Urban operations data monitoring system, method, device, and computer readable medium

Abstract

Embodiments of the present disclosure disclose a city operation data monitoring system, method, device and computer readable medium. A specific embodiment of the system comprises: a city operation data uploading node configured to encrypt city operation data; uploading the encrypted city operation data to a city operation data storage cluster; a city operation data access node configured to send data request information to a node monitoring cluster; obtaining the encrypted city operation data from the city operation data storage cluster; decrypting the encrypted city operation data to obtain city operation data; and monitoring the obtained city operation data. The embodiment can reduce the computing resources and time consumed by the city operation data monitoring system in monitoring city operation data, improve the security of the data and the stability of the city operation monitoring system, and reduce the occurrence of single-point failure of the city operation monitoring system.

Description

Technical Field

[0001] Embodiments of this disclosure relate to the field of computer technology, and more specifically to urban operation data monitoring systems, methods, devices, and computer-readable media. Background Technology

[0002] A city operation data monitoring system is used to share and monitor city operation data containing a large amount of data that needs to be encrypted (sensitive data). For example, sensitive data could include the identity information of individuals who violate traffic rules. Currently, the main approach is to integrate the original CP-ABE (Ciphertext Policy Attribute Base Encryption) method into the city operation data monitoring system to implement access control for multi-user, multi-terminal data, either for monitoring the city operation data or for direct sharing of city operation data between various nodes (servers) to achieve city operation data monitoring.

[0003] However, in practice, it has been found that when using the above methods to monitor urban operation data, the following technical problems often arise:

[0004] When various nodes (servers) directly share city operation data for monitoring, the lack of preprocessing of the city operation data results in low data security and a high risk of data leakage. When the original CP-ABE method is integrated into the city operation data monitoring system, the original CP-ABE method relies on a trusted third party, resulting in low data security and a single point of failure when a node (server) in the city operation monitoring system fails.

[0005] The information disclosed in this background section is only intended to enhance the understanding of the background of the inventive concept, and therefore may contain information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] The summary portion of this disclosure is intended to provide a brief overview of the concepts, which will be described in detail in the detailed description portion. This summary portion is not intended to identify key or essential features of the claimed technical solutions, nor is it intended to limit the scope of the claimed technical solutions.

[0007] Some embodiments of this disclosure provide urban operation data monitoring systems, methods, electronic devices, and computer-readable media to address one or more of the technical problems mentioned in the background section above.

[0008] In a first aspect, some embodiments of this disclosure provide a city operation data monitoring system, including a city operation data upload node, a city operation data access node, a node monitoring cluster, and a city operation data storage cluster; the city operation data upload node is configured to encrypt city operation data to obtain encrypted city operation data; upload the encrypted city operation data to the city operation data storage cluster; the city operation data storage cluster is configured to store the received encrypted city operation data; send the storage address information corresponding to the encrypted city operation data to the city operation data upload node corresponding to the encrypted city operation data; the node monitoring cluster is configured to receive user registration information... The system processes user registration requests by registering the corresponding user nodes to obtain user registration information. This user registration information is then sent to the corresponding user nodes, where the node monitoring cluster deploys a first blockchain and a second blockchain. The city operation data access nodes are configured to send data request information to the node monitoring cluster. Based on the secondary encrypted data details sent by the node monitoring cluster, encrypted city operation data corresponding to the data request information is obtained from the city operation data storage cluster. The obtained encrypted city operation data is then decrypted to obtain the city operation data corresponding to the data request information. Finally, the obtained city operation data is monitored and processed.

[0009] Secondly, some embodiments of this disclosure provide a method for monitoring urban operation data, applied to the aforementioned urban operation data monitoring system, comprising: preprocessing urban operation data to obtain preprocessed urban operation data; combining the preprocessed urban operation data to obtain combined urban operation data; visualizing the combined urban operation data; determining a warning level information corresponding to the combined urban operation data based on the combined urban operation data; in response to determining that the warning level information meets preset warning conditions, highlighting the warning information and sending the warning information to an associated terminal device to monitor and process the aforementioned urban operation data.

[0010] Thirdly, some embodiments of this disclosure provide an electronic device, including: one or more processors; and a storage device having one or more programs stored thereon, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any of the implementations of the second aspect above.

[0011] Fourthly, some embodiments of this disclosure provide a computer-readable medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method described in any of the implementations of the second aspect above.

[0012] The above-described embodiments of this disclosure have the following beneficial effects: the urban operation data monitoring system of some embodiments of this disclosure improves data security, reduces the occurrence of single points of failure, and further shortens the time spent on detecting urban operation data and reduces the computational resources consumed. Specifically, the reasons for low data security, frequent single points of failure, long detection time for urban operation data, and high computational resource consumption are as follows: when various nodes (servers) directly share urban operation data for monitoring, no preprocessing of the urban operation data is considered, resulting in low data security and a high risk of data leakage; when the original CP-ABE method is integrated into the urban operation data monitoring system, the original CP-ABE method relies on a trusted third party, resulting in low data security and a high risk of single points of failure when a node (server) fails in the urban operation monitoring system. Based on this, some embodiments of the urban operation data monitoring system disclosed herein include an urban operation data upload node, an urban operation data access node, a node monitoring cluster, and an urban operation data storage cluster; and the aforementioned urban operation data upload node is configured to first encrypt the urban operation data to obtain encrypted urban operation data. Thus, encrypted urban operation data can be obtained. Then, the encrypted urban operation data is uploaded to the aforementioned urban operation data storage cluster. Thus, the encrypted urban operation data can be stored, reducing the storage space consumption of the urban operation data upload node. The aforementioned urban operation data storage cluster is configured to first store the received encrypted urban operation data. Thus, the encrypted urban operation data can be stored in the urban operation data storage cluster. Then, the storage address information corresponding to the aforementioned encrypted urban operation data is sent to the corresponding urban operation data upload node. Thus, the urban operation data upload node can obtain the storage address information of the encrypted urban operation data. The aforementioned node monitoring cluster is configured to first register the user node corresponding to the received user registration request information to obtain user registration information. Therefore, user nodes can be registered, enabling them to upload or access city operation data stored in the city operation data storage cluster within the city operation data monitoring system. Then, the user registration information is sent to the corresponding user node, where the node monitoring cluster deploys a first blockchain and a second blockchain. This allows registered users to obtain their registration information. The city operation data access node is configured to first send data request information to the node monitoring cluster. Thus, the node monitoring cluster can authenticate the city operation data access node.Then, based on the secondary encrypted data details sent by the aforementioned node monitoring cluster, encrypted city operation data corresponding to the aforementioned data request information is obtained from the aforementioned city operation data storage cluster. Thus, the city operation data access node can obtain the requested encrypted city operation data from the city operation data storage cluster. Afterwards, the obtained encrypted city operation data is decrypted to obtain the city operation data corresponding to the aforementioned data request information. Thus, decrypted city operation data can be obtained. Finally, the obtained city operation data is monitored. This allows for monitoring and processing of city operation data, enabling timely detection of risks within the data. Because the city operation data monitoring system uses blockchain for decentralization, rather than directly relying on a trusted third party, data security is improved, and single points of failure are reduced, enhancing the stability and security of the city operation data monitoring system. Furthermore, because the node monitoring cluster included in the city operation data monitoring system represents blockchain consortium nodes, dynamic node (server) access and exit can be achieved, reducing the time spent on node (server) access and exit and the wasted computing resources. The use of dynamic consortium nodes also improves the stability of the city operation data monitoring system. Furthermore, because the data is not shared directly with the city's operational data, but rather after each node registers and encrypts the data, data security is enhanced and the risk of data leakage is reduced. This reduces the computational resources and time required for the city's operational data monitoring system, improves data security and the stability of the system, and reduces the likelihood of single points of failure. Attached Figure Description

[0013] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and elements are not necessarily drawn to scale.

[0014] Figure 1 This is a timing diagram of some embodiments of the urban operation data monitoring system according to this disclosure;

[0015] Figure 2 This is a flowchart of some embodiments of the urban operation data monitoring method according to this disclosure;

[0016] Figure 3 This is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. Detailed Implementation

[0017] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0018] It should also be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other.

[0019] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0020] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0021] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0022] This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0023] Figure 1 A timing diagram is shown for some embodiments of an urban operation data monitoring system according to this disclosure.

[0024] like Figure 1 As shown, a city operation data monitoring system includes: city operation data upload nodes, city operation data access nodes, node monitoring clusters, and city operation data storage clusters. The interaction steps between the aforementioned city operation data upload nodes, city operation data access nodes, node monitoring clusters, and city operation data storage clusters may include the following steps:

[0025] Step 101: The node monitoring cluster registers the user node corresponding to the received user registration request information to obtain the user registration information.

[0026] In some embodiments, the node monitoring cluster can register the user node corresponding to the received user registration request information to obtain user registration information. The city operation data upload node can represent a server that uploads city operation data. The city operation data access node can represent a server that acquires city operation data. The node monitoring cluster can represent a consortium node of the blockchain. The node monitoring cluster can be various servers monitoring the city operation data upload node and the city operation data access node. The city operation data monitoring system can include a first blockchain for storing user identification information and a set of user attribute information, and a second blockchain for storing city operation data and encrypted ciphertext information. Both the first and second blockchains can be consortium blockchains. The user attribute information in the user attribute information set can represent the attributes of the user node corresponding to the user identification information. For example, the user attribute information can be: "Attribute Name: Identifier (DID); Identifier (DID) is: 123456xxx". The node monitoring cluster is deployed with smart contracts corresponding to the first blockchain and smart contracts corresponding to the second blockchain. The city operation data can include various data information of the target city. The target city can be any city. The data information mentioned above can represent transportation data, emergency data, population and employment data, or industry data. For example, city operation data could be: "Transportation data: x vehicles were transported in the target city on month x; Emergency data: a fire occurred in the target city on month x; Population and employment data: the employment rate in 2023 was 70%; and Industry data: x electronic products were produced in the target city in month x." The city operation data storage cluster mentioned above can represent the various servers used to store the city operation data. The user registration request information mentioned above can represent the statement by which a user node requests the generation of user registration information. The user registration request information mentioned above can include user identification information. The user identification information mentioned above can represent the identifier (DID) of the user node. For example, the user registration request information could be: "The user node with identifier xx requests the generation of user registration information." The user node mentioned above can be any city operation data upload node or any city operation data access node.

[0027] In some optional implementations of certain embodiments, before the node monitoring cluster registers the user node corresponding to the received user registration request information and obtains the user registration information, it can be further configured to perform the following steps:

[0028] The first step is to generate a target value set based on preset values. These preset values ​​can represent the generators of a cyclic group. The specific setting of these preset values ​​is not limited here. For example, the preset value could be 'b'. The target value set can represent a cyclic group of order 'a'. 'a' can be a prime number. The target data set can include 'a' elements. The value of 'a' is not specifically limited here. In practice, for each preset order in the preset order set, the node monitoring cluster can determine the target value as the power of the preset order of the preset value, thus obtaining the target value set.

[0029] The second step is to select two target values ​​from the aforementioned set of target values ​​as the first encryption parameter and the second encryption parameter. In practice, the node monitoring cluster can select any two distinct target values ​​from the aforementioned set of target values ​​as the first encryption parameter and the second encryption parameter.

[0030] The third step involves encrypting the preset value according to the second encryption parameter to obtain a second encrypted preset value. This second encrypted preset value represents the encrypted preset value. In practice, the node monitoring cluster can determine the second encrypted preset value by raising the preset value to the power of the second encryption parameter.

[0031] The fourth step involves determining the first encryption parameter and the second encryption preset value as the main encryption information. This main encryption information can represent the master key of the corresponding city operation data monitoring system.

[0032] Fifth, based on the first encryption parameter, the preset value is encrypted to obtain the first encrypted preset value. In practice, the node monitoring cluster can determine the first encrypted preset value by raising the preset value to the power of the first encryption parameter.

[0033] Step 6: Generate constraint values ​​based on the aforementioned preset values. These constraint values ​​can represent the preset values ​​after bilinear mapping. In practice, the aforementioned node monitoring cluster can use a bilinear mapping function to perform bilinear mapping on the preset values ​​to obtain the constraint values.

[0034] Step 7: Based on the second encryption parameter mentioned above, encrypt the constraint value to obtain the encrypted constraint value. This encrypted constraint value represents the encrypted constraint value. In practice, the node monitoring cluster can determine the encrypted constraint value by raising the second encryption parameter to the power of the constraint value.

[0035] Step 8: The aforementioned target value set, the aforementioned preset value, the aforementioned first encryption preset value, and the aforementioned encryption constraint value are determined as the encryption public key information. The aforementioned encryption public key information can represent the public key of the aforementioned city operation data monitoring system.

[0036] However, in practice, it has been found that in the process of adopting technical solutions to solve the aforementioned technical problem one, the following technical problems often arise: When sharing city operation data directly through commonly used nodes (servers), the following technical problems often occur: Without considering the registration of each node (server), any node can participate in data sharing, making city operation data vulnerable to unauthorized access, interception, or leakage by third parties, resulting in low security and reliability of the city operation data. To address these problems, the conventional solution is generally to directly grant designated nodes (servers) permission to participate in city operation data monitoring. Considering the drawbacks of directly granting designated nodes (servers) permission to participate in city operation data monitoring, and combining this with the advantages of the inventor's company in data security sharing, we have decided to adopt the following solution:

[0037] In some optional implementations of certain embodiments, the node monitoring cluster may be further configured to perform the following steps to register the user node corresponding to the received user registration request information, thereby obtaining user registration information:

[0038] The first step is to verify the aforementioned user registration request information to obtain verification result information. This verification result information indicates whether the verification of the user registration request information was successful or failed. In practice, the aforementioned node monitoring cluster can use the DID system to verify the user identification information included in the user registration request information to obtain verification result information.

[0039] The second step, in response to the confirmation that the above verification result information indicates successful verification, determines the user attribute information set, user public encrypted information, and user private encrypted information corresponding to the user identification information included in the above user registration request information. The user public encrypted information can represent the public key of the user node corresponding to the above user identification information. The user private encrypted information can represent the private key of the user node corresponding to the above user identification information. In practice, firstly, the node monitoring cluster can determine the preset user attribute information set whose identifiers (DIDs) included in the preset user attribute information set are the same as the user identification information included in the above user registration request information as the user attribute information set corresponding to the above user registration request information. Then, the node monitoring cluster can determine the preset public-private key pairs whose identifiers (DIDs) corresponding to the identifiers (DIDs) included in the preset public-private key pair set are the same as the user identification information included in the above user registration request information as the user public encrypted information and user private encrypted information corresponding to the above user registration request information. The preset public-private key pairs in the preset public-private key pair set can represent the public key and private key of the user node.

[0040] The third step is to select a target value from the above set of target values ​​as the third encryption parameter.

[0041] The fourth step involves generating random encrypted information based on the first, second, and third encryption parameters, and the preset value. This random encrypted information can represent random elements in the attribute private key. In practice, the node monitoring cluster first determines the first value by the sum of the second and third encryption parameters. Then, the ratio of the first value to the first encryption parameter is determined as the second value. Finally, the second power of the preset value is used to determine the random encrypted information.

[0042] Fifth, based on the aforementioned target value set, the aforementioned user attribute information set is encrypted to obtain an encrypted attribute information set. This encrypted attribute information set represents the encrypted user attribute information set. In practice, for the user attribute information in the aforementioned user attribute information set, firstly, the aforementioned node monitoring cluster can randomly select a target value from the aforementioned target value set as a random value. Then, the random power of the aforementioned preset value is used to determine the encrypted attribute information. Finally, the resulting encrypted attribute information is used to define the encrypted attribute information set.

[0043] The sixth step is to determine the above-mentioned random encrypted information, the above-mentioned set of encrypted attribute information, the user's public encrypted information, and the user's private encrypted information as user registration information.

[0044] The above-described technical solution, as an inventive point of this disclosure, solves the technical problem of "low security and reliability of urban operation data." Factors leading to low security and reliability of urban operation data often include: failure to register each node (server), allowing any node to participate in data sharing, making urban operation data vulnerable to unauthorized access, interception, or leakage by third parties. Solving these factors can improve the security and reliability of urban operation data. To achieve this, when monitoring urban operation data, this disclosure first verifies the user registration request information received from nodes. Then, it generates random encrypted information for the corresponding node, the aforementioned set of encrypted attribute information, user public encrypted information, and user private encrypted information to obtain user registration information. Therefore, when monitoring urban operation data, node (server) registration can be implemented, thereby improving the security and reliability of urban operation data during monitoring.

[0045] Step 102: The node monitoring cluster sends the above user registration information to the user node corresponding to the above user registration request information.

[0046] In some embodiments, the node monitoring cluster can send the aforementioned user registration information to the user node corresponding to the user registration information. In practice, the node monitoring cluster can send the aforementioned user registration information to the user node corresponding to the user identification information included in the aforementioned user registration request information.

[0047] Optionally, after step 102, the aforementioned node monitoring cluster can upload the user identification information and the set of user attribute information included in the aforementioned user registration request information to the aforementioned first blockchain.

[0048] Step 103: The city operation data upload node encrypts the city operation data to obtain encrypted city operation data.

[0049] In some embodiments, the city operation data uploading node can encrypt the city operation data to obtain encrypted city operation data. The aforementioned city operation data can be the city operation data received by the city operation data uploading node. The encrypted city operation data can represent the encrypted city operation data. In practice, the city operation data uploading node can use an encryption algorithm and preset encryption information to encrypt the city operation data to obtain encrypted city operation data. The preset encryption information can represent the file encryption key. For example, the encryption algorithm can be the AES algorithm.

[0050] Step 104: The city operation data upload node uploads the encrypted city operation data to the aforementioned city operation data storage cluster.

[0051] In some embodiments, the aforementioned city operation data upload node can upload encrypted city operation data to the aforementioned city operation data storage cluster. In practice, the city operation data upload node can upload encrypted city operation data to the aforementioned city operation data storage cluster based on the IP address of the aforementioned city operation data storage cluster.

[0052] Step 105: The city operation data storage cluster stores the received encrypted city operation data.

[0053] In some embodiments, the city operation data storage cluster can store the received encrypted city operation data. In practice, firstly, the city operation data storage cluster can allocate storage space for the received encrypted city operation data. Then, the received encrypted city operation data can be stored in the aforementioned storage space. Afterward, the storage address corresponding to the aforementioned storage space can be determined as the storage address information for the received encrypted city operation data.

[0054] Step 106: The city operation data storage cluster sends the storage address information corresponding to the encrypted city operation data to the city operation data upload node corresponding to the encrypted city operation data.

[0055] In some embodiments, the aforementioned city operation data storage cluster can send the storage address information corresponding to the encrypted city operation data to the city operation data upload node corresponding to the encrypted city operation data.

[0056] Optionally, after step 106, the aforementioned city operation data upload node can be further configured to perform the following steps:

[0057] The first step is to encrypt the preset encrypted information to obtain encrypted ciphertext information. This encrypted ciphertext information represents the ciphertext of the preset encrypted information. In practice, the aforementioned city operation data upload node can use an encryption algorithm to encrypt the preset encrypted information to obtain encrypted ciphertext information. For example, the encryption algorithm can be an attribute-based encryption algorithm.

[0058] The second step is to extract keywords from the encrypted city operation data to obtain a keyword set. These keywords represent the words within the encrypted city operation data. In practice, the city operation data uploading node can use the TF-IDF keyword extraction algorithm to extract keywords from the encrypted city operation data, thus obtaining the corresponding keyword set.

[0059] The third step involves hashing the aforementioned encrypted city operation data to obtain encrypted data hash information. This hash information characterizes the hashed encrypted city operation data. In practice, the nodes uploading the aforementioned city operation data can use a hash algorithm to hash the encrypted city operation data to obtain the encrypted data hash information.

[0060] The fourth step involves determining the storage address information, keyword set, encrypted data hash information, and encrypted ciphertext information sent by the aforementioned city operation data storage cluster as the encrypted data details information corresponding to the aforementioned city operation data. The storage address information represents the storage address of the aforementioned city operation data.

[0061] The fifth step involves signing the encrypted data details to obtain the signature information. In practice, the city operation data upload node can use a signature algorithm to sign the encrypted data details to obtain the signature information. For example, the signature algorithm could be the RSA signature algorithm.

[0062] The sixth step is to send the encrypted data details and the signature information to the node monitoring cluster.

[0063] Optionally, after step 106, the aforementioned city operation data uploading node can also upload the aforementioned city operation data and encrypted ciphertext information to the aforementioned second blockchain.

[0064] In some optional implementations of certain embodiments, after the city operation data uploading node sends the encrypted data details and the signature information to the node monitoring cluster, the node monitoring cluster can be further configured to perform the following steps:

[0065] The first step involves receiving encrypted data details and signature information from the aforementioned city operation data upload node. The received signature information is then verified to obtain a signature verification result. This signature verification result indicates whether the verification passed or failed. In practice, the node monitoring cluster can use the RSA signature mechanism to verify the received signature information and obtain the signature verification result.

[0066] The second step involves storing the received encrypted data details in response to the confirmation that the signature verification result indicates successful verification. In practice, the aforementioned node monitoring cluster can store the received encrypted data details in a database that stores encrypted data details.

[0067] Step 107: The city operation data access node sends the data request information to the aforementioned node monitoring cluster.

[0068] In some embodiments, the aforementioned city operation data access node can send data request information to the aforementioned node monitoring cluster. The data request information may include node identification information and a set of requested data keywords. The set of requested data keywords can represent various keywords related to the requested data. For example, the set of data keywords could represent "traffic, fire, employment".

[0069] Step 108: The city operation data access node obtains the encrypted city operation data corresponding to the data request information from the city operation data storage cluster based on the secondary encrypted data details information sent by the node monitoring cluster.

[0070] In some embodiments, the aforementioned city operation data access node can obtain encrypted city operation data corresponding to the aforementioned data request information from the aforementioned city operation data storage cluster based on the secondary encrypted data details information sent by the aforementioned node monitoring cluster.

[0071] In some optional implementations of certain embodiments, before the city operation data access node obtains the encrypted city operation data corresponding to the data request information from the city operation data storage cluster based on the secondary encrypted data details information sent by the node monitoring cluster, the node monitoring cluster may be further configured to perform the following steps:

[0072] The first step involves receiving a data request from the aforementioned city operation data access node, and then performing registration verification processing on the city operation data access node to obtain registration verification result information. This registration verification result information indicates whether the verification of the city operation data access node has passed. In practice, firstly, the node monitoring cluster can determine whether the user node corresponding to the aforementioned city operation data access node has registered using the node's identifier. Then, in response to determining that the user node corresponding to the aforementioned city operation data access node has registered, the verification passing result is designated as the registration verification result information for that city operation data access node. Finally, in response to determining that the user node corresponding to the aforementioned city operation data access node has not registered, the verification failing result is designated as the registration verification result information for that city operation data access node.

[0073] The second step involves, in response to the confirmation that the registration verification result indicates successful verification, obtaining encrypted data details information corresponding to the request data keyword set included in the data request information, based on the node identifier information included in the data request information. In practice, the node monitoring cluster can obtain encrypted data details information containing each keyword from the request data keyword set from the database storing the encrypted data details information.

[0074] The third step is to obtain the publicly encrypted user information for the corresponding city operation data access nodes.

[0075] The fourth step involves encrypting the obtained encrypted data details based on the publicly available encrypted information of the users accessing the aforementioned city operation data nodes, resulting in secondary encrypted data details. This secondary encrypted data details represent the encrypted data details obtained after encryption. In practice, the executing entity can use an encryption algorithm to encrypt the obtained encrypted data details to obtain the secondary encrypted data details. For example, the encryption algorithm could be AES.

[0076] The fifth step is to send the obtained secondary encrypted data details to the aforementioned city operation data access node.

[0077] In some optional implementations of certain embodiments, the city operation data access node may be further configured to perform the following steps to obtain encrypted city operation data corresponding to the data request information from the city operation data storage cluster based on the secondary encrypted data details information sent by the node monitoring cluster:

[0078] The first step involves decrypting the received user-encrypted private information to obtain the encrypted data details corresponding to the data request. In practice, city operation data access nodes can use an encryption algorithm to decrypt the encrypted data details to obtain the encrypted data details corresponding to the data request. For example, the encryption algorithm could be RSA.

[0079] The second step is to obtain the encrypted city operation data corresponding to the above-mentioned storage address information from the city operation data storage cluster based on the storage address information included in the encrypted data details information corresponding to the above-mentioned data request information.

[0080] Step 109: The city operation data access node decrypts the acquired encrypted city operation data to obtain the city operation data corresponding to the above data request information.

[0081] In some embodiments, the aforementioned city operation data access node can decrypt the acquired encrypted city operation data to obtain the city operation data corresponding to the aforementioned data request information. In practice, the city operation data access node can decrypt the encrypted ciphertext information included in the aforementioned encrypted data details using the aforementioned user-private encrypted information, and then obtain the decrypted encrypted ciphertext information. Subsequently, an encryption algorithm is used to decrypt the acquired encrypted city operation data based on the decrypted encrypted ciphertext information to obtain the city operation data corresponding to the aforementioned data request information. For example, the encryption algorithm can be the AES algorithm.

[0082] Step 110: The city operation data access node monitors and processes the obtained city operation data.

[0083] In some embodiments, the aforementioned city operation data access node can monitor and process the obtained city operation data. In practice, firstly, for each piece of data in the aforementioned city operation data, the executing entity can input the data information into a pre-trained early warning information generation model to obtain early warning information for that data information. Thus, various early warning messages corresponding to the aforementioned city operation data can be obtained. The early warning information in each of these messages can represent the early warning level of the data information. For example, the early warning information can be "Level 1 Early Warning". The aforementioned early warning information generation model can be a model that takes the data information in the city operation data as input and outputs the corresponding early warning information. For example, the early warning information generation model can be a decision tree model. Then, in response to determining that the obtained early warning information meets preset early warning conditions, the obtained early warning information is displayed. The preset early warning conditions can be that the early warning level represented by the early warning information is Level 1, Level 2, or Level 3.

[0084] It should be noted that the specific implementation method for the city operation data access node to monitor and process the obtained city operation data can also be found in [reference needed]. Figure 2 An example of the urban operation data monitoring method described herein.

[0085] The above-described embodiments of this disclosure have the following beneficial effects: the urban operation data monitoring system of some embodiments of this disclosure improves data security, reduces the occurrence of single points of failure, and further shortens the time spent on detecting urban operation data and reduces the computational resources consumed. Specifically, the reasons for low data security, frequent single points of failure, long detection time for urban operation data, and high computational resource consumption are as follows: when various nodes (servers) directly share urban operation data for monitoring, no preprocessing of the urban operation data is considered, resulting in low data security and a high risk of data leakage; when the original CP-ABE method is integrated into the urban operation data monitoring system, the original CP-ABE method relies on a trusted third party, resulting in low data security and a high risk of single points of failure when a node (server) fails in the urban operation monitoring system. Based on this, some embodiments of the urban operation data monitoring system disclosed herein include an urban operation data upload node, an urban operation data access node, a node monitoring cluster, and an urban operation data storage cluster; and the aforementioned urban operation data upload node is configured to first encrypt the urban operation data to obtain encrypted urban operation data. Thus, encrypted urban operation data can be obtained. Then, the encrypted urban operation data is uploaded to the aforementioned urban operation data storage cluster. Thus, the encrypted urban operation data can be stored, reducing the storage space consumption of the urban operation data upload node. The aforementioned urban operation data storage cluster is configured to first store the received encrypted urban operation data. Thus, the encrypted urban operation data can be stored in the urban operation data storage cluster. Then, the storage address information corresponding to the aforementioned encrypted urban operation data is sent to the corresponding urban operation data upload node. Thus, the urban operation data upload node can obtain the storage address information of the encrypted urban operation data. The aforementioned node monitoring cluster is configured to first register the user node corresponding to the received user registration request information to obtain user registration information. Therefore, user nodes can be registered, enabling them to upload or access city operation data stored in the city operation data storage cluster within the city operation data monitoring system. Then, the user registration information is sent to the corresponding user node, where the node monitoring cluster deploys a first blockchain and a second blockchain. This allows registered users to obtain their registration information. The city operation data access node is configured to first send data request information to the node monitoring cluster. Thus, the node monitoring cluster can authenticate the city operation data access node.Then, based on the secondary encrypted data details sent by the aforementioned node monitoring cluster, encrypted city operation data corresponding to the aforementioned data request information is obtained from the aforementioned city operation data storage cluster. Thus, the city operation data access node can obtain the requested encrypted city operation data from the city operation data storage cluster. Afterwards, the obtained encrypted city operation data is decrypted to obtain the city operation data corresponding to the aforementioned data request information. Thus, decrypted city operation data can be obtained. Finally, the obtained city operation data is monitored. This allows for monitoring and processing of city operation data, enabling timely detection of risks within the data. Because the city operation data monitoring system uses blockchain for decentralization, rather than directly relying on a trusted third party, data security is improved, and single points of failure are reduced, enhancing the stability and security of the city operation data monitoring system. Furthermore, because the node monitoring cluster included in the city operation data monitoring system represents blockchain consortium nodes, dynamic node (server) access and exit can be achieved, reducing the time spent on node (server) access and exit and the wasted computing resources. The use of dynamic consortium nodes also improves the stability of the city operation data monitoring system. Furthermore, because the data is not shared directly with the city's operational data, but rather after each node registers and encrypts the data, data security is enhanced and the risk of data leakage is reduced. This reduces the computational resources and time required for the city's operational data monitoring system, improves data security and the stability of the system, and reduces the likelihood of single points of failure.

[0086] The following is for reference. Figure 2 The flowchart 200 illustrates some embodiments of the urban operation data monitoring method according to this disclosure. The urban operation data monitoring method includes the following steps:

[0087] Step 201: Preprocess the city operation data to obtain preprocessed city operation data.

[0088] In some embodiments, the implementing entity of the urban operation data monitoring method (e.g., an urban operation data access node) can preprocess the urban operation data to obtain preprocessed urban operation data. The aforementioned urban operation data can be obtained through methods such as... Figure 1 The data was obtained from the city's operational data monitoring system.

[0089] However, in practice, it has been found that in the process of adopting technical solutions to solve the above-mentioned technical problem one, the following technical problems often arise:

[0090] When monitoring urban operational data directly, the following technical problems often arise: Direct monitoring and processing of urban operational data, the presence of redundant and erroneous data without preprocessing, leads to high computational resource consumption for monitoring redundant and erroneous data, and long monitoring time. Conventional solutions to these problems typically involve simply deleting duplicate data from the urban operational data. However, considering the shortcomings of simply deleting duplicate data and leveraging the data processing advantages of our company, we have decided to adopt the following solution:

[0091] In some optional implementations of certain embodiments, the entity executing the urban operation data monitoring method can preprocess the urban operation data through the following steps to obtain preprocessed urban operation data:

[0092] The first step is to determine whether any data in the aforementioned city operation data meets the preset missing data condition. The aforementioned city operation data can include various data entries. The preset missing data condition can be the presence of missing values ​​in the data. In practice, the executing entity can use the `isna()` function in Pandas to determine whether any data in the aforementioned city operation data meets the preset abnormal data condition.

[0093] The second step is to determine, in response to the determination that there is data information in the above-mentioned city operation data that meets the above-mentioned preset missing data conditions, to identify the data information in the above-mentioned city operation data that meets the above-mentioned preset missing data conditions as target data information.

[0094] The third step is to impute missing values ​​in the aforementioned target data to obtain the imputed city operation data. In practice, the implementing entity can use special value imputation to impute missing values ​​in the target data to obtain the imputed city operation data. For example, the special value can be "N / A".

[0095] The fourth step is to normalize the aforementioned city operation data to obtain normalized city operation data. In practice, the implementing entity can use the max-min normalization method to normalize the city operation data to obtain normalized city operation data.

[0096] The fifth step is to determine whether the density information of the normalized urban operation data meets the preset density accessibility condition. This preset density accessibility condition can be that the density information is accessible. In practice, the executing entity can use the DBSCAN algorithm to determine whether the density information of the normalized urban operation data meets the preset density accessibility condition.

[0097] The sixth step involves, in response to the determination that the density information of the normalized urban operation data satisfies the preset density accessibility condition, generating an extended cluster corresponding to the normalized density information. In practice, the executing entity can use the DBSCAN algorithm to generate the extended cluster corresponding to the normalized density information.

[0098] Step 7: Based on the expanded clusters described above, perform clustering processing on the normalized density information. In practice, the execution entity can use the DBSCAN algorithm to perform clustering processing on the normalized density information.

[0099] Step 8: Based on the clustering information described above, perform data cleaning on the city operation data that meets the first preset abnormal data condition to obtain cleaned city operation data. The first preset abnormal data condition can be a data type that is dispersed. In practice, the executing entity can use the DBSCAN algorithm to perform data cleaning on the city operation data that meets the first preset abnormal data condition to obtain cleaned city operation data.

[0100] The above-described technical solution, as an inventive point of this disclosure, solves the technical problem of "the high computational resource consumption for monitoring redundant and erroneous data, and the long time consumption for monitoring urban operation data." The factors leading to the high computational resource consumption for monitoring redundant and erroneous data, and the long time consumption for monitoring urban operation data, are often as follows: direct monitoring and processing of urban operation data, urban operation data containing redundant and erroneous data, and lack of preprocessing of the urban operation data. Solving these factors can reduce the computational resources consumed in monitoring redundant and erroneous data, and shorten the time consumed in monitoring urban operation data. To achieve this effect, this disclosure, when monitoring urban operation data, firstly fills in missing values ​​in the urban operation data, and then performs data cleaning, thereby reducing the amount of redundant and erroneous data in the urban operation data, thus achieving the effect of reducing the computational resources consumed in monitoring redundant and erroneous data, and shortening the time consumed in monitoring urban operation data.

[0101] Step 202: Combine the preprocessed urban operation data to obtain combined urban operation data.

[0102] In some embodiments, the aforementioned executing entity can combine the preprocessed urban operation data to obtain combined urban operation data. In practice, firstly, the executing entity can input each data piece of information included in the preprocessed urban operation data into the aforementioned early warning information generation model to obtain early warning information corresponding to the aforementioned data piece of information. Then, the data pieces of information that meet the preset identical conditions are determined as data information groups, resulting in various data information groups. The preset identical condition can be that the early warning information corresponding to each data piece of information is the same. Finally, the obtained data information groups are determined as the combined urban operation data.

[0103] Step 203: Visualize the combined urban operation data.

[0104] In some embodiments, the aforementioned executing entity can perform visualization processing on the combined processed urban operation data. In practice, for each data information group in the aforementioned urban operation data, firstly, the executing entity can determine the warning information corresponding to the aforementioned data information group. Then, it can determine the preset display area corresponding to the aforementioned warning information from a preset display area set. Thus, a preset display area corresponding to each data information group in the aforementioned urban operation data can be obtained. The preset display areas in the aforementioned preset display area set can represent the correspondence between preset display areas and warning information. Finally, each data information in the aforementioned urban operation data can be displayed in its corresponding preset display area.

[0105] Step 204: Determine the early warning level information of the corresponding city operation data based on the combined and processed city operation data.

[0106] In some embodiments, the executing entity can determine the target early warning level information corresponding to the combined processed urban operation data. The target early warning level information can characterize the early warning level corresponding to the urban operation data. In practice, firstly, the executing entity can determine the number of early warning messages characterizing a Level 1 early warning among the various early warning messages corresponding to the urban operation data. Then, in response to determining that the number is greater than a preset number, a Level 1 early warning is determined as the target early warning level information corresponding to the urban operation data. Here, the value of the preset number is not specifically limited.

[0107] Step 205: In response to determining that the warning level information meets the preset warning conditions, the warning information is highlighted and sent to the associated terminal devices to monitor and process the city's operational data.

[0108] In some embodiments, in response to determining that the aforementioned warning level information meets preset warning conditions, the executing entity can highlight the warning information and send it to an associated terminal device to monitor and process the aforementioned city operation data. The preset warning condition can be that the aforementioned warning level information is greater than a preset warning level. The specific setting of the preset warning level is not limited here. The terminal device can be a mobile phone, computer, or other similar device. In practice, firstly, the executing entity can highlight the warning information in the form of a pop-up window or flashing. Then, it can send the warning information to the associated terminal device via SMS or email.

[0109] The above-described embodiments of this disclosure have the following beneficial effects: the urban operation data monitoring method of some embodiments of this disclosure improves data security, reduces the occurrence of single points of failure, and further reduces the time and computing resources consumed in detecting urban operation data. Specifically, the reasons for low data security, frequent single points of failure, long detection time, and high computing resources consumption in urban operation data are: only displaying risky data in urban operation data results in low visibility of early warning information, leading to poor timeliness of early warning information detection; directly monitoring and processing urban operation data without considering preprocessing results in long monitoring time and high computing resources consumption. Based on this, the urban operation data monitoring method of some embodiments of this disclosure first preprocesses the urban operation data to obtain preprocessed urban operation data. This reduces redundant and erroneous data in the urban operation data. Then, the preprocessed urban operation data is combined to obtain combined processed urban operation data. This allows data information with similar risks to be combined. Next, the combined and processed urban operation data is visualized. This allows risky data information to be displayed. Then, based on the combined and processed urban operation data, the corresponding warning level information is determined. This yields the warning level for the corresponding urban operation data. Finally, in response to the determination that the warning level information meets the preset warning conditions, the warning information is highlighted and sent to related terminal devices for monitoring and processing of the urban operation data. This improves the timeliness of monitoring urban operation data and warnings of traffic violations. Because it does not directly monitor urban operation data or directly display risky data information, but rather preprocesses the urban operation data before monitoring, and combines various data information and highlights warning information, the timeliness of users discovering warning information is improved, and the time and computing resources consumed in monitoring urban operation data are reduced.

[0110] The following is for reference. Figure 3 It shows a schematic diagram of the structure of an electronic device (e.g., a computing device) 300 suitable for implementing some embodiments of the present disclosure. Figure 3 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of this disclosure.

[0111] like Figure 3As shown, the electronic device 300 may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage device 308 into a random access memory (RAM) 303. The RAM 303 also stores various programs and data required for the operation of the electronic device 300. The processing unit 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0112] Typically, the following devices can be connected to I / O interface 305: input devices 306 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 307 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 308 including, for example, magnetic tapes, hard disks, etc.; and communication devices 309. Communication device 309 allows electronic device 300 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 3 An electronic device 300 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively. Figure 3 Each box shown can represent a device or multiple devices as needed.

[0113] In particular, according to some embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, some embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication device 309, or installed from storage device 308, or installed from ROM 302. When the computer program is executed by processing device 301, it performs the functions defined in the methods of some embodiments of this disclosure.

[0114] It should be noted that, in some embodiments of this disclosure, the computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In some embodiments of this disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In some embodiments of this disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0115] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0116] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to: preprocess urban operation data to obtain preprocessed urban operation data; combine the preprocessed urban operation data to obtain combined processed urban operation data; visualize the combined processed urban operation data; determine the corresponding early warning level information based on the combined processed urban operation data; and, in response to determining that the early warning level information meets preset early warning conditions, highlight the early warning information and send the early warning information to associated terminal devices to monitor and process the aforementioned urban operation data.

[0117] Computer program code for performing operations of some embodiments of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0118] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0119] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0120] The above description is merely a selection of preferred embodiments of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in the embodiments of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in the embodiments of this disclosure.

Claims

1. A city operation data monitoring system, comprising a city operation data uploading node, a city operation data access node, a node monitoring cluster, a city operation data storage cluster; the city operation data uploading node is configured to encrypt city operation data to obtain encrypted city operation data; upload the encrypted city operation data to the city operation data storage cluster; the city operation data storage cluster is configured to store the received encrypted city operation data; send the storage address information corresponding to the encrypted city operation data to the city operation data uploading node corresponding to the encrypted city operation data; the node monitoring cluster is configured to register the user node corresponding to the user registration request information according to the received user registration request information to obtain user registration information; send the user registration information to the user node corresponding to the user registration information, wherein the node monitoring cluster is deployed with a first block chain and a second block chain; the city operation data access node is configured to send data request information to the node monitoring cluster; obtain encrypted city operation data corresponding to the data request information from the city operation data storage cluster according to the secondary encrypted data detail information sent by the node monitoring cluster, wherein the data request information comprises node identification information and a set of request data keywords, and the obtaining of the encrypted city operation data corresponding to the data request information from the city operation data storage cluster according to the secondary encrypted data detail information sent by the node monitoring cluster comprises: decrypting the secondary encrypted data detail information according to the received user private encryption information to obtain encrypted data detail information corresponding to the data request information; obtaining encrypted city operation data corresponding to the storage address information from the city operation data storage cluster according to the storage address information included in the obtained encrypted data detail information corresponding to the data request information; decrypting the obtained encrypted city operation data to obtain city operation data corresponding to the data request information; and monitoring the obtained city operation data; the node monitoring cluster is configured to respond to the data request information sent by the city operation data access node to perform registration verification processing on the city operation data access node to obtain registration verification result information; in response to determining that the registration verification result information represents that the verification is passed, obtain encrypted data detail information corresponding to a set of request data keywords included in the data request information according to the node identification information included in the data request information; obtain user public encryption information corresponding to the city operation data access node; encrypt the obtained encrypted data detail information according to the user public encryption information corresponding to the city operation data access node to obtain secondary encrypted data detail information; and send the obtained secondary encrypted data detail information to the city operation data access node.

2. The urban operation data monitoring system of claim 1, wherein, the node monitoring cluster is further configured to: generate a target value set according to a preset value; select two target values from the target value set as a first encryption parameter and a second encryption parameter; encrypt the preset value according to the second encryption parameter to obtain a second encrypted preset value; determine the first encryption parameter and the second encrypted preset value as main encryption information; encrypt the preset value according to the first encryption parameter to obtain a first encrypted preset value; generate a constraint value according to the preset value and preset constraint information; encrypt the constraint value according to the second encryption parameter to obtain an encrypted constraint value; determine the target value set, the preset value, the first encrypted preset value, and the encrypted constraint value as encryption public key information.

3. The urban operation data monitoring system of claim 1, wherein, The city operation data uploading node is further configured to: perform encryption processing on preset encryption information to obtain encrypted ciphertext information; extract keywords of the encrypted city operation data to obtain a keyword set; perform hash processing on the encrypted city operation data to obtain encrypted data hash information; determine, as encrypted data detail information corresponding to the city operation data, storage address information corresponding to the encrypted city operation data, the keyword set, the encrypted data hash information, and the encrypted ciphertext information sent by the city operation data storage cluster; perform signature processing on the encrypted data detail information to obtain signature information; send the encrypted data detail information and the signature information to the node monitoring cluster.

4. The urban operation data monitoring system of claim 3, wherein, The node monitoring cluster is further configured to: in response to receiving the encrypted data detail information and the signature information sent by the city operation data uploading node, perform verification processing on the received signature information to obtain signature verification result information; in response to determining that the signature verification result information indicates that the verification is passed, perform storage processing on the received encrypted data detail information.

5. A city operation data monitoring method, applied to the city operation data monitoring system of any one of claims 1-4, comprising: preprocessing city operation data to obtain preprocessed city operation data, wherein the preprocessing city operation data comprises: determining whether there is data information in the city operation data that satisfies a preset missing data condition; in response to determining that there is data information in the city operation data that satisfies the preset missing data condition, determining the data information in the city operation data that satisfies the preset missing data condition as target data information; performing missing value filling processing on the target data information to obtain filled city operation data as city operation data; performing normalization processing on the city operation data to obtain normalized city operation data; determining whether density information of the normalized city operation data satisfies a preset density reachability condition; in response to determining that the density information of the normalized city operation data satisfies the preset density reachability condition, generating an extended cluster corresponding to the normalized density information according to the normalized density information. According to the extended cluster, the normalized density information is clustered; According to the clustering information, data cleaning processing is performed on data in the city operation data that meets a first preset abnormal data condition; The preprocessed city operation data is combined to obtain combined city operation data; The combined city operation data is visually displayed; According to the combined city operation data, warning level information corresponding to the city operation data is determined; In response to determining that the warning level information meets a preset warning condition, the warning prompt information is highlighted, and the warning prompt information is sent to an associated terminal device to monitor the city operation data.

6. An electronic device, comprising: one or more processors; storage configured to store one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the method of claim 5.

7. A computer readable storage medium having stored thereon a computer program, wherein, The computer program is executed by the processor to implement the method of claim 5.

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