Cloud database key management method based on Internet of Things

Abstract

The invention discloses a cloud database key management method based on the Internet of Things, and particularly relates to the technical field of the Internet of Things, and the method comprises the steps: S1, system initialization and definition: defining a data privacy degree evaluation index; s2, data collection and evaluation: collecting data, carrying out data classification, and adding privacy degree labels; s3, key generation and distribution: generating a key strategy, and uploading key metadata to a block chain network; s4, data encryption and uploading: encrypting the data, uploading the encrypted data to an edge computing node, and uploading the encrypted data to a cloud database; s5, data query and recovery: querying the encrypted data, and obtaining key metadata to decrypt the encrypted data; and S6, auditing monitoring and fault tolerance: monitoring a key management operation state in real time, and calculating a key management comprehensive evaluation index. The security and traceability of the key management are effectively improved by adopting a specific encryption strategy for the division of the data privacy degree and monitoring the running state of the key management in real time.

Description

Technical Field

[0001] The present invention relates to the technical field of the Internet of Things. More specifically, the present invention relates to a method for managing keys of a cloud database based on the Internet of Things. Background Art

[0002] With the rapid development of the Internet of Things and cloud computing technologies, the Internet of Things connects various devices through the Internet to achieve data collection and sharing, and is widely applied in the fields of smart home and smart city. However, the number of devices is huge and they are widely distributed, and data security and privacy protection have become key issues. Cloud computing provides powerful computing and storage capabilities to support the processing and analysis of large-scale data. When data is stored in the cloud, it faces security threats. Therefore, key management is an effective technical means to protect data security. Key management includes key generation, storage, distribution, update, and destruction, and is the basis of data encryption.

[0003] However, when it is actually used, there are still some drawbacks. First, there is a lack of device collaboration and real-time performance. Traditional cloud database key management methods do not fully consider the diversity of Internet of Things devices and the requirements for real-time data collection. The amount of data generated by Internet of Things device terminals is huge and real-time, and it is difficult for traditional methods to effectively manage and control these devices, lacking real-time performance.

[0004] Second, the management of data privacy level is not fine enough. Traditional cloud database key management methods often consider data privacy level in a relatively single way, and may only make simple classifications based on a few factors such as data type or access permission, and it is difficult to comprehensively and accurately evaluate the privacy degree of data.

[0005] Third, the security and traceability of key management are insufficient. In the process of key management by traditional methods, there is a lack of effective security guarantee and traceability mechanism. There may be security vulnerabilities in key generation, distribution, and storage. Once the key is leaked, it is difficult to quickly locate and trace the root cause of the problem. Summary of the Invention

[0006] In view of this, embodiments of the present invention provide a method for managing keys of a cloud database based on the Internet of Things. By dividing the sensitivity of data, the privacy degree of data is then judged, corresponding key management strategies are adopted according to the privacy degree of data, and by real-time monitoring the running state in the process of key management and taking effective solutions, the problems of lack of real-time performance, insufficiently fine management of data privacy degree, and insufficient security degree proposed in the background art are effectively solved.

[0007] To achieve the above object, the present invention provides the following technical solution: A method for managing keys of a cloud database based on the Internet of Things, including an Internet of Things device terminal, an edge computing node, a cloud database, a blockchain network, and a management console, which are connected through the Internet. Specifically, it includes the following steps: S1: System initialization and definition: Initialize the system, define data privacy evaluation metrics, configure the blockchain network, deploy smart contracts, and assign identifiers; S2: Data collection and evaluation: Collect data through IoT device terminals, classify the data according to privacy evaluation metrics, and attach privacy tags to the data; S3: Key generation and distribution: Edge computing nodes generate key policies based on data privacy, securely distribute the keys to IoT device terminals, and upload key metadata to the blockchain network; S4: Data encryption and upload: IoT device terminals use the received keys to encrypt the data, upload the encrypted data to edge computing nodes, and edge computing nodes process the data and upload it to the cloud database; S5: Data query and recovery: The management console queries the encrypted data through the cloud database, edge computing nodes obtain key metadata from the blockchain network, decrypt the keys, and use the decrypted keys to decrypt the encrypted data; S6: Audit monitoring and fault tolerance: Real-time monitor the operation status of key management, calculate the comprehensive evaluation index of key management, recover damaged keys, and recover and encrypt lost data.

[0008] Technical effects and advantages of the present invention: 1. By adopting the collaborative work of IoT device terminals and edge computing nodes, the present invention can collect device-side data in real time, making the entire IoT device terminal closely connected to the key management system. It can collect data in real time and participate in data privacy evaluation, encryption and other links, realizing the full-process security management of data from generation to storage, and improving the coordination and real-time performance of the device; 2. By defining data privacy evaluation metrics, and dividing data sensitivity into low sensitivity, medium sensitivity, and high sensitivity, determining the scoring range and weight for different evaluation metrics, generating different key policies for data with different privacy levels, and comprehensively considering factors such as the source, use, and privacy of the data for evaluation, the present invention can generate more appropriate key policies and provide more refined data protection.

[0009] 3. By real-time monitoring the operation status of key management and calculating the comprehensive evaluation index of key management, the present invention can comprehensively and effectively reflect whether there are abnormalities in the key management process. By uploading key metadata to the blockchain network, the distributed ledger and smart contract technologies of the blockchain ensure the immutability and traceability of key metadata. Through the real-time monitoring of the key management operation status and the upload and processing of key metadata, the security and traceability of key management are improved. Brief Description of the Drawings

[0010] Figure 1Schematic diagram of the method steps of the present invention.

[0011] Figure 2 Schematic diagram of the system structure of the present invention. Detailed implementation manners

[0012] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0013] As shown in the attached Figure 1 A cloud database key management method based on the Internet of Things, including an Internet of Things device terminal, an edge computing node, a cloud database, a blockchain network, and a management console, which are connected through the Internet.

[0014] Specifically, in this embodiment, the Internet of Things device terminal is used to connect to the edge computing node through wireless communication, and is responsible for data collection, data encryption, key reception and update, and lightweight computing. Among them, data collection refers to collecting data from sensors or actuators, data encryption refers to encrypting data using symmetric keys stored locally, key reception and update refer to receiving encrypted keys from the edge computing node and updating the keys, and lightweight computing refers to performing simple encryption and decryption operations and communication protocol processing.

[0015] The edge computing node is connected to the Internet of Things device terminal through wireless communication, receives device data and distributes keys, is connected to the cloud database through the Internet, uploads encrypted data, is connected to the blockchain network through the Internet, uploads key metadata and operation logs, and is responsible for key management, data processing, local storage and caching, blockchain interaction, and security authentication. Among them, key management refers to generating, distributing, and updating symmetric keys, and encapsulating and unsealing. Data processing refers to verifying, generating indexes, and performing hash calculations on the encrypted data uploaded by the Internet of Things devices. Local storage and caching refer to temporarily storing keys and data to reduce the load on the cloud. Blockchain interaction refers to uploading key metadata and operation logs to the blockchain. Security authentication refers to authenticating the identity of the Internet of Things devices and performing access control.

[0016] The cloud database is connected to the edge computing nodes via the Internet to receive encrypted data, and is connected to the management console via the Internet to provide data query and management interfaces. It is mainly responsible for data storage, data query, data backup and recovery, and access control. Among them, data storage refers to storing encrypted data. Data query refers to quickly retrieving data based on indexes and key identifiers. Data backup and recovery refer to regularly backing up data and supporting disaster recovery. Access control refers to authenticating the permissions of the management console and data requests.

[0017] The blockchain network is connected to the edge computing nodes via the Internet to receive key metadata and operation logs, and is connected to the management console via the Internet to provide auditing and verification interfaces. It is mainly responsible for key metadata storage, operation log recording, decentralization and immutability, and audit support. Among them, key metadata storage refers to storing the metadata and lifecycle information of keys. Operation log recording refers to recording the operation logs of key generation, distribution, update, and destruction. Decentralization and immutability refer to ensuring the transparency and security of data through a consensus mechanism. Audit support refers to providing immutable operation records to support security audits.

[0018] The management console is connected to the cloud database via the Internet to query and manage data, is connected to the blockchain network via the Internet to view operation logs and audit information, and is connected to the edge computing nodes via the Internet to monitor and manage the key lifecycle. It is mainly responsible for key management, data management, audit and monitoring, and user management. Among them, key management refers to monitoring the key lifecycle and manually triggering key update or recovery operations. Data management refers to querying and retrieving encrypted data stored in the cloud database, and managing data backup and data recovery. Audit and monitoring refer to viewing the operation logs in the blockchain, ensuring system security, and monitoring the running status and performance metrics of the system. User management refers to managing the permissions and access controls of administrators and users.

[0019] For the connection methods of the above IoT device terminals, edge computing nodes, cloud databases, blockchain networks, and management consoles, see Figure 2 .

[0020] The specific implementation of the present invention includes the following steps: S1: System initialization and definition: Initialize the system, define data privacy degree evaluation indicators, configure the blockchain network, deploy smart contracts, and assign identifiers.

[0021] Furthermore, initializing the system specifically includes component deployment and configuration, establishing a secure channel, initializing the blockchain network, and configuring the management console.

[0022] Specifically in this embodiment, component deployment and configuration refer to deploying Internet of Things device terminals, edge computing nodes, cloud databases, blockchain networks, and management consoles, configuring the communication protocols between components, and assigning unique identifiers to all Internet of Things devices and edge computing nodes in the Internet of Things device terminals. Establishing a secure channel specifically means establishing a secure communication channel between Internet of Things devices and edge computing nodes, and establishing secure connections between edge computing nodes and cloud databases and blockchain networks. Initializing the blockchain network specifically means deploying smart contracts, storing key metadata and operation logs, and configuring the consensus mechanism and node permissions of the blockchain network. Configuring the management console specifically means configuring the user permissions and access control policies of the management console, setting audit and monitoring functions, and ensuring the visualization and transparency of system operation.

[0023] Furthermore, defining the data privacy degree evaluation index includes the following steps: A1: Determine the data privacy degree evaluation index and determine the data sensitivity classification; Specifically in this embodiment, the data privacy degree evaluation index is based on data type, data usage, privacy, data risk, and legal compliance. Among them, the data type refers to the nature and content of the data. For example, environmental data is low-sensitivity data, device status data is medium-sensitivity data, and personal privacy data is high-sensitivity data. Data usage refers to the usage scenarios and purposes of the data. For example, internal monitoring and analysis are low-sensitivity data, and commercial use is medium-sensitivity data. Privacy refers to whether the data contains personal identity information or sensitive personal information. For example, data that does not contain personal identity information is low-sensitivity data, data that contains personal identity information is medium-sensitivity data, and data that includes sensitive personal information is high-sensitivity data. Data risk refers to the losses caused by data leakage or tampering. For example, low-risk data corresponds to low sensitivity, medium-risk data corresponds to medium sensitivity, and high-risk data corresponds to high sensitivity. Legal compliance refers to whether the data complies with relevant laws and regulations. For example, data that does not require special protection is low-sensitivity, data that requires general protection is medium-sensitivity, and data that requires strict protection is high-sensitivity.

[0024] A2: Set the scoring criteria and define the scoring range and weight for different evaluation indexes; Specifically in this embodiment, setting the scoring criteria is used to quantify the data privacy degree. The scoring range corresponding to different evaluation indexes is determined to be 1-5, indicating the data sensitivity level from low to high from low to high. Weights are assigned to each evaluation index according to the importance of the evaluation index, and the sum of the weights is 1. For example, the weight coefficient of the data type is 0.2, the weight coefficient of the data usage is 0.2, the weight coefficient of the privacy is 0.4, the weight coefficient of the data risk is 0.1, and the weight coefficient of the legal compliance is 0.1.

[0025] A3: Divide the data privacy level according to the weighted scoring result; Specifically in this embodiment, the weighted scoring result of the data to be rated is calculated according to the above scoring criteria, and the data privacy level is divided into low privacy level (1 - 2 points), medium privacy level (2.1 - 3.5 points), and high privacy level (3.6 - 5 points).

[0026] A4: Assign labels to the privacy level classification for easy system identification and processing.

[0027] Specifically in this embodiment, labels are assigned to the privacy level classification. The label for low privacy level is "Low", the label for medium privacy level is "Medium", and the label for high privacy level is "High". This helps to simplify the process of data classification and management, provides basic support for the security, efficiency, and scalability of the system. The privacy level label provides a basis for the automated processing of the system. The system can automatically perform corresponding operations according to the label, reducing manual intervention and improving efficiency.

[0028] S2: Data collection and evaluation: Collect data through the IoT device terminal, classify the data according to the privacy level evaluation indicators, and attach the privacy level label to the data.

[0029] Furthermore, data collection and evaluation specifically include collecting data through the IoT devices in the IoT device terminal, classifying the collected data according to the predefined data privacy level evaluation indicators, attaching the corresponding privacy level label to the data according to the data privacy level, transmitting the data and the privacy level label to the edge computing node, and verifying the privacy level label.

[0030] Specifically in this embodiment, before data classification, the IoT device terminal needs to preprocess the collected data to ensure the integrity and consistency of the data, which specifically includes data cleaning, data formatting, and data annotation. Verifying the privacy level label specifically means that the edge computing node receives data from the IoT device terminal. The data contains the privacy level label. Extract the privacy level label from the received data. According to the predefined privacy level evaluation indicators, verify the accuracy of the privacy level label. Compare the calculated privacy level with the privacy level label. If they are consistent, the verification is successful; otherwise, the verification fails. According to the verification result, the edge computing node takes corresponding solutions. If the verification is successful, the edge computing node continues to process the data; if the verification fails, the edge computing node records the data and the reason for the verification failure in the log, and recalculates the privacy level score according to the data attributes and updates the privacy level label.

[0031] S3: Key generation and distribution: The edge computing node generates a key policy according to the data privacy level, securely distributes the key to the IoT device terminal, and uploads the key metadata to the blockchain network.

[0032] Furthermore, the generation of the key policy specifically refers to generating different key policies for data with different privacy levels. For data with low privacy level, a unified symmetric key is used to encrypt the low-privacy data, and the key is updated once a month. For data with medium privacy level, an independent symmetric key is assigned to each device, and the key is updated once a week. For data with high privacy level, an independent symmetric key is assigned to each piece of data, and the key is updated once per session. Additionally, asymmetric encryption is used to encapsulate and distribute the symmetric key.

[0033] Specifically in this embodiment, for data with low privacy level, a symmetric key such as AES-128 is generated, the key is distributed to all relevant IoT devices, and the key metadata is uploaded to the blockchain network. For data with medium privacy level, an independent symmetric key such as AES-192 is generated for each group of devices, the symmetric key is encapsulated using the public key of the device, and is securely distributed to the device, and the key metadata is uploaded to the blockchain network. For data with high privacy level, an independent symmetric key such as AES-256 is generated for each piece of data, the symmetric key is encapsulated using the public key of the device, and is securely distributed to the device, and the key metadata is uploaded to the blockchain network. This helps with fine-grained security control, optimizes the resource allocation efficiency, and compresses the storage cost.

[0034] S4: Data Encryption and Upload: The IoT device terminal uses the received key to encrypt the data and uploads the encrypted data to the edge computing node. The edge computing node processes the data and uploads it to the cloud database.

[0035] Furthermore, data encryption and upload includes the IoT device terminal receiving and storing the key, continuously collecting data, encrypting the data, and then uploading the data to the edge computing node; the edge computing node receives the encrypted data from the IoT device terminal, generates an index for the encrypted data based on the received data meta-information, and calculates the hash value of the encrypted data. The edge computing node uploads the encrypted data, the generated index, and the calculated hash value to the cloud database; the cloud database receives the data uploaded by the edge computing node through the Internet, verifies the data, checks the data format, ensures that the data comes from a legitimate edge computing node, and stores the verified data in the cloud database.

[0036] What needs to be specifically explained in this embodiment is that the IoT device terminal stores the received key securely in its internal secure storage area, such as a chip with encryption function, to prevent the key from being illegally obtained. The encrypted data is uploaded to the edge computing node. During the upload process, in order to ensure the integrity and reliability of data transmission, the device will encapsulate the encrypted data and add some necessary metadata, such as device identification, data type, timestamp and other information. The edge computing node parses the received message, extracts the encrypted data and related metadata information, and the data index is used to quickly locate and retrieve data in the cloud database. Storing the verified data in the cloud database will facilitate subsequent queries and use.

[0037] S5: Data query and recovery: The management console queries encrypted data through the cloud database. The edge computing node obtains key metadata from the blockchain network, unseals the key, and uses the unseal key to decrypt the encrypted data.

[0038] Furthermore, data query and recovery specifically include the following steps: B1: The management console operator enters query conditions in the management console based on business needs. The management console encapsulates the query conditions and sends a query request to the cloud database through a secure communication protocol. The cloud database receives the query request from the management console and verifies the request. After verification, the cloud database retrieves data based on the query conditions, encapsulates the queried encrypted data and related cloud data, and returns them to the management console.

[0039] Specifically, in this embodiment, the query conditions in the above steps can be device ID, data time range, and data type information. For example, in factory management, a worker wants to query the encrypted operating status data of a particular device for the past week. In the management console, they enter the device ID "DEVICE1" and the time range "2025-02-01 to 2025-02-07" and click the query button. The query request in the above steps should include the management console's identity authentication information, such as the data certificate and API key, to ensure the legitimacy of the query request.

[0040] B2: After receiving the encrypted data from the cloud database, the management console sends instructions to the edge computing node to unseal the key and decrypt the data. The instructions should include key information related to the encrypted data. After receiving the instructions from the management console, the edge computing node constructs a query request to the blockchain network based on the instruction information. The blockchain network searches for the corresponding key metadata based on the request and passes it to the edge computing node. It should be specifically noted in this embodiment that the key information contained in the instructions in the above steps can be the device ID and the data timestamp, which facilitates the edge computing node to accurately obtain the corresponding key metadata. The blockchain network stores the metadata related to the key, such as the generation time of the key, the update record, the key version number, and the encryption algorithm.

[0041] B3: The edge computing node determines the key version to be used and the corresponding encryption algorithm according to the received key metadata, obtains the encrypted key block from the local and other secure storage locations, and performs an unsealing operation on the encrypted key.

[0042] It should be specifically noted in this embodiment that the key metadata in the above steps can use the AES-256 encryption algorithm, and the key is stored in blocks and uses a specific encryption algorithm. The key blocks may be stored in the secure hard disk partition of the edge computing node, and each key block has a corresponding identifier. For example, the edge computing node reads the corresponding encrypted key block according to the key block identifier in the key metadata.

[0043] S6: Audit monitoring and fault tolerance: Real-time monitor the operation status of key management, calculate the comprehensive evaluation index of key management, recover damaged keys, and recover and encrypt lost data.

[0044] Furthermore, obtaining the operation status of key management requires real-time monitoring of the operation status parameters, specifically including the key usage frequency f1 of the IoT device terminal, the key unsealing efficiency η1 of the edge computing node, the data processing delay time t, and the node load rate η2, the data access frequency f2 of the cloud database, and the number of database connections X. The comprehensive evaluation index of key management is calculated through processing the operation status parameters.

[0045] It should be specifically noted in this embodiment that the key usage frequency refers to the number of times the IoT device uses the key for data encryption or decryption per unit time, which is used to reflect the actual usage of the key; the key unsealing efficiency refers to the average time for the edge computing node to obtain the key metadata from the blockchain network and unseal the key, which is used to measure the node's ability to process keys; the data processing delay time refers to the time for the edge computing node to process the encrypted data. Excessive delay may affect the overall performance of the system; the node load rate refers to the usage of resources such as CPU, memory, and storage, which is obtained through the system monitoring tool of the node. Excessive load may cause the node to run slowly or even fail; the data access frequency refers to the number of operations such as querying and reading encrypted data in the cloud database per unit time, which reflects the usage popularity of the data. Excessive access frequency may affect the database performance; the number of database connections refers to the number of current connections established with the cloud database. Too many connections may cause the database performance to decline, which can be obtained through the database management tool.

[0046] Further, to obtain the comprehensive evaluation index of key management, a time interval needs to be set and divided into unit sub-time regions according to the equal-time region division method, which are respectively labeled as 1, 2, …, i, …, n, and the key usage frequency f within any sub-time region is collected. 1i The sum of the key usage frequencies within any sub-time region is added and divided by n to obtain the average key usage frequency, and then divided by the maximum key usage frequency to obtain the management evaluation index K of the IoT device terminal. I The key decryption efficiency η within any sub-time region is collected. 1i The data processing delay time t i and the node load rate η 2i are obtained respectively. The average key decryption efficiency, the average data processing delay time, and the average node load rate, and the corresponding maximum values η 1max and t max and η 2max are used to calculate the management evaluation index K of the edge computing node by using the formula where ω1, ω2, and ω3 respectively represent the weight coefficients of the key decryption efficiency, the data processing delay time, and the node load rate, and the sum is 1; and the data access frequency f within any sub-time region is collected. e and the number of database connections X 2i The average data access frequency and the average number of database connections are obtained respectively, and the maximum data access frequency f i and the maximum number of database connections X 2max corresponding to them are obtained. The management evaluation index K of the cloud database is calculated by using the formula max where ρ1 and ρ2 respectively represent the weight coefficients of the data access frequency and the number of database connections, and the sum is 1. The comprehensive evaluation index RSI of key management is calculated by substituting the management evaluation index of the IoT device terminal, the management evaluation index of the edge computing node, and the management evaluation index of the cloud database into the formula where μ1, μ2, and μ3 respectively represent the weight coefficients of the management evaluation index of the IoT device terminal, the management evaluation index of the edge computing node, and the management evaluation index of the cloud database, and the sum is 1. c

[0047] ​​This embodiment requires specific explanation of the aforementioned weight coefficients, which must be set by personnel during use, and the impact of various parameters of IoT device terminals, edge computing nodes, and cloud databases on key management performance. The comprehensive key management evaluation index is used to determine whether there are any problems with the key management process, and to collect corresponding solutions. For example, a low parameter value for key decryption efficiency may indicate a problem with the key decryption process, necessitating further inspection of the connection between the edge computing node and the blockchain network.

[0048] What needs to be specifically explained in this embodiment is that to determine the location of the damaged key, it is necessary to analyze the log information and monitoring data of relevant components such as the Internet of Things device terminal, edge computing node, blockchain network, etc., to determine whether the damaged key has a problem during the storage process, or is lost or damaged during the transmission process. According to the monitoring parameters of the cloud database, it is judged whether the lost data was lost during the upload process to the cloud database, or a problem occurred during the storage process of the cloud database, and the data is restored from the backup, and the lost data is regenerated using the data redundancy and reconstruction mechanism.

[0049] Secondly: The drawings of the embodiments disclosed in the present invention only involve structures related to the embodiments disclosed in the present invention. Other structures may refer to conventional designs. The same embodiment and different embodiments of the present invention may be combined with each other without conflict. Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for managing keys of a cloud database based on the Internet of Things, characterized in that, It includes an Internet of Things device terminal, an edge computing node, a cloud database, a blockchain network, and a management console, which are connected through the Internet. Specifically, it includes the following steps: S1: System initialization and definition: Initialize the system, define data privacy degree evaluation metrics, configure the blockchain network, deploy smart contracts, and assign identifiers; S2: Data collection and evaluation: Collect data through the Internet of Things device terminal, classify the data according to the privacy degree evaluation metrics, and attach privacy degree labels to the data; S3: Key generation and distribution: The edge computing node generates a key policy according to the data privacy degree, securely distributes the key to the Internet of Things device terminal, and uploads the key metadata to the blockchain network; S4: Data encryption and upload: The Internet of Things device terminal uses the received key to encrypt the data, uploads the encrypted data to the edge computing node, and the edge computing node processes the data and uploads it to the cloud database; S5: Data query and recovery: The management console queries the encrypted data through the cloud database, the edge computing node obtains the key metadata from the blockchain network, unseals the key, and uses the unsealed key to decrypt the encrypted data; S6: Audit monitoring and fault tolerance: Real-time monitor the operation status of key management, calculate the comprehensive evaluation index of key management, recover damaged keys, and recover and encrypt lost data.

2. The method for managing keys of a cloud database based on the Internet of Things according to claim 1, wherein: The system initialization specifically includes component deployment and configuration, establishing a secure channel, initializing the blockchain network, and configuring the management console.

3. The method for managing keys of a cloud database based on the Internet of Things according to claim 1, characterized in that: The definition of data privacy degree evaluation metrics includes the following steps: A1: Determine the data privacy degree evaluation metrics and determine the data sensitivity classification; A2: Set the scoring criteria and define the scoring range and weight for different evaluation metrics; A3: Divide the data privacy degree levels according to the weighted scoring results; A4: Assign labels to the privacy degree levels for easy system identification and processing.

4. A method for managing keys of a cloud database based on the Internet of Things according to claim 1, characterized in that: The data collection and evaluation specifically includes collecting data through the Internet of Things devices in the Internet of Things device terminal, classifying the collected data according to the predefined data privacy degree evaluation metrics, attaching corresponding privacy degree labels to the data according to the data privacy degree, transmitting the data and the privacy degree labels to the edge computing node, and verifying the privacy degree labels.

5. A method for managing keys of a cloud database based on the Internet of Things according to claim 1, characterized in that: The generation of the key policy specifically refers to generating different key policies for data with different privacy degrees. Among them, for low-privacy data, a unified symmetric key is used to encrypt the low-privacy data, and the key is updated once a month; for medium-privacy data, an independent symmetric key is assigned to each device, and the key is updated once a week; for high-privacy data, an independent symmetric key is assigned to each piece of data, and the key is updated once per session, and the symmetric key is encapsulated and distributed in combination with asymmetric encryption.

6. The method for managing keys of a cloud database based on the Internet of Things according to claim 1, characterized in that: The data encryption and upload include that the IoT device terminal receives and stores keys, continuously collects data, encrypts the data, and then uploads the data to the edge computing node; the edge computing node receives the encrypted data from the IoT device terminal, generates an index for the encrypted data according to the received data element information, and calculates the hash value of the encrypted data. The edge computing node uploads the encrypted data, the generated index, and the calculated hash value to the cloud database; The cloud database receives the data uploaded by the edge computing node through the Internet, verifies the data, checks the data format to ensure that the data comes from a legitimate edge computing node, and stores the verified data in the cloud data.

7. A method for managing keys of a cloud database based on the Internet of Things according to claim 1, characterized in that: The data query and recovery specifically include the following steps: B1: The operator of the management console inputs the query conditions on the management console according to the business requirements. The management console encapsulates the query conditions and sends a query request to the cloud database through the secure communication protocol. The cloud database receives the query request from the management console, verifies the request. After the verification passes, the cloud database retrieves the data according to the query conditions, and encapsulates the retrieved encrypted data and related cloud data and returns them to the management console; B2: After receiving the encrypted data returned by the cloud database, the management console sends an instruction to decrypt the key and the data to the edge computing node. The instruction should contain the key information related to the encrypted data. After receiving the instruction from the management console, the edge computing node constructs a query request for the blockchain network according to the instruction information. The blockchain network searches for the corresponding key metadata according to the request and passes it to the edge computing node; B3: The edge computing node determines the key version and the corresponding encryption algorithm to be used according to the received key metadata, obtains the encrypted key blocks from the local and other secure storage locations, and performs an unsealing operation on the encrypted key.

8. A method for managing keys of a cloud database based on the Internet of Things according to claim 1, characterized in that: Obtaining the running state of the key management requires real-time monitoring of the running state parameters, specifically including the key usage frequency f1 of the IoT device terminal, the key unsealing efficiency η1, the data processing delay time t, and the node load rate η2 of the edge computing node, the data access frequency f2 and the database connection number X of the cloud database. The comprehensive evaluation index of the key management is calculated through the processing of the running state parameters.

9. The method for managing keys of a cloud database based on the Internet of Things according to claim 1, wherein: The acquisition of the comprehensive evaluation index of key management requires setting a time interval, which is divided into unit sub-time regions according to the equal-time region division method, and is respectively labeled as 1, 2, …, i, …, n, and the key usage frequency f within any sub-time region is collected 1i , the key usage frequencies within any sub-time region are added up and divided by n to obtain the average key usage frequency, and then divided by the maximum value of the key usage frequency to obtain the management evaluation index K of the IoT device terminal I , the key decryption efficiency η within any sub-time region is collected 1i , the data processing delay time t i and the node load rate η 2i , the average key decryption efficiency, the average data processing delay time and the average node load rate are respectively obtained, and the corresponding maximum values η 1max , t max and η 2max , using the formula Calculate the edge computing node management evaluation index K e , where ω1, ω2, and ω3 represent the weight coefficients of key decryption efficiency, data processing delay time, and node load rate, respectively, and the sum is 1; and the data access frequency f in any sub-time region is collected 2i Number of database connections X i , respectively obtain the average data access frequency and the average number of database connections, and the corresponding maximum data access frequency f 2max The maximum number of database connections is X max , and using the formula Calculate the cloud database management evaluation index K c , where ρ1 and ρ2 respectively represent the weight coefficients of data access frequency and the number of database connections, and the sum is 1. Substitute the Internet of Things device terminal management evaluation index, edge computing node management evaluation index, and cloud database management evaluation index into the formula The comprehensive evaluation index RSI of key management is calculated. μ1, μ2, and μ3 represent the weight coefficients of the management evaluation index of IoT device terminals, the management evaluation index of edge computing nodes, and the management evaluation index of cloud databases respectively, and their sum is 1.

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