Distributed data model tampering risk assessment method and device, electronic equipment, medium and product

Abstract

The invention discloses a distributed data model tampering risk assessment method and device, electronic equipment, a medium and a product, and relates to the technical field of block chains. The distributed data model tampering risk assessment method comprises the steps that an original unified data model is converted into a unified model chain in a block chain network according to an original deployment scheme corresponding to the original unified data model, and the unified model chain at least comprises a plurality of model chain nodes; according to fields of the data models corresponding to the model chain nodes, corresponding field chains are constructed, and the field chains are used for recording field data in the data models; and when the unified model chain or the field chain generates a modification record, auditing the unified model chain or the field chain based on a preset smart contract to obtain a corresponding auditing result and an auditing report. According to the technical scheme, the problem that the tampering condition of the data cannot be effectively controlled in time through a traditional tampering prevention strategy of a distributed data model is solved.

Description

Technical Field

[0001] The present application relates to the field of blockchain technology, and in particular to a distributed data model tampering risk assessment method, device, electronic device, computer-readable storage medium, and computer program product. Background Art

[0002] At present, since the distributed data models are distributed in different nodes, unauthorized malicious users or internal employees may tamper with the data in the distributed nodes when accessing specific distributed nodes, which may lead to deviations between the node data and the data of the original model, so the data model is at risk of being tampered with. In order to overcome this problem, the common strategy is to encrypt the data or authorize the user's permissions, but this management method will increase the difficulty of system management (for example, additional encryption and decryption authentication of the data is required). In addition, when authorized users maliciously or beyond the scope of data tampering, it is difficult for the management party to promptly learn about the tampering of the data (including the time and location of the tampering, etc.), so the control effect of data tampering of the distributed data model is poor.

[0003] The above contents are only used to assist in understanding the technical solution of the present application and do not constitute an admission that the above contents are prior art. Summary of the invention

[0004] The main purpose of this application is to provide a distributed data model tampering risk assessment method, device, electronic device, computer-readable storage medium and computer program product, aiming to solve the technical problem that the traditional distributed data model anti-tampering strategy cannot effectively control the tampering of data in a timely manner.

[0005] To achieve the above objectives, the present application proposes a distributed data model tampering risk assessment method, the distributed data model tampering risk assessment method comprising:

[0006] Converting the original unified data model into a unified model chain in the blockchain network according to the original deployment scheme corresponding to the original unified data model, wherein the unified model chain includes at least a virtual unified node and a plurality of model chain nodes associated with and mapped to the virtual unified node;

[0007] Constructing a corresponding field chain according to the field of the data model corresponding to each of the model chain nodes, wherein the field chain is used to record the field data in the data model;

[0008] When the unified model chain or the field chain generates a modification record, the unified model chain or the field chain is audited based on a preset smart contract to obtain a corresponding audit result;

[0009] An audit report is generated according to the audit result, wherein the audit report at least includes a tampering risk assessment result.

[0010] In one embodiment, the step of converting the original unified data model into a unified model chain in the blockchain network according to the original deployment scheme corresponding to the original unified data model includes:

[0011] Based on the original unified data model and the data model in the child node of the original deployment solution, a mapping relationship between the data model in the model chain node and the data model in the virtual unified node is established;

[0012] According to the mapping relationship, a virtual unified node and a plurality of model chain nodes associated with the virtual unified node are generated to obtain a unified model chain.

[0013] In one embodiment, the mapping relationship includes at least a table mapping relationship, a field mapping relationship, and an enumeration value mapping relationship;

[0014] The step of establishing a mapping relationship between the data model in the model chain node and the data model in the virtual unified node based on the original unified data model and the data model in the child node of the original deployment solution includes:

[0015] Establishing a table mapping relationship according to the contents corresponding to the table in the original unified data model and the table in the data model in the child node;

[0016] On the basis of the table mapping relationship, a field mapping relationship is established according to the field differences between the original unified data model and the data model in the child node;

[0017] An enumeration value mapping relationship is established according to the original unified data model and the enumeration values ​​in the data model in the child node.

[0018] In one embodiment, the step of constructing a corresponding field chain according to the fields of the data model corresponding to each of the model chain nodes includes:

[0019] Traversing the data of each model chain node in the unified model chain, and reading the field content in each model chain node;

[0020] A corresponding field chain is generated according to the field definition, field value and field format of the field content in each of the model chain nodes.

[0021] In one embodiment, the smart contract includes at least a model smart contract and a field smart contract, the audit result includes at least a model audit result and a field audit result, and the step of auditing the unified model chain or the field chain based on the preset smart contract to obtain the corresponding audit result includes:

[0022] Perform hash calculation on the model data in the model chain node that generates the modification record to obtain the current model data;

[0023] Acquire the table, field and enumeration value corresponding to the model chain node generating the modification record from the virtual unified node to obtain the reference model data;

[0024] Compare the current model data with the reference model data based on the audit rules of the model smart contract to generate a model audit result;

[0025] Perform hash calculation on the field of the field chain node that generates the modified record to obtain the current field data;

[0026] Obtain the field corresponding to the initial node in the field chain to obtain reference field data;

[0027] The current field data and the reference field data are compared based on the audit rules of the field smart contract to generate a field audit result.

[0028] In one embodiment, before the step of auditing the unified model chain or the field chain based on a preset smart contract, the method further includes:

[0029] Receive the input audit rules through the visualization page and generate regular expressions corresponding to the audit rules;

[0030] Load the regular expressions into the preset model smart contract and field smart contract respectively;

[0031] Among them, the model smart contract is used to audit at least one of the basic information, deployment node, version information, deployment time, deployment order and deployment integrity of the data model corresponding to each model chain node, and the field smart contract is used to audit at least one of the field name, data type, data length, field enumeration value definition, publishing node information, field version information and field deployment time of the data table of each data model.

[0032] In addition, to achieve the above purpose, the present application also proposes a distributed data model tampering risk assessment device, the distributed data model tampering risk assessment device comprising:

[0033] A model chain construction module, used to convert the original unified data model into a unified model chain in the blockchain network according to the original deployment scheme corresponding to the original unified data model, wherein the unified model chain at least includes a virtual unified node and a plurality of model chain nodes associated with and mapped to the virtual unified node;

[0034] A field chain building module, used to build a corresponding field chain according to the field of the data model corresponding to each of the model chain nodes, wherein the field chain is used to record the field data in the data model;

[0035] A contract audit module, used for auditing the unified model chain or the field chain based on a preset smart contract when a modification record is generated in the unified model chain or the field chain, and obtaining a corresponding audit result;

[0036] A report generation module is used to generate an audit report based on the audit results, wherein the audit report at least includes tampering risk assessment results.

[0037] In addition, to achieve the above-mentioned purpose, the present application also proposes an electronic device, which includes: a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the computer program is configured to implement the steps of the distributed data model tampering risk assessment method as described above.

[0038] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the distributed data model tampering risk assessment method as described above are implemented.

[0039] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, it implements the steps of the distributed data model tampering risk assessment method as described above.

[0040] The present application proposes a distributed data model tampering risk assessment method, firstly, according to the original deployment scheme corresponding to the original unified data model, the original unified data model is converted into a unified model chain in the blockchain network, wherein the unified model chain at least includes a virtual unified node and a plurality of model chain nodes associated with the virtual unified node, and then the corresponding field chain is constructed according to the field of the data model corresponding to each of the model chain nodes, wherein the field chain is used to record the field data in the data model, when the unified model chain or the field chain generates a modification record, the unified model chain or the field chain is audited based on a preset smart contract to obtain a corresponding audit result, and an audit report is generated according to the audit result, wherein the audit report at least includes a tampering risk assessment result. The technical solution of the present application first realizes the conversion of the distributed deployed data model to the blockchain by constructing a unified model chain and a field chain, and associates each data model by virtually constructing a unified node, so as to realize the tamper-proof protection of the distributed data model through the blockchain technology itself. In addition, when the modification record is generated, the unified model chain and the field chain are audited by the smart contract, so that the tampering of the data model of the distributed node of the distributed deployment can be timely learned. Moreover, in the embodiment of the present application, the method of auditing the model chain and the field chain separately can comprehensively cover the tampering of the data model and avoid omissions. When only the model structure is tampered with, only the model chain needs to be audited, avoiding unnecessary audits and saving a certain amount of calculation. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0042] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0043] Figure 1 A flow chart of the first embodiment of the distributed data model tampering risk assessment method provided in this application;

[0044] Figure 2 A schematic diagram of a process for auditing module chain nodes and field chain nodes that generate modification records in an embodiment of the present application;

[0045] Figure 3 This is a schematic diagram of the overall process of constructing a module chain, a field chain, and auditing based on a smart contract in the embodiment of the present application;

[0046] Figure 4 This is a schematic diagram of the structure of a distributed data model tampering risk assessment device in an embodiment of the present application;

[0047] Figure 5 Schematic diagram of the device structure of the hardware operating environment involved in the distributed data model tampering risk assessment method in the embodiment of the present application.

[0048] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0049] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0050] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0051] The execution subject of this embodiment may be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, a server, etc., or an electronic device or a control device capable of realizing the above functions. The following takes the server as an execution subject as an example to illustrate this embodiment and the following embodiments.

[0052] Although the current business model of the unified data model for distributed deployment can achieve efficient data processing and storage, there are still problems that the unified original model data is easily tampered with and the central node is difficult to detect the period of tampering of the distributed model data. Since the distributed data model is distributed in different nodes, unauthorized malicious users or internal employees may tamper with the data in the distributed node when accessing a specific distributed node, which will lead to a deviation between the data and the data of the original model. In addition, since data in the distributed system needs to be transmitted through the network between different nodes, this method also brings the risk of malicious network attacks and data theft by hackers to a certain extent. The commonly used solution is to encrypt data or authorize user permissions, but this method will increase the difficulty of system management (additional encryption and decryption authentication of data is required), and secondly, it is impossible to timely and effectively manage data tampering (it is impossible to avoid malicious or excessive data tampering by authorized users).

[0053] For example, since data in the mobile communication system industry is usually distributed in data centers or servers in different geographical locations, and due to network delays and transmission time issues, the central node may not be able to obtain the data status on all distributed nodes in a timely manner, which in turn causes the central node to be unable to detect data tampering in a timely manner; in addition, if an attacker tampers with the data during data transmission, the central node will also be unable to detect data tampering in a timely manner. Moreover, since the distributed system is relatively large, the central node cannot track the data transmission and processing history in a timely manner, resulting in an inability to accurately determine which distributed node's data has been tampered with.

[0054] In order to overcome the above technical defects, the present application embodiment provides a distributed data model tampering risk assessment method, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the distributed data model tampering risk assessment method of the present application, and the distributed data model tampering risk assessment method includes:

[0055] Step S10, converting the original unified data model into a unified model chain in the blockchain network according to the original deployment scheme corresponding to the original unified data model, wherein the unified model chain at least includes a virtual unified node and a plurality of model chain nodes associated with and mapped to the virtual unified node;

[0056] In order to overcome the defect that data under the business model of distributed deployment of data models in the prior art is easily tampered with, the embodiment of the present application essentially provides an anti-tampering strategy for distributed deployed data models based on a unified model chain with the help of the anti-tampering characteristics of blockchain. First, the original unified data model input by the developer and the original deployment plan (i.e., distributed deployment plan) of the original unified data model are received, and then the corresponding unified model chain is generated for the above original unified data model and original deployment plan. In summary, the purpose of step S10 is to construct the distributed deployed data model into a "unified model chain" based on the principle of blockchain.

[0057] Specifically, in the process of converting the unified model chain, a virtual unified node is constructed for the original unified data model, and a model chain node is constructed for the data model of each distributed node in the original deployment plan. In the unified model chain, a virtual unified node is included, and each model chain node associated with the virtual unified node is also included. The above virtual unified nodes and each model chain node correspond one-to-one to each node in the original unified data model and the original deployment plan. Moreover, the virtual unified node and the model chain node together constitute the entire blockchain as blockchain nodes. The advantage of the unified model link design is that it can use the blockchain technology itself to prevent illegal or unauthorized users from tampering with model data, and avoid malicious tampering of model data by unauthorized users.

[0058] It should be noted that the virtual unified node and the model chain node in the embodiment of the present application both record the model structure, model parameters, model modification records and model unique identifiers, the difference is that the data on the virtual unified node and the data model on the model chain node are not exactly the same. Specifically, relative to the data on the virtual unified node (regarded as the full set), the data in the data model on the model chain node belongs to a subset of the data on the virtual unified node.

[0059] Step S20, constructing a corresponding field chain according to the field of the data model corresponding to each model chain node, wherein the field chain is used to record the field data in the data model;

[0060] The purpose of step S20 is to construct a corresponding field chain based on the unified model chain generated in the previous step. Specifically, for the fields in each model chain node data in the unified model chain, corresponding field chain nodes are constructed and combined to form a field chain.

[0061] Among them, the field chain records the field data of each field of the data in each model chain node, and the field data includes field definition, field value and field format. It should be noted that each data model in the distributed deployment of the embodiment of the present application corresponds to a model chain node in the unified model chain, and each model chain node is deployed with a field chain node corresponding to the current data model, and the unified model chain is a consortium blockchain, which is open to users with permission to access the distributed nodes for login and use, while the field chain is a private blockchain, which is only open to users of the current distributed deployment node for login and use.

[0062] Step S30: When a modification record is generated in the unified model chain or field chain, the unified model chain or field chain is audited based on a preset smart contract to obtain a corresponding audit result;

[0063] In order to realize the tampering risk assessment of each data model in the blockchain, when the model chain node in the unified model chain or the field chain node in the field chain generates a modification record, a pre-established smart contract is used for automatic auditing. Smart contracts on the blockchain are contracts that can be triggered and executed by transactions on the blockchain system. They are usually defined in the form of code. When conducting an audit, the smart contract compares the data in the model chain node or the field chain node according to the pre-defined audit rules to determine whether the data content is normal.

[0064] It should be noted that the audit results include audits of indicators of each dimension of data in the model chain node or field chain node. For example, the model chain node is verified for correctness at the data level, and the field chain is verified for correctness at the data table level. When the verified data does not conform to the normal situation in the preset audit rules, it is recorded until the data of each dimension is verified and the audit results are obtained.

[0065] Step S40, generating an audit report based on the audit results, wherein the audit report at least includes tampering risk assessment results.

[0066] After the audit results are determined, a more visual audit report is generated. The audit report is mainly used to summarize the audit results and list the data dimensions that the staff is concerned about one by one, so that the staff can comprehensively evaluate the modification of the data model. Specifically, for the data model of each distributed node in the distributed deployment, the quality of the data model is judged according to the audit results corresponding to the model smart contract and the field smart contract respectively. If there are multiple audit rules for the data model of the same distributed node, the probability value is obtained according to the ratio of the audit results of multiple audit rules to the audit results of all audit rules. The quality of the current data model is evaluated according to the probability value. If the quality of the current data model is lower than the set threshold, the deployment personnel are notified to redeploy the model to reduce the risk of data model tampering.

[0067] Exemplarily, the contents of the audit report may include: basic information of the model, the results of the contract execution of the current node (including the contract content, execution time, results of the model audit and field audit), consensus of the audit results of each node in the model chain (mainly refers to the recognition conclusion of the audit results of the current node by each node where the model and fields need to be deployed), and anti-tampering risk assessment conclusion (whether there is tampering, and the location of the cause of the tampering risk. For example, when the result of the node is inconsistent with the consensus of other nodes, it can be considered that the model data of the node has been tampered with; when the result of the node is consistent with some other nodes on the chain and inconsistent with some nodes, it can be considered that there is a tampering risk in the publishing node).

[0068] The embodiment of the present application provides a convenient way for users to conduct a comprehensive model audit on a distributed data model, and provides a detailed audit report to help users better manage and control model quality. Here, in subsequent work, the data source end (based on the mapping relationship mark) and target end audit of the field can also be marked in the annotation of the field attribute of the distributed deployed data model. Information on whether the audit has passed (based on the audit result of the field chain smart contract). If in subsequent work, the user changes the audit rules corresponding to the smart contract, then only the corresponding relationship between the field attribute annotation and the audit rule is needed to obtain the data model corresponding to the audit rule, and then the smart contract corresponding to the updated audit rule can be used to re-audit the model quality, thereby achieving more flexible data auditing and improving audit efficiency.

[0069] In the embodiment of the present application, the principle of blockchain is used to convert the unified original data model of distributed deployment into a unified model chain, and a virtual unified node corresponding to the unified original model data and a model chain node corresponding to the data model under each distributed node of distributed deployment are constructed in the unified model chain. Blockchain technology is further used to construct a field chain for the current data model for each module chain node. Since the unified model chain and the field chain both belong to the blockchain, only members of the blockchain alliance have the right to access them, and each data modification of the access will leave a modification record, thereby achieving the effect of tamper-proofing the unified original model data of distributed deployment.

[0070] Further, in a feasible embodiment, the step of converting the original unified data model into a unified model chain in the blockchain network according to the original deployment scheme corresponding to the original unified data model may include:

[0071] Step S11, establishing a mapping relationship between the data model in the model chain node and the data model in the virtual unified node based on the original unified data model and the data model in the child node of the original deployment solution;

[0072] Before building a unified model chain, it is necessary to first establish a mapping relationship between the data model of the model node in the model chain to be built and the data model of the virtual unified node based on the mapping relationship between the original unified data model and the data model in the subnode of the original deployment plan. The mapping relationship between the two is respectively corresponding, that is, the mapping relationship between the original unified data model and the data model in the subnode of the original deployment plan needs to be transplanted into the unified model chain. In addition, while establishing the mapping relationship between the data model in the model chain node and the data model in the virtual unified node, it is also necessary to build a model standard library, wherein the model standard library is used to store the mapping relationship and data content.

[0073] Specifically, the mapping relationship includes at least a table mapping relationship, a field mapping relationship and an enumeration value mapping relationship; specifically, the mapping relationship includes a table mapping relationship between the table of the data model in the virtual unified node and the table of the data model in the model chain node, a field mapping relationship between the field of the data model in the virtual unified node and the field of the data model in the model chain node, and an enumeration value mapping relationship between the enumeration value of the data model in the virtual unified node and the enumeration value of the data model in the model chain node.

[0074] The step of establishing a mapping relationship between the data model in the model chain node and the data model in the virtual unified node based on the original unified data model and the data model in the child node of the original deployment solution may include:

[0075] Step S111, establishing a table mapping relationship according to the corresponding contents of the table in the original unified data model and the table in the data model in the child node;

[0076] Exemplarily, the data model in the sub-node of the current distributed deployment and the original unified data model are first obtained, and the tables in the sub-node of the distributed deployment and the tables in the original unified data model are identified and mapping relationships are established to obtain table mapping relationships.

[0077] The table mapping relationship constructed in the embodiment of the present application can define the corresponding relationship between each table in the data model of the distributed deployed sub-node and the corresponding table in the original unified data model.

[0078] Step S112, on the basis of the table mapping relationship, according to the field differences between the original unified data model and the data model in the child node, establishing a field mapping relationship;

[0079] Exemplarily, the data model in the sub-node of the current distributed deployment, the original unified data model and the table mapping relationship are first obtained, and then the field differences between the data model in the sub-node of the current distributed deployment and the original unified data model are analyzed based on the table mapping relationship, and a mapping relationship is established to obtain a field mapping relationship.

[0080] The field mapping relationship constructed in the embodiment of the present application can correctly map each field in the data model of the sub-nodes currently deployed in a distributed manner to the corresponding field in the original unified data model.

[0081] Step S113: establishing an enumeration value mapping relationship according to the original unified data model and the enumeration values ​​in the data model in the child node.

[0082] Exemplarily, the data model in the child node of the current distributed deployment and the original unified data model are obtained and it is determined whether there are enumeration values ​​(such as enumeration values ​​such as status and type). If there are enumeration values, a mapping relationship is established between the data model in the child node of the current distributed deployment and the enumeration value in the original unified data model to obtain an enumeration value mapping relationship.

[0083] The enumeration value mapping relationship constructed in the embodiment of the present application can ensure the consistency and accuracy of the enumeration values ​​when using data query and retrieval services.

[0084] Step S12: generating a virtual unified node and a plurality of model chain nodes associated with the virtual unified node and mapped according to the mapping relationship, so as to obtain a unified model chain.

[0085] After determining the above table mapping relationship, field mapping relationship and enumeration value mapping relationship, a unified model chain is established by building an association between the data model in the unified model chain node and the data model in the virtual unified node. The mapping relationship between the data model of the virtual unified node in the unified model chain and the data model of each model chain node follows the above determined table mapping relationship, field mapping relationship and enumeration value mapping relationship.

[0086] In a feasible embodiment, the step of constructing a corresponding field chain according to the fields of the data model corresponding to each of the model chain nodes may include:

[0087] Step S21, traversing the data of each model chain node in the unified model chain, and reading the field content in each model chain node;

[0088] Step S22: Generate a corresponding field chain according to the field definition, field value and field format of the field content in each model chain node.

[0089] In the process of constructing the field chain of the fields of the data model in the model chain node, it is necessary to construct corresponding field chain nodes for the field content in the data of each model chain node, and record the field data of each field and transcribe it into the field chain node. Specifically, the field chain includes at least field definition, field value, and field format.

[0090] Establishing a field chain based on the unified model chain can further record the specific data of the field in detail in the blockchain, thereby converting the original unified model and the field content in each node in the distributed deployment solution to the blockchain, so that the model structure and field content can be managed separately in the blockchain. After the model structure or field is modified, timely auditing can be carried out to determine which node the change is located at, thereby improving the management and control efficiency of distributed data models.

[0091] In a feasible embodiment, the smart contract includes at least a model smart contract and a field smart contract, and the audit result includes at least a model audit result and a field audit result. Figure 2 The step of auditing the unified model chain or the field chain based on the preset smart contract in step S30 to obtain the corresponding audit result may include:

[0092] Step S31, performing hash calculation on the model data in the model chain node that generates the modification record to obtain the current model data;

[0093] Step S32, obtaining the table, field and enumeration value corresponding to the model chain node generating the modification record from the virtual unified node, and obtaining the reference model data;

[0094] Step S33, comparing the current model data with the reference model data based on the audit rules of the model smart contract to generate a model audit result;

[0095] Step S34, performing hash calculation on the field of the field chain node that generates the modified record to obtain the current field data;

[0096] Step S35, obtaining the field corresponding to the initial node in the field chain to obtain reference field data;

[0097] Step S36, compare the current field data with the reference field data based on the audit rules of the field smart contract to generate a field audit result.

[0098] It should be noted that in the embodiment of the present application, steps S31 to S33 and steps S34 to S36 are relatively independent and are respectively executed when modification records are generated in the model chain node and when modification records are generated in the field chain node. Part or all of the execution may also be selected according to actual conditions.

[0099] Exemplarily, when a model chain node or a field chain node generates a modification record, the relevant instructions of the smart contract are triggered, causing the smart contract (model smart contract and field smart contract) to execute corresponding audit steps.

[0100] Specifically, in the process of executing the audit step of the model smart contract, the model smart contract first obtains the virtual unified node in the unified model chain as the authority node, and uses the model chain node that generates the model modification record as the execution node. Then, the latest model data in the execution node is calculated by the hash algorithm to obtain the current model data. According to the determined mapping relationship, the reference model data composed of the corresponding table, field and enumeration value is obtained from the authority node. The current model data and the reference model data are audited according to the pre-defined model audit rules, and the corresponding model audit results are generated.

[0101] Specifically, in the process of executing the audit step of the field smart contract, the initial node in the field chain is first obtained as the authority node, the field chain node that generates the field modification record is used as the execution node, the field in the execution node is calculated by the hash algorithm to obtain the current field data, the current field data and the reference field data in the authority node are audited according to the field audit rules, and the corresponding audit results are generated. Among them, the field audit rules include at least abnormal value audit and field structure audit. When the field structure is audited, the combined data of the field definition and the field format is calculated by the hash algorithm as the current field data content, and the abnormal value audit takes the field value and calculates it by the hash algorithm as the current field data.

[0102] It should be noted that, under normal circumstances, the initial node of the field chain of each model chain node is always verified to be correct. This is because the modification permission of the initial node is higher than the modification permission of other field chain nodes and module chain nodes, and it will not be tampered by ordinary users who only have node login permission. Therefore, the field smart contract can use the initial node as a permission node without having to compare it with the original unified data model in the virtual unified node, which also reduces the amount of calculation to a certain extent. In addition, the model audit rules in the model smart contract are to audit the model structure of the data model. The benefit of this design is that it can not only ensure the comprehensiveness of the audit but also avoid unnecessary audits (if only the model structure of the data model is tampered with, only the model structure needs to be audited, and there is no need to audit the field).

[0103] Since a virtual unified node is designed when constructing a corresponding unified data chain for a distributed deployment solution in the embodiment of the present application, and a mapping relationship between a model chain node and a virtual unified node is established in the unified model chain, once a model modification record is generated in the subsequent model use phase, a fast and efficient data model audit can be achieved through a model smart contract in combination with the mapping relationship and the virtual unified node, thereby improving the audit efficiency and timely discovering situations where the data model has been tampered with. Similarly, the initial node of the field chain records the fields of the current data model, and once a field modification record occurs in the subsequent model use phase, a fast and efficient field audit can be achieved through a field smart contract in combination with the initial node in the field chain. The smart contract in the embodiment of the present application can trigger the smart contract for auditing as soon as a model modification or field modification occurs, and the audit of the field and the audit of the model structure do not interfere with each other, thereby achieving efficient auditing.

[0104] Further, before the step of auditing the unified model chain or the field chain based on the preset smart contract, the method may also include:

[0105] Step A10, receiving the input audit rules through the visualization page, and generating regular expressions corresponding to the audit rules;

[0106] Step A20, loading the regular expression into the preset model smart contract and field smart contract respectively;

[0107] Among them, the model smart contract is used to audit at least one of the basic information, deployment node, version information, deployment time, deployment order and deployment integrity of the data model corresponding to each of the model chain nodes, and the field smart contract is used to audit at least one of the field name, data type, data length, field enumeration value definition, publishing node information, field version information and field deployment time of the data table of each data model.

[0108] The embodiment of the present application is equivalent to providing a method for editing a smart contract. Specifically, the user can edit the audit rules (including model audit rules and field audit rules) on the visual page and generate corresponding regular expressions as achievable audit rules in the background and load them into the corresponding smart contract. The audit rules configured by the user can support integration with the database to achieve flexible and accurate data audit functions. The query SQL (Structured Query Language) statement generated by this solution executes the audit rules through the smart contract.

[0109] Exemplarily, model audit rules are mainly used for correctness checking and verification at the data model level. The main contents include basic information of the model (such as the model name and the table name of the data table contained in the model. For model names that are not strictly constrained, the generation rules of basic information can also be regarded as audit rules), model deployment nodes, model version information, model deployment time (including update time, such as whether the deployment is completed on time, etc.), model deployment sequence (including node sequence and deployment sequence of data tables in the model), model deployment integrity, etc., and contract execution trigger conditions based on audit rules, so as to achieve overall control of distributed data models through model audit rules.

[0110] Furthermore, when a user with login and usage rights of a blockchain node uses the data model of the corresponding model chain node in the "unified model chain", a model modification record will be generated. At this time, the "model smart contract" is set through code to access the model chain node of the newly generated model modification record when the model modification record is learned to execute the model audit rules. The specific model audit rules are freely edited and set by the user on the visualization page.

[0111] Exemplarily, field audit rules are mainly used to check the correctness of specific definitions of data tables in data models. The main content includes the DDL (Data Definition Language) of data tables in data models, such as field names (field names must be consistent with model definitions when constraints are enforced, and only the naming rules need to conform to model definitions when constraints are not enforced), data types, data lengths, field enumeration value definitions, etc.; as well as field publishing node information, field version information, field deployment time, etc. (this part is similar to model audit rules, but at a lower level).

[0112] Furthermore, when a user with blockchain node permissions uses the data model of the corresponding model chain node in the "unified model chain", if a field is edited, the field chain record will be triggered to record the field modification record. The "field smart contract" is set through code to access the corresponding field chain to execute the field audit rules when the field modification record is learned. The specific field audit rules are freely edited and set by the user on the visualization page.

[0113] The technical solution of the embodiment of the present application realizes the customized editing of audit rules, and converts the audit rules in the traditional mode into smart contracts under the blockchain to perform data audit; and the smart contracts are divided into model smart contracts for the unified model chain and field smart contracts for the field chain. The field smart contract uses the initial node of the field chain as the authority node, and the model smart contract uses the virtual unified node as the authority node to realize data audit of low data volume, so as to achieve the effect that the central node is informed of the tampering of the data model of the distributed nodes in the distributed deployment in a timely manner.

[0114] In combination with the contents of the aforementioned application embodiments, the core principle of the distributed data model tampering risk assessment method provided by this application is to utilize the multi-node computing power of the multi-node system of the blockchain, as well as the similarity and consistency requirements of the distributed deployed data model after deployment. The distributed deployed data model is constructed from three levels, namely, the deployment plan, the unified model, and the data tables that constitute the model, into a blockchain data structure with alliance chain characteristics. Then, the creation and control of the chain data of the model are realized through the unified model chain construction module and the field chain construction module. Then, the smart contract editing, execution and other modules that match the chain data realize the contractualization of the unified model data inspection, verification and other rules or business actions, which are automatically executed without human intervention, to ensure the authenticity and effectiveness of the model data audit.

[0115] For example, refer to Figure 3 The distributed data model tampering risk assessment method of the present application can be applied in a blockchain system, which may include a unified model chain construction unit, a field chain construction unit, a smart contract editing unit, a smart contract execution unit and other parts. Specifically, the unified model chain construction unit (including a table mapping subunit, a field mapping subunit and an enumeration value mapping subunit) maps the original unified model and distributed nodes in the input distributed deployment scheme to generate a unified model chain including a virtual unified node and a model chain node, and then the field chain construction unit generates the corresponding field chain; when the modification record is generated, the smart contract execution unit performs the audit and generates the audit result and audit report. In addition, the smart contract editing unit is used to pre-edit the model smart contract (including the model audit rules) and the field smart contract (including the field audit rules).

[0116] The technical solution of the embodiment of the present application can be applied to the audit management scenario of the distributed deployed big data model. In the traditional scenario, the data model of big data is stored in a distributed framework, and data tampering is avoided by data encryption or user authority control, but it is impossible to avoid data tampering by authorized users, and the scheme control logic of the entire system is complex. The technical solution of the embodiment of the present application can not only reduce the tampering of the data model simply and efficiently with the help of blockchain technology, but also allow the central node to obtain the tampering of the distributed deployed data model in the first time, reducing system management and design costs while improving data security.

[0117] In addition, the technical solution of the embodiment of the present application can also be applied to the audit rule modification scenario of the big data model. The traditional audit rule modification requires a dedicated developer to re-edit the audit rules and audit tasks. Especially when the amount of data in the data model is too large, the audit rules of the traditional solution cannot be effectively modified. After adopting the technical solution of the embodiment of the present application, the user can quickly modify the audit rules through smart contract editing to achieve custom modification of the audit rules of the big data model.

[0118] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the distributed data model tampering risk assessment method of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0119] This application also provides a distributed data model tampering risk assessment device, referring to Figure 4 , the distributed data model tampering risk assessment device comprises:

[0120] A model chain construction module 10, configured to convert the original unified data model into a unified model chain in the blockchain network according to the original deployment scheme corresponding to the original unified data model, wherein the unified model chain at least includes a virtual unified node and a plurality of model chain nodes associated with and mapped to the virtual unified node;

[0121] A field chain building module 20, used to build a corresponding field chain according to the field of the data model corresponding to each of the model chain nodes, wherein the field chain is used to record the field data in the data model;

[0122] The contract audit module 30 is used to audit the unified model chain or the field chain based on a preset smart contract when a modification record is generated in the unified model chain or the field chain, and obtain a corresponding audit result;

[0123] The report generation module 40 is used to generate an audit report according to the audit result, wherein the audit report at least includes a tampering risk assessment result.

[0124] In one embodiment, the model chain building module 10 is further used for:

[0125] Based on the original unified data model and the data model in the child node of the original deployment solution, a mapping relationship between the data model in the model chain node and the data model in the virtual unified node is established;

[0126] According to the mapping relationship, a virtual unified node and a plurality of model chain nodes associated with the virtual unified node are generated to obtain a unified model chain.

[0127] In one embodiment, the mapping relationship includes at least a table mapping relationship, a field mapping relationship, and an enumeration value mapping relationship, and the model chain building module 10 is further used to:

[0128] Establishing a table mapping relationship according to the contents corresponding to the table in the original unified data model and the table in the data model in the child node;

[0129] On the basis of the table mapping relationship, a field mapping relationship is established according to the field differences between the original unified data model and the data model in the child node;

[0130] An enumeration value mapping relationship is established according to the original unified data model and the enumeration values ​​in the data model in the child node.

[0131] In one embodiment, the field chain building module 20 is further used to:

[0132] Traversing the data of each model chain node in the unified model chain, and reading the field content in each model chain node;

[0133] A corresponding field chain is generated according to the field definition, field value and field format of the field content in each of the model chain nodes.

[0134] In one embodiment, the smart contract includes at least a model smart contract and a field smart contract, the audit result includes at least a model audit result and a field audit result, and the contract audit module is further used to:

[0135] Perform hash calculation on the model data in the model chain node that generates the modification record to obtain the current model data;

[0136] Acquire the table, field and enumeration value corresponding to the model chain node generating the modification record from the virtual unified node to obtain the reference model data;

[0137] Comparing the current model data with the reference model data based on the audit rules of the model smart contract to generate a model audit result;

[0138] Perform hash calculation on the field of the field chain node that generates the modified record to obtain the current field data;

[0139] Obtain the field corresponding to the initial node in the field chain to obtain reference field data;

[0140] The current field data and the reference field data are compared based on the audit rules of the field smart contract to generate a field audit result.

[0141] In one embodiment, the distributed data model tampering risk assessment device further includes a contract editing module, which is used to:

[0142] Receive the input audit rules through the visualization page and generate regular expressions corresponding to the audit rules;

[0143] Load the regular expressions into the preset model smart contract and field smart contract respectively;

[0144] Among them, the model smart contract is used to audit at least one of the basic information, deployment node, version information, deployment time, deployment order and deployment integrity of the data model corresponding to each model chain node, and the field smart contract is used to audit at least one of the field name, data type, data length, field enumeration value definition, publishing node information, field version information and field deployment time of the data table of each data model.

[0145] The distributed data model tampering risk assessment device provided by the present application adopts the distributed data model tampering risk assessment method in the above-mentioned embodiment, which can solve the technical problem that the traditional distributed data model anti-tampering strategy cannot effectively and timely control the tampering of data. Compared with the prior art, the beneficial effects of the distributed data model tampering risk assessment device provided by the present application are the same as the beneficial effects of the distributed data model tampering risk assessment method provided by the above-mentioned embodiment, and the other technical features in the distributed data model tampering risk assessment device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0146] The present application provides an electronic device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the distributed data model tampering risk assessment method in the above-mentioned embodiment one.

[0147] Reference below Figure 5, which shows a schematic diagram of the structure of an electronic device suitable for implementing the embodiments of the present application. The electronic devices in the embodiments of the present application may include but are not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 5 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0148] like Figure 5 As shown, the electronic device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the electronic device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the electronic device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows an electronic device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0149] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0150] The electronic device provided by the present application adopts the distributed data model tampering risk assessment method in the above embodiment, which can solve the technical problem that the traditional distributed data model anti-tampering strategy cannot effectively and timely control the tampering of data. Compared with the prior art, the beneficial effects of the electronic device provided by the present application are the same as the beneficial effects of the distributed data model tampering risk assessment method provided by the above embodiment, and the other technical features in the electronic device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0151] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0152] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0153] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the distributed data model tampering risk assessment method in the above-mentioned embodiment.

[0154] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0155] The computer-readable storage medium may be included in the electronic device, or may exist independently without being installed in the electronic device.

[0156] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by an electronic device, the electronic device: converts the original unified data model into a unified model chain in a blockchain network according to the original deployment plan corresponding to the original unified data model, wherein the unified model chain includes at least a virtual unified node and a plurality of model chain nodes associated with and mapped to the virtual unified node; constructs a corresponding field chain according to the fields of the data model corresponding to each of the model chain nodes, wherein the field chain is used to record the field data in the data model; when the unified model chain or the field chain generates a modification record, audits the unified model chain or the field chain based on a preset smart contract to obtain a corresponding audit result; generates an audit report according to the audit result, wherein the audit report includes at least a tampering risk assessment result.

[0157] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0158] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0159] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0160] The readable storage medium provided in the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned distributed data model tampering risk assessment method, and can solve the technical problem that the traditional distributed data model anti-tampering strategy cannot effectively control the tampering of data in a timely manner. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in the present application are the same as the beneficial effects of the distributed data model tampering risk assessment method provided in the above-mentioned embodiment, which will not be repeated here.

[0161] The present application also provides a computer program product, including a computer program, which implements the steps of the above-mentioned distributed data model tampering risk assessment method when executed by a processor.

[0162] The computer program product provided by this application can solve the technical problem that the traditional anti-tampering strategy of the distributed data model cannot effectively and timely control the tampering of the data. Compared with the prior art, the beneficial effects of the computer program product provided by this application are the same as the beneficial effects of the distributed data model tampering risk assessment method provided by the above embodiment, which will not be repeated here.

[0163] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A distributed data model tampering risk assessment method, characterized in that: The distributed data model tampering risk assessment method comprises: Converting the original unified data model into a unified model chain in the blockchain network according to the original deployment scheme corresponding to the original unified data model, wherein the unified model chain includes at least a virtual unified node and a plurality of model chain nodes associated with and mapped to the virtual unified node; Constructing a corresponding field chain according to the field of the data model corresponding to each of the model chain nodes, wherein the field chain is used to record the field data in the data model; When the unified model chain or the field chain generates a modification record, the unified model chain or the field chain is audited based on a preset smart contract to obtain a corresponding audit result; An audit report is generated according to the audit result, wherein the audit report at least includes a tampering risk assessment result.

2. The distributed data model tampering risk assessment method according to claim 1, characterized in that: The step of converting the original unified data model into a unified model chain in the blockchain network according to the original deployment scheme corresponding to the original unified data model includes: Based on the original unified data model and the data model in the child node of the original deployment solution, a mapping relationship between the data model in the model chain node and the data model in the virtual unified node is established; According to the mapping relationship, a virtual unified node and a plurality of model chain nodes associated with the virtual unified node are generated to obtain a unified model chain.

3. The distributed data model tampering risk assessment method according to claim 2, characterized in that: The mapping relationship includes at least a table mapping relationship, a field mapping relationship and an enumeration value mapping relationship; The step of establishing a mapping relationship between the data model in the model chain node and the data model in the virtual unified node based on the original unified data model and the data model in the child node of the original deployment solution includes: Establishing a table mapping relationship according to the contents corresponding to the table in the original unified data model and the table in the data model in the child node; On the basis of the table mapping relationship, a field mapping relationship is established according to the field differences between the original unified data model and the data model in the child node; An enumeration value mapping relationship is established according to the original unified data model and the enumeration values ​​in the data model in the child node.

4. The distributed data model tampering risk assessment method according to claim 1, characterized in that: The step of constructing a corresponding field chain according to the fields of the data model corresponding to each of the model chain nodes includes: Traversing the data of each model chain node in the unified model chain, and reading the field content in each model chain node; A corresponding field chain is generated according to the field definition, field value and field format of the field content in each of the model chain nodes.

5. The distributed data model tampering risk assessment method according to claim 1, characterized in that: The smart contract includes at least a model smart contract and a field smart contract, the audit result includes at least a model audit result and a field audit result, and the step of auditing the unified model chain or the field chain based on the preset smart contract to obtain the corresponding audit result includes: Perform hash calculation on the model data in the model chain node that generates the modification record to obtain the current model data; Acquire the table, field and enumeration value corresponding to the model chain node generating the modification record from the virtual unified node to obtain the reference model data; Comparing the current model data with the reference model data based on the audit rules of the model smart contract to generate a model audit result; Perform hash calculation on the field of the field chain node that generates the modified record to obtain the current field data; Obtain the field corresponding to the initial node in the field chain to obtain reference field data; The current field data and the reference field data are compared based on the audit rules of the field smart contract to generate a field audit result.

6. The distributed data model tampering risk assessment method according to claim 5, characterized in that: Before the step of auditing the unified model chain or the field chain based on the preset smart contract, the method further includes: Receive the input audit rules through the visualization page and generate regular expressions corresponding to the audit rules; Load the regular expressions into the preset model smart contract and field smart contract respectively; Among them, the model smart contract is used to audit at least one of the basic information, deployment node, version information, deployment time, deployment order and deployment integrity of the data model corresponding to each model chain node, and the field smart contract is used to audit at least one of the field name, data type, data length, field enumeration value definition, publishing node information, field version information and field deployment time of the data table of each data model.

7. A distributed data model tampering risk assessment device, characterized in that: The distributed data model tampering risk assessment device comprises: A model chain construction module, used to convert the original unified data model into a unified model chain in the blockchain network according to the original deployment scheme corresponding to the original unified data model, wherein the unified model chain at least includes a virtual unified node and a plurality of model chain nodes associated with and mapped to the virtual unified node; A field chain building module, used to build a corresponding field chain according to the field of the data model corresponding to each of the model chain nodes, wherein the field chain is used to record the field data in the data model; A contract audit module, used for auditing the unified model chain or the field chain based on a preset smart contract when a modification record is generated in the unified model chain or the field chain, and obtaining a corresponding audit result; A report generation module is used to generate an audit report based on the audit results, wherein the audit report at least includes tampering risk assessment results.

8. An electronic device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the distributed data model tampering risk assessment method according to any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the distributed data model tampering risk assessment method as described in any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the distributed data model tampering risk assessment method according to any one of claims 1 to 6 are implemented.

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