of the to-be-monitored device; the trusted computing module is used for ensuring the authenticity and non-tamperability of the target data; the homomorphic encryption module is used for performing complete homomorphic encryption on the target data to obtain a return data packet; the data signature module is used for performing identity identification using a digital certificate and performing digital signature on the return data packet; the secure storage module is used for storing the target data and the return data packet; and the data transmission module is used for transmitting the encrypted and signed return data packet to the intelligent gateway device.

[0064] In the detailed description of the present specification, as Figure 1As shown, the data acquisition module collects the running state data (such as temperature, humidity, pressure, vibration, etc.) and health state data (such as equipment running time, fault record, maintenance record, etc.) of the equipment to be monitored through sensors, data interfaces, etc. The trusted computing module uses the trusted execution environment (TEE) technology to build a secure isolated trusted execution environment inside the data acquisition terminal, and performs integrity verification on the collected target data to ensure that the data has not been tampered with. The homomorphic encryption module uses a fully homomorphic encryption algorithm based on lattice cryptography to encrypt the target data that passes the verification to obtain a return data packet. The fully homomorphic encryption algorithm supports computing on data in a ciphertext state, and the calculation result after decryption is consistent with the result of the same calculation on plaintext data. The data signature module uses the private key of the data acquisition terminal to digitally sign the return data packet, and attaches the digital certificate of the data acquisition terminal to the return data packet for verifying the data source and integrity. The secure storage module locally encrypts and stores the target data and the return data packet to prevent data leakage. The data transmission module transmits the encrypted and signed return data packet to the intelligent gateway device through a secure communication protocol (such as TLS / SSL).

[0065] Optionally, the intelligent gateway device is electrically connected with the blockchain device, and comprises:

[0066] The intelligent gateway device receives the return data packet and performs signature verification on the return data packet.

[0067] When the intelligent gateway device determines that the signature verification of the return data packet passes, the return data packet is parsed, and the parsed return data packet is written into the smart contract of the blockchain device.

[0068] In the specific embodiments of the present specification, as shown Figure 2 The return data packet from the data acquisition terminal is received, the digital signature of the return data packet is verified using the digital certificate of the data acquisition terminal to confirm that the data source is authentic and reliable, the return data packet is hashed, and the hash value in the digital signature is compared to confirm the data integrity. The return data packet that passes the signature verification is parsed to extract the encrypted target data, the identifier of the data acquisition terminal, the timestamp, etc.

[0069] The parsed return data packet is written into the smart contract of the blockchain device, specifically, the interface of the smart contract is called, the encrypted target data, the identifier of the data acquisition terminal, the timestamp, etc. are transmitted as parameters, the smart contract stores the received data on the blockchain, generates a corresponding transaction record, and triggers the corresponding event to notify the online monitoring platform that new data is uploaded.

[0070] Optionally, the intelligent gateway device is electrically connected with the blockchain device, and further comprises:

[0071] When the intelligent gateway device determines that the backhaul data packet signature verification fails, the backhaul data packet is determined to be an illegal data packet, and the backhaul data packet is discarded.

[0072] In the specific embodiments of the present specification, an abnormal event is recorded, including the content of the backhaul data packet, the identifier of the data collection terminal, the timestamp, and the like. The abnormal event is reported to an online monitoring platform for further analysis and processing. The backhaul data packet is discarded to prevent illegal data packets from entering the system.

[0073] Optionally, the blockchain device is electrically connected with the online monitoring platform, and includes:

[0074] The online monitoring platform acquires the backhaul data through the blockchain device;

[0075] The online monitoring platform analyzes the backhaul data to obtain a monitoring analysis result of the to-be-monitored device;

[0076] The online monitoring platform writes the monitoring analysis result back to the blockchain device.

[0077] In the specific embodiments of the present specification, as shown in Figure 3 The smart contract interface of the blockchain device is called to query the backhaul data in a specified time range. The encrypted backhaul data packet is downloaded from the blockchain device. The private key of the authorized node is used to decrypt the backhaul data packet to obtain target data. The target data is analyzed to generate a device running state report, a health state evaluation report, fault early warning information, and the like. The analysis result is displayed to the user in the form of a chart, a report, and the like. The monitoring analysis result is encrypted and packaged into a data packet. The smart contract interface of the blockchain device is called to write the data packet into the blockchain. The smart contract stores the received data on the blockchain and generates a corresponding transaction record.

[0078] Optionally, the online monitoring platform analyzes the backhaul data, including:

[0079] The backhaul data is analyzed through a statistical process control model;

[0080] and / or,

[0081] The backhaul data is analyzed through a time series prediction model;

[0082] and / or,

[0083] The backhaul data is analyzed through a decision tree model;

[0084] and / or,

[0085] analyzing the backhaul data by a support vector machine;

[0086] and / or,

[0087] analyzing the backhaul data by a deep learning model.

[0088] In the detailed description of the present specification, the backhaul data is analyzed by a time series prediction model. Specifically, a time series model, such as an ARIMA model, an exponential smoothing model, etc., is constructed to predict the future operation state of the equipment; the operation trend and periodic changes of the equipment are identified and predicted; and the equipment maintenance plan and optimized operation strategy are formulated according to the prediction results.

[0089] The backhaul data is analyzed by a support vector machine. Specifically, a support vector machine model is constructed for classification and regression analysis; the nonlinear relationship of the equipment operation state is identified; and the equipment fault early warning and operation optimization strategy are formulated according to the analysis results of the support vector machine model.

[0090] The backhaul data is analyzed by a deep learning model. Specifically, a deep learning model, such as a convolutional neural network, a recurrent neural network, etc., is constructed to process high-dimensional, unstructured data; the complex patterns and features of the equipment operation state are identified; and the equipment fault prediction, health state evaluation and operation optimization are realized according to the analysis results of the deep learning model.

[0091] Optionally, the backhaul data is analyzed by a statistical process control model, including:

[0092] statistical characteristics of the backhaul data are calculated, and a control chart is constructed using the statistical characteristics to monitor the stability of the equipment operation state;

[0093] abnormal data points of the backhaul data are identified to realize the fault early warning of the equipment to be monitored.

[0094] In the detailed description of the present specification, statistical characteristics of the backhaul data, such as mean, variance, standard deviation, etc., are calculated; a control chart, such as an X-bar chart, an R chart, etc., is constructed to monitor the stability of the equipment operation state; and abnormal data points in the equipment operation process are identified and warned.

[0095] Optionally, the backhaul data is analyzed by a decision tree model, including:

[0096] a decision tree model is constructed for classification and regression analysis;

[0097] key factors affecting the equipment operation state are identified;

[0098] According to the analysis result of the decision tree model, the fault diagnosis and health status evaluation scheme of the to-be-monitored equipment is adjusted in real time.

[0099] Optionally, the obtaining of the monitoring analysis result of the to-be-monitored equipment further includes:

[0100] The different analysis results are fused and analyzed, and the monitoring analysis result of the to-be-monitored equipment is generated based on the result of the fusion analysis.

[0101] In the specific embodiments of the present specification, the results of different analysis models are standardized to eliminate the influence of dimensions and orders of magnitude. Key features are extracted from the results of different analysis models, such as the number of abnormal data points, the confidence of the prediction result, etc. The results of different analysis models are fused using methods such as weighted average, voting, Stacking, etc. to generate the final monitoring analysis result.

[0102] Optionally, it further includes:

[0103] Cross-chain connection is established with other blockchain platforms to realize cross-chain sharing and collaborative analysis of equipment monitoring data.

[0104] Cross-chain homomorphic encryption technology is adopted to ensure data security and privacy protection during cross-chain data interaction.

[0105] In the specific embodiments of the present specification, a suitable cross-chain protocol is selected, such as Cosmos, Polkadot, etc.; a cross-chain gateway is deployed to realize communication and data transmission between different blockchain platforms; cross-chain routing rules are configured to specify data forwarding paths and access permissions.

[0106] The equipment monitoring data on the blockchain platform is encrypted and packaged into a data packet; the data packet is forwarded to the target blockchain platform through the cross-chain gateway; the target blockchain platform receives the data packet and performs decryption and storage.

[0107] The smart contract interface of the target blockchain platform is called to obtain the required equipment monitoring data; the obtained equipment monitoring data is fused and analyzed with local data; and the analysis result is written back to the target blockchain platform.

[0108] Optionally, it further includes:

[0109] A lightweight homomorphic encryption algorithm and an edge computing model are deployed on a data acquisition terminal or an intelligent gateway device.

[0110] The equipment monitoring data is subjected to local homomorphic calculation and real-time analysis to reduce data transmission volume and cloud computing pressure.

[0111] The local analysis result is collaboratively fused with the cloud analysis result to improve the accuracy and real-time performance of data analysis.

[0112] In the specific embodiments of the present specification, a suitable lightweight homomorphic encryption algorithm is selected, such as BFV, CKKS, etc.;The lightweight homomorphic encryption algorithm is compiled into code that can run on an embedded device. The compiled code is deployed to a data acquisition terminal or an intelligent gateway device.

[0113] A suitable edge computing model is selected, such as decision tree, support vector machine, neural network, etc.;The edge computing model is trained into a model that can run on an embedded device. The trained model is deployed to a data acquisition terminal or an intelligent gateway device.

[0114] The device monitoring data is encrypted using a lightweight homomorphic encryption algorithm. The edge computing model is used to analyze the device monitoring data in real time in a ciphertext state. The analysis result is encrypted and stored locally.

[0115] The local analysis result is encrypted and transmitted to the cloud. The cloud decrypts the local analysis result and performs fusion analysis with the cloud analysis result. The fusion analysis result is returned to the data acquisition terminal or the intelligent gateway device.

[0116] The present application uses fully homomorphic encryption technology to encrypt device monitoring data, ensuring the security of data during transmission, storage and calculation. Even if the data is stolen, it cannot be decrypted. The encrypted device monitoring data is stored on the blockchain, and only authorized nodes can decrypt and access the data, effectively protecting data privacy. The blockchain technology has the characteristics of non-tamperability, which can ensure the authenticity and traceability of the device monitoring data. The system based on the blockchain technology has good scalability, which can easily access new device nodes and authorized nodes. The online monitoring platform provides multiple data analysis methods and supports data fusion analysis, which can meet the data analysis needs in different scenarios. Local real-time analysis is performed on the data acquisition terminal or the intelligent gateway device, reducing data transmission and cloud computing pressure, and improving the real-time performance of data analysis. The local analysis result is cooperatively fused with the cloud analysis result to improve the accuracy of data analysis. Cross-chain connection with other blockchain platforms is supported to realize cross-chain sharing and collaborative analysis of device monitoring data. Lightweight homomorphic encryption algorithms and edge computing models are deployed on the data acquisition terminal or the intelligent gateway device to realize local homomorphic computation and real-time analysis of device monitoring data.

[0117] The present application can be implemented in hardware, or as software modules running in one or more processors, or in combinations thereof. Skilled persons should understand that some or all of the functions of some or all of the components according to the embodiments of the present application can be implemented in practice using a general-purpose data processing device such as a microprocessor or a digital signal processor (DSP). The present application can also be implemented as a device or apparatus program (for example, a computer program and a computer program product) for performing part or all of the methods described herein. Such a program implementing the present application can be stored on a computer readable medium, or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, or provided on a carrier signal, or in any other form.

[0118] The above-described specific embodiments further illustrate the purposes, technical solutions and beneficial effects of the present application. It should be understood that the present application is not inherently related to any specific computer, virtual device or electronic device, and various general-purpose devices can implement the present application. The above-described specific embodiments are merely examples of the present application, and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0119] Each of the embodiments in the specification is described in a progressive manner, and the same or similar parts between the embodiments can be mutually referred to. Each of the embodiments mainly describes the differences from other embodiments.

[0120] The above-described specific embodiments are merely examples of the present application, and are not intended to limit the present application. For those skilled in the art, the present application can have various modifications and changes. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A blockchain device monitoring system based on fully homomorphic encryption technology, characterized in that, The application relates to an online monitoring system and method. The data acquisition terminal, the intelligent gateway device, the blockchain device and the online monitoring platform are electrically connected; wherein the online monitoring platform obtains backhaul data through the blockchain device; the online monitoring platform analyzes the backhaul data to obtain monitoring analysis results of the to-be-monitored device; and the online monitoring platform writes the monitoring analysis results back to the blockchain device. The online monitoring platform analyzes the backhaul data by using a statistical process control model, a time series prediction model, a decision tree model, a support vector machine or a deep learning model. The data acquisition terminal comprises a data acquisition module, a trusted computing module, a homomorphic encryption module, a data signature module, a secure storage module and a data transmission module; the data acquisition module is used for acquiring target data of the to-be-monitored device, wherein the target data comprises running state data and health state data of the to-be-monitored device; the trusted computing module is used for ensuring the authenticity and non-tamperability of the target data; the homomorphic encryption module is used for performing full homomorphic encryption on the target data to obtain a backhaul data packet; the data signature module is used for performing identity identification by using a digital certificate and performing digital signature on the backhaul data packet; the secure storage module is used for storing the target data and the backhaul data packet; and the data transmission module is used for transmitting the encrypted and signed backhaul data packet to the intelligent gateway device. The intelligent gateway device receives the backhaul data packet and performs signature verification on the backhaul data packet; When the intelligent gateway device determines that the signature verification of the backhaul data packet is passed, the intelligent gateway device analyzes the backhaul data packet and writes the analyzed backhaul data packet into a smart contract of the blockchain device.

2. The fully homomorphic encryption technology based blockchain device monitoring system of claim 1, wherein, When the intelligent gateway device determines that the signature verification of the backhaul data packet is not passed, the intelligent gateway device regards the backhaul data packet as an illegal data packet and discards the backhaul data packet. The statistical process control model is used for calculating statistical characteristics of the backhaul data, constructing a control chart by using the statistical characteristics and monitoring the stability of the running state of the device; and the abnormal data points of the backhaul data are identified to realize fault early warning of the to-be-monitored device. ​ 3. The fully homomorphic encryption technique based blockchain device monitoring system of claim 2, wherein, ​ ​ 4. The fully homomorphic encryption technique based blockchain device monitoring system of claim 3, wherein, ​ ​ ​ 5. The fully homomorphic encryption technique based blockchain device monitoring system of claim 4, wherein, The analysis of the backhaul data by the decision tree model comprises: Constructing a decision tree model for classification and regression analysis; Identifying key factors affecting the operating state of the equipment; According to the analysis result of the decision tree model, real-time adjustment of the fault diagnosis and health state evaluation scheme of the to-be-monitored equipment.

6. The fully homomorphic encryption technique based blockchain device monitoring system of claim 5, wherein, The monitoring analysis result of the to-be-monitored equipment also includes: Fusion analysis of different analysis results, and generation of the monitoring analysis result of the to-be-monitored equipment based on the fusion analysis result.

7. The fully homomorphic encryption technique based blockchain device monitoring system of claim 6, wherein, Also includes: Establishing cross-chain connection with other blockchain platforms to realize cross-chain sharing and collaborative analysis of equipment monitoring data; Using cross-chain homomorphic encryption technology to ensure data security and privacy protection during cross-chain data interaction.

8. The fully homomorphic encryption technique based blockchain device monitoring system of claim 7, wherein, Also includes: Deploying lightweight homomorphic encryption algorithms and edge computing models on data acquisition terminals or intelligent gateway devices; Local homomorphic computation and real-time analysis of equipment monitoring data to reduce data transmission volume and cloud computing pressure; Collaborative fusion of local analysis results and cloud analysis results to improve the accuracy and real-time performance of data analysis.

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