Fire data security sharing method, system and equipment based on cloud platform

Abstract

The present invention relates to the field of digital information transmission technology, and specifically to a cloud platform-based fire protection data security sharing method, system, and device, including: obtaining the risk level of modified data transmission for each user, determining the abnormality level of data modification for each user in each time period based on the difference in the number of times each user updates and modifies data in adjacent time periods, and combining the correlation of elements in adjacent time periods in data sets of all dimensions, thereby updating the modification transmission priority of each user, and judging whether the updated and modified content of the data currently updated and modified by each user is uploaded and shared based on the difference between fire protection acceptance specifications and updated and modified content. The present invention updates the modification transmission priority by analyzing the user's authority and data sensitivity, and then combines the difference between fire protection acceptance specifications and updated and modified data to ensure the security of the data transmission sharing process.

Description

Technical Field

[0001] The present invention relates to the technical field of digital information transmission, and in particular to a method, system and equipment for securely sharing fire protection data based on a cloud platform. Background Art

[0002] Fire safety has received increasing attention and attention in recent years. The proper operation and routine maintenance of firefighting facilities are particularly crucial. However, the current safety management system for firefighting facilities is inadequate, often relying solely on personnel inspections, which often fail to promptly identify safety hazards. By using IoT technology to connect firefighting equipment to user terminals via the internet, establishing a networked fire monitoring system can facilitate real-time monitoring of firefighting facility operations, timely troubleshooting, and tracing equipment maintenance and management.

[0003] The fire protection industry possesses vast amounts of business data, and sharing this data involves the division of permissions among multiple users or accessors. Cloud storage technology facilitates efficient data sharing within the fire protection industry, but it also presents numerous security issues during the data sharing and aggregation process, such as accidental loss or corruption of cloud-stored data, data privacy breaches, and malicious access by unauthorized users. Because networked fire protection monitoring systems require data to be immutable and exchanged rapidly, the aggregation of data during fire inspections is often combined with audit tracking.

[0004] Existing problems: Data sharing during the building completion fire inspection process involves diverse user attributes (such as construction units, supervision units, and fire departments, etc.). Different departments have different levels of access to project data and different management permissions. Existing audit tracking methods can only record users' access and modification behaviors to project data on the platform. When multiple users modify the same project data, audit tracking cannot coordinate the operation sequence between multiple users in real time, causing the data modification processes of multiple users to interfere with each other. When there are logical inconsistencies between the modified contents, it may lead to errors in the project data sharing scope on the platform. Summary of the Invention

[0005] The present invention provides a fire protection data security sharing method, system and equipment based on a cloud platform to solve existing problems.

[0006] The cloud platform-based fire data security sharing method, system and equipment of the present invention adopt the following technical solutions:

[0007] One embodiment of the present invention provides a method for securely sharing fire protection data based on a cloud platform, the method comprising the following steps:

[0008] For several dimensions in a building project, obtain the fire acceptance standards for each dimension, the data set for each dimension, the modification transmission priority of each user, the time and content of each update and modification by each user, and the number of dimension types each user is allowed to update and modify;

[0009] Determine the risk level of each user's modified data transmission based on the number of dimensions that different users are allowed to update and modify.

[0010] Divide the time periods and determine the degree of abnormality of each user's data modification in each time period based on the difference in the number of times each user updates and modifies data in adjacent time periods, combined with the correlation of elements in adjacent time periods in the data sets of all dimensions;

[0011] According to the abnormal degree of data modification of each user in each time period and the risk degree of each user's modification data transmission, the modification transmission priority of each user is updated to obtain the modification transmission update priority of each user. Combined with the fire acceptance specifications of each dimension and the difference between the updated modification content of each user's updated data each time, it is determined whether the updated modification content of each user's current updated data is uploaded and shared.

[0012] Furthermore, the step of determining the risk level of data transmission modification for each user includes the following specific steps:

[0013] Each element in the data set of each dimension is divided into a presence modification element and a non-presence modification element, and the presence modification element corresponds to a number of users;

[0014] The ratio of the number of dimension types that the i-th user is allowed to update and modify to the number of all dimension types is recorded as the i-th user's modification permission range for project data;

[0015] In the data set of the g-th dimension, obtain the ratio of the number of modified elements corresponding to the i-th user to the number of all elements, and record it as the data transmission status of the i-th user in the g-th dimension;

[0016] Determine the data transmission duplication between the i-th user and the j-th user based on the difference in the scope of the project data modification permissions between the i-th user and the j-th user, as well as the difference in the data transmission status between the i-th user and the j-th user in each dimension;

[0017] Obtain the mean of the data transmission repeatability between the i-th user and all other users, and record it as the risk level of data transmission modification of the i-th user.

[0018] Furthermore, the determining of the data transmission repetitiveness between the i-th user and the j-th user includes the following specific steps:

[0019] Get the absolute value of the difference between the modification permissions of the i-th user and the j-th user for project data The inverse proportional normalized value of is used to calculate the absolute value of the difference between the data transmission conditions of the i-th user and the j-th user in the g-th dimension, and then the sum of the absolute values ​​of the difference between the data transmission conditions of the i-th user and the j-th user in all dimensions is calculated. The inverse proportional normalized value of The inversely proportional normalized value is The product of the inversely proportional normalized values ​​of is recorded as the data transmission repeatability of the i-th user and the j-th user.

[0020] Furthermore, the specific steps of determining the abnormal degree of data modification of each user in each time period include the following:

[0021] The first time duration C is preset, and starting from the current time, a number of non-repeating time periods of duration C are divided in reverse chronological order;

[0022] Based on the time when the i-th user updates and modifies the data each time, count the number of times the i-th user updates and modifies the data in the x-th time period. In chronological order, take the absolute value of the difference between the number of times the i-th user updates and modifies the data in the x-1th time period and the x-th time period, and record it as the difference value of the number of information modifications and updates for the i-th user in the x-th time period;

[0023] Each element in the data set of each dimension corresponds to a timestamp. In the data sets of all dimensions, based on the timestamp of each element, the set consisting of all elements in the x-th time period is counted and recorded as the total set of the x-th time period;

[0024] Determine the degree of change in information modification and update performed by the i-th user in the x-th time period based on the correlation between the total set of the x-1-th time period and the x-th time period and the difference in the number of information modification and update times of the i-th user in the x-th time period;

[0025] Obtain the intersection and union of the total set of the x-1th time period and the xth time period respectively, and record the ratio of the number of elements in the intersection to the number of elements in the union as the data modification and update overlap process in the xth time period;

[0026] The abnormality degree of the data modification of the i-th user in the x-th time period is determined based on the change degree of the information modification and update performed by the i-th user in the x-th time period and the overlap degree of the data modification and update in the x-th time period.

[0027] Furthermore, the step of determining the degree of change of information modification and update performed by the i-th user in the x-th time period includes the following specific steps:

[0028] Using the Jaccard similarity measurement method, the correlation between the total set of the x-1th time period and the xth time period is obtained, and the inverse proportional value of the correlation between the total set of the x-1th time period and the xth time period is recorded as the project data dissimilarity of the xth time period;

[0029] Obtain the minimum value among the difference values ​​of the number of information modifications and updates of the i-th user in all time periods, subtract the difference of the number of information modifications and updates of the i-th user in the x-th time period from the minimum value, and record it as the first difference value; multiply the first difference value by the dissimilarity of the project data in the x-th time period, and record it as the degree of change of the information modification and update performed by the i-th user in the x-th time period.

[0030] Furthermore, the step of determining the abnormality level of data modification of the i-th user in the x-th time period includes the following specific steps:

[0031] Get the mean of the degree of change in the information modification and update performed by the i-th user in all time periods, recorded as the first mean. Then, obtain the inversely proportional normalized value of the absolute value of the difference between the degree of change in the information modification and update performed by the i-th user in the x-th time period and the first mean, recorded as the consistency of the information modification and update performed by the i-th user in the x-th time period.

[0032] Obtain the absolute value of the consistency difference between the information modification and update of the i-th user in the x-1th time period and the x-th time period, and record it as the first absolute value of the difference. Take the inverse proportional normalized value of the ratio of the degree of overlap of data modification and update in the x-th time period to the first absolute value of the difference, and record it as the degree of data modification anomaly of the i-th user in the x-th time period.

[0033] Furthermore, the specific steps of obtaining the modification transmission update priority of each user include the following:

[0034] A second duration H is preset, and starting from the current moment, a number of non-repeating update time periods of duration H are sequentially divided in reverse chronological order; H is greater than the preset first duration C, and H is an integer multiple of C;

[0035] In the yth update time period, obtain the average of the data modification abnormality levels of the i-th user in all time periods, and record it as the data modification abnormality level of the i-th user in the yth update time period;

[0036] The average of the absolute values ​​of the differences in the abnormal degree of data modification of the i-th user in all two adjacent update time periods is recorded as the data sensitivity of the i-th user;

[0037] The product of the normalized value of the data sensitivity of the i-th user and the risk level of the i-th user's modified data transmission is recorded as the attention level of the i-th user's data transmission;

[0038] The ratio of the modification transmission priority of the i-th user to the attention level of the data transmission of the i-th user is recorded as the modification transmission update priority of the i-th user.

[0039] Furthermore, the specific steps of determining whether the updated and modified data of each user is uploaded and shared include the following:

[0040] Based on the fire acceptance standards of all dimensions, use difference analysis to obtain the degree of deviation between the updated and modified content of each user and the fire acceptance standards;

[0041] The inversely proportional normalized value of the product of the i-th user's modification transmission update priority and the degree of deviation between the i-th user's current update content and the fire protection acceptance specification is recorded as the credibility of the i-th user's current update data;

[0042] If the credibility of the data updated and modified by the i-th user is greater than the preset credibility threshold, the updated and modified content of the data updated and modified by the i-th user will be uploaded and shared;

[0043] If the credibility of the data updated and modified by the i-th user is less than or equal to the preset credibility threshold, the updated and modified content of the data updated and modified by the i-th user will not be uploaded and shared.

[0044] The present invention also proposes a fire data security sharing system based on a cloud platform, which adopts any of the fire data security sharing methods based on a cloud platform. The system includes the following modules:

[0045] Data collection module: For several dimensions in a construction project, it obtains the fire protection acceptance specifications for each dimension, the data set for each dimension, the modification transmission priority of each user, the time and content of each data update by each user, and the number of dimension types each user is allowed to update and modify;

[0046] Transmission risk analysis module: Determines the degree of risk of data transmission for each user based on the number of dimensions that different users are allowed to update and modify.

[0047] Anomaly Analysis Module: This module divides the time periods into sections and determines the degree of data modification anomaly for each user in each time period based on the difference in the number of occurrences of each user's data modification in adjacent time periods and the correlation between elements in adjacent time periods in the data sets of all dimensions.

[0048] Security sharing module: Based on the degree of data modification anomalies of each user in each time period and the degree of risk of each user's modified data transmission, the modification transmission priority of each user is updated to obtain the modification transmission update priority of each user. Combined with the fire acceptance specifications of each dimension and the difference in the updated modification content of each user's updated data each time, it is determined whether the updated modification content of each user's current updated data is uploaded and shared.

[0049] The present invention also proposes a fire data security sharing device based on a cloud platform, including a memory, a processor, and a computer program stored in the memory and runnable on the processor. The processor executes the computer program stored in the memory to implement the steps of the aforementioned cloud platform-based fire data security sharing method.

[0050] The beneficial effects of the technical solution of the present invention are:

[0051] In an embodiment of the present invention, the risk level of each user's modified data transmission is obtained, and the risk level of the modified data transmission is determined by analyzing the modification permissions and modification contents possessed by the user, so as to ensure the accuracy of subsequent modification transmission priority updates. The time periods are divided, and the abnormality level of each user's data modification in each time period is determined based on the difference in the number of occurrences of each user's update and modification time in adjacent time periods, combined with the correlation of elements in adjacent time periods in the data set of all dimensions, so as to update the modification transmission priority of each user, and combine the difference between the fire acceptance specifications of each dimension and the updated modification contents of each user's updated data to determine whether the updated modification contents of each user's current data update are uploaded and shared, thereby avoiding project data errors or distortions caused by multiple users' data transmission during the project data update process, and thus ensuring the security and accuracy of the project data during the sharing process. At this point, the present invention updates the modification transmission priority by analyzing the user's permissions and data sensitivity, and then combines the difference between the fire acceptance specifications and the updated modification data to ensure the security of the data transmission sharing process. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0053] Figure 1 This is a flowchart of the steps of the cloud platform-based fire data security sharing method of the present invention;

[0054] Figure 2 This is a structural block diagram of the cloud platform-based fire data security sharing system of the present invention. DETAILED DESCRIPTION

[0055] To further illustrate the technical means and effectiveness of the present invention in achieving its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features, and effectiveness of the cloud-based fire data security sharing method, system, and device proposed by the present invention. In the following description, different references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0056] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0057] The specific solutions of the fire protection data security sharing method, system and equipment based on the cloud platform provided by the present invention are described in detail below with reference to the accompanying drawings.

[0058] See also Figure 1 , which shows a flowchart of a method for securely sharing fire data based on a cloud platform provided by one embodiment of the present invention, the method comprising the following steps:

[0059] Step S001: For several dimensions in a construction project, obtain the fire inspection and acceptance specifications for each dimension, the data set for each dimension, the modification transmission priority for each user, the time and content of each data update and modification by each user, and the number of dimension types that each user is allowed to update and modify.

[0060] First, a fire protection data storage and sharing platform is established using a distributed architecture. Then, a set of all data in each dimension of any building project is obtained from the shared data storage platform. Each data element in each dimension is associated with a timestamp. Each element in the data set for each dimension is associated with a timestamp. Each element is divided into a presence-modified element and a non-modified element. Each presence-modified element corresponds to a number of users.

[0061] It should be noted that the various dimensions within a construction project include: project design drawings, construction progress data, fire protection equipment layout parameters during construction, on-site inspection data from the supervisory department, review and acceptance analysis data, and rectification records. Each dimension is assigned corresponding fire protection acceptance specifications. Each fire protection management platform or user uploads relevant business information, which is encrypted and stored within the corresponding project on the platform to provide a basis for subsequent review and use. When project data is updated or modified, the platform automatically records relevant information about the update operation, including the operating user, modification time, and update and modification content. When a piece of data is modified multiple times by different users, it is associated with multiple users. An audit tracking mechanism monitors the project data modification process in real time, capturing and saving detailed records of the modification data and generating a traceable audit log by project name. Log parsing tools are used to process the collected audit logs, extracting structured information from the logs, including user IP address, time, and operation. Each user on the platform has two modification permissions for each dimension: allowed or denied. The greater the user's permission, the higher the modification transmission priority. The platform's permission management tool is used to obtain a quantitative value for each user's permission level, which serves as the modification transmission priority for each user.

[0062] Step S002: Determine the risk level of each user's modified data transmission based on the difference in the number of dimension types that different users are allowed to update and modify.

[0063] It should be noted that in the fire protection data storage and sharing platform, due to the real-time modification and update of project data by different users, the existing audit tracking log can only record the data content and timestamp of the user's modification, but cannot detect the transmission priority of the data during transmission, or whether the modified data meets the project's correctness standards or the consistency of the original data. Therefore, this embodiment analyzes the real-time modification data tracked by the audit log to determine the risk level of the modified data. It further compares the deviation of the project data before and after the modification with contextual information, analyzes the impact of the modified data, and then determines the transmission priority of different modified data. In other words, when there are multiple users uploading modifications at the same time, the following analysis is performed.

[0064] It's also important to note that data transmission within a project node involves multiple users, each with varying access rights to project data. For example, a fire engineer may have access to all fire equipment parameters and modifications, while the construction team may modify fire equipment data for the entire project construction process and transmit rectification results. Different users have varying degrees of data access, so the data transmission risk level for a user updating or modifying project data is first determined based on their permissions and the degree of duplication with other users in the project.

[0065] Preferably, in one embodiment of the present invention, the method for obtaining the modified data transmission risk level of each user includes:

[0066] Taking the i-th user as an example, the ratio of the number of dimension types that the i-th user is allowed to update and modify to the number of all dimension types is recorded as the i-th user's modification permission range for project data.

[0067] In the data set of the g-th dimension, the ratio of the number of modified elements corresponding to the i-th user to the number of all elements is obtained, which is recorded as the data transmission status of the i-th user in the g-th dimension.

[0068] Get the absolute value of the difference between the modification permissions of the i-th user and the j-th user for project data The inverse proportional normalized value of is used to calculate the absolute value of the difference between the data transmission conditions of the i-th user and the j-th user in the g-th dimension, and then the sum of the absolute values ​​of the difference between the data transmission conditions of the i-th user and the j-th user in all dimensions is calculated. The inverse proportional normalized value of The inversely proportional normalized value is The product of the inversely proportional normalized values ​​of is recorded as the data transmission repeatability of the i-th user and the j-th user, where i is not equal to j.

[0069] It should be noted that: in this embodiment, and As the The inversely proportional normalized value is The inverse normalized value of It is a linear normalization function used to normalize data values ​​between 0 and 1. The smaller it is, the more similar the modification permissions of the two users in the project are. The smaller the value, the more similar the data transmission situations of the two users in the same dimension are. The inversely proportional normalized value is The product of the inversely proportional normalized values ​​of is taken as the data transmission repeatability between the i-th user and the j-th user. The greater the data transmission repeatability, the greater the possibility that the i-th user will be affected by the j-th user during the process of updating and modifying project data.

[0070] Obtain the mean of the data transmission repeatability between the i-th user and all other users, and record it as the risk level of data transmission modification of the i-th user.

[0071] It should be noted that: the greater the repetitiveness of data transmission between the i-th user and all other users, the greater the possibility of conflict in the data transmission modification processes of multiple users, that is, the greater the risk of data transmission modification.

[0072] Step S003: Divide the time periods, and determine the degree of abnormality of data modification for each user in each time period based on the difference in the number of times each user updates and modifies data in adjacent time periods, combined with the correlation of elements in adjacent time periods in the data sets of all dimensions.

[0073] It should be noted that as the acceptance process progresses, multiple users may modify and adjust project data. When multiple users modify and update project data simultaneously within the same time period, data transmission conflicts may occur, leading to errors or distortions in the construction project data transmitted by different users. Consequently, data analysis may reveal discrepancies in the fire acceptance inspection results for the construction project. Therefore, this embodiment utilizes audit tracking technology, combined with the contextual information of project data transmitted by different users, to compare the magnitude of changes between the updated data and the original data. By analyzing the degree of abnormality in data modifications and updates, the degree of concern for different users' data transmission can be determined.

[0074] Preferably, in one embodiment of the present invention, the method for obtaining the abnormal degree of data modification of each user in each time period includes:

[0075] The first duration C is preset to 1 hour, and this is used as an example for description.

[0076] Starting from the current moment, a number of non-repeating time periods of length C are divided in reverse chronological order.

[0077] For example, if the current time is 10:00, the time periods are 10:00 to 9:00, 9:00 to 8:00, and 8:00 to 7:00, etc. The end time of the time period division is the start time of the dimension data collection in the construction project. If the duration of the last time period is less than C, it is also considered a time period.

[0078] According to the time when the i-th user updates and modifies the data each time, the number of times the i-th user updates and modifies the data in the x-th time period is counted. In chronological order, the absolute value of the difference between the number of times the i-th user updates and modifies the data in the x-1-th time period and the x-th time period is recorded as the difference value of the number of information modifications and updates of the i-th user in the x-th time period.

[0079] It should be noted that in this embodiment, the first time period is not analyzed according to the chronological order.

[0080] In the data sets of all dimensions, according to the timestamp of each element, the set consisting of all elements in the x-th time period is counted and recorded as the total set of the x-th time period.

[0081] The Jaccard similarity measurement method is used to obtain the correlation between the total set of the x-1th time period and the xth time period, and the inverse proportional value of the correlation between the x-1th time period and the total set of the xth time period is recorded as the project data dissimilarity of the xth time period.

[0082] Among them, the Jaccard similarity measurement method is a well-known technology, and the specific method is not introduced here. The value range of the correlation obtained by the Jaccard similarity measurement method is between 0 and 1. Therefore, in this embodiment, the difference between 1 and the correlation is used as the inverse proportional value of the correlation.

[0083] Obtain the minimum value among the difference values ​​of the number of information modifications and updates of the i-th user in all time periods, subtract the difference of the number of information modifications and updates of the i-th user in the x-th time period from the minimum value, and record it as the first difference value; multiply the first difference value by the dissimilarity of the project data in the x-th time period, and record it as the degree of change of the information modification and update performed by the i-th user in the x-th time period.

[0084] It should be noted that when a user modifies the same area of ​​building content multiple times, the modified data becomes more correlated. Therefore, the greater the correlation between the total set of information modifications between the x-1th time period and the xth time period, and the greater the difference in the number of times the i-th user modified and updated information within the xth time period, the greater the degree of change in the information modification and update. This, combined with contextual information related to the user's modification and update data, analyzes the logical consistency between the data modification deviation and the original project data, and calculates the degree of data modification anomaly.

[0085] Get the mean of the degree of change of information modification and update performed by the i-th user in all time periods, record it as the first mean, and then get the absolute value of the difference between the degree of change of information modification and update performed by the i-th user in the x-th time period and the first mean The inverse proportional normalized value of is recorded as the consistency of the information modification and update performed by the i-th user in the x-th time period.

[0086] It should be noted that: in this embodiment, As The inverse normalized value of It is a linear normalization function used to normalize data values ​​between 0 and 1. The greater the consistency, the more complex the changes in the data modification and update content during the x-th time period, and the less consistent the data modification and update content is with the original data.

[0087] The intersection and union of the total set of the x-1th time period and the xth time period are obtained respectively, and the ratio of the number of elements in the intersection to the number of elements in the union is recorded as the degree of data modification and update overlap in the xth time period.

[0088] Get the absolute value of the consistency difference between the information modification and update of the i-th user in the x-1th time period and the x-th time period, record it as the first absolute value of the difference, and calculate the ratio of the degree of overlap of data modification and update in the x-th time period to the first absolute value of the difference. The inverse proportional normalized value of is recorded as the abnormal degree of data modification of the i-th user in the x-th time period.

[0089] It should be noted that: in this embodiment, As The inverse normalized value of It is a linear normalization function used to normalize data values ​​between 0 and 1. The greater the overlap of data modifications and updates in two adjacent time periods, and the more consistent the information modifications and updates in two adjacent time periods, it means that the user mainly made corrections to the same area or part of the construction project, without significant reverse adjustments or abnormal changes, and therefore the degree of data modification anomaly is smaller.

[0090] Step S004: Update the modification transmission priority of each user according to the abnormal degree of data modification of each user in each time period and the risk degree of modification data transmission of each user, and obtain the modification transmission update priority of each user. Combined with the fire acceptance specifications of each dimension and the difference between the update modification content of each user's updated data each time, determine whether the update modification content of each user's current update modification data is uploaded and shared.

[0091] What needs to be explained is that based on the audit log records on the platform project node, the fluctuation of the project's modified abnormal data over a period of time is determined. When a project is modified multiple times within a certain period of time, and the modification process involves a large amount of abnormal data, it indicates that the possibility of data transmission conflicts during the real-time update of the project data is greater. When the changes in the project's modified abnormal data are relatively consistent at several moments, it indicates that the fire protection data carried by the project is less sensitive and the risk of being tampered with during the real-time update process is relatively small. Therefore, this embodiment uses the volatility of abnormal data in the user's historical transmission data to analyze the degree of attention paid to user data.

[0092] Preferably, in one embodiment of the present invention, the method for determining whether the updated or modified content of the data currently updated or modified by each user is uploaded and shared includes:

[0093] The second time period H is preset to be 1 month, which is used as an example for description. The second time period H is greater than the first time period C, and H is an integer multiple of C.

[0094] Starting from the current moment, a number of non-repeating update time periods of length H are divided in reverse chronological order.

[0095] The stop time of the update time period is the start time of the dimension data collection in the building project. If the duration of the last update time period is less than H, it is also an update time period.

[0096] In the yth update time period, obtain the average of the data modification abnormality levels of the i-th user in all time periods, and record it as the data modification abnormality level of the i-th user in the yth update time period.

[0097] Obtain the absolute value of the difference in the degree of data modification anomaly of the i-th user in any two adjacent update time periods, and record the average of the absolute value of the difference in the degree of data modification anomaly of the i-th user in all two adjacent update time periods as the data sensitivity of the i-th user.

[0098] It should be noted that the data stability of users in different time periods varies. By analyzing the variation in the modified data of the same user between different months, we can focus on data with obvious fluctuations, that is, the more sensitive the data, the more attention it needs.

[0099] The product of the normalized value of the data sensitivity of the i-th user and the risk level of the modified data transmission of the i-th user is recorded as the attention level of the data transmission of the i-th user.

[0100] It should be noted that in this embodiment, the maximum and minimum data sensitivities of all users are obtained, and the ratio of the difference between the i-th user's data sensitivity and the minimum value is used as the normalized value of the i-th user's data sensitivity. The greater the data sensitivity and the greater the risk of data modification, the more attention should be paid to the data transmission.

[0101] The ratio of the modification transmission priority of the i-th user to the attention level of the data transmission of the i-th user is recorded as the modification transmission update priority of the i-th user.

[0102] It should be noted that when multiple users simultaneously modify and update project data within the same time period, data with less attention and less data volatility and risk should be prioritized to reduce conflicts during data transmission. Data with a high level of attention and a higher risk or abnormal changes should be transmitted with a delay to ensure that the data has an opportunity for error repair or verification. Therefore, the ratio of the modification transmission priority to the level of attention received by the data transmission is used as the modification transmission update priority. Therefore, if multiple users have the same modification uploaded at the current moment, each user's modified data will be uploaded in descending order of modification transmission update priority.

[0103] Based on the fire acceptance standards of all dimensions, variance analysis is used to obtain the degree of deviation between the updated and modified content of each user's data and the fire acceptance standards.

[0104] It should be noted that variance analysis is a well-known technique, and the specific method is not described here. Each user's data update includes updated data in several different dimensions. Based on the fire safety acceptance standards for each dimension, variance analysis can be used to determine the difference between the updated data and the acceptance standards for each dimension. The sum of the differences between the updated data for all dimensions and the corresponding acceptance standards for each user's data update is used as the degree of deviation from the fire safety acceptance standards for each user's data update.

[0105] The product of the modification transmission update priority of the i-th user and the deviation degree between the updated content of the i-th user's current update and the fire acceptance specification The inversely proportional normalized value of is recorded as the credibility of the data updated by the i-th user this time.

[0106] It should be noted that: in this embodiment, As The inverse normalized value of It is a linear normalization function used to normalize data values ​​between 0 and 1. For data with higher priority, when the data itself does not meet the fire inspection and acceptance standards, the fluctuation is small, indicating that the user's modification range is small, which will amplify the deviation of the modified data and make the modified data less credible.

[0107] The preset trust threshold is 0.5, and this is used as an example for description.

[0108] If the credibility of the data updated by the i-th user is greater than the preset credibility threshold, the updated content of the data updated by the i-th user will be uploaded and shared. This means that the updated data is accurate and meets the fire protection acceptance standards and should be uploaded and shared.

[0109] If the credibility of the data updated by the i-th user is less than or equal to the preset credibility threshold, the updated content of the data will not be uploaded and shared. The updated content of the data updated by the i-th user will be marked in the database, and an alarm will be issued to prompt relevant personnel to conduct further review and processing, thereby ensuring safe sharing.

[0110] Second, see Figure 2 , which shows a fire data security sharing system based on a cloud platform provided by an embodiment of the present invention, which includes the following modules:

[0111] Data collection module: For several dimensions in a construction project, it obtains the fire protection acceptance specifications for each dimension, the data set for each dimension, the modification transmission priority of each user, the time and content of each data update by each user, and the number of dimension types each user is allowed to update and modify;

[0112] Transmission risk analysis module: Determines the degree of risk of data transmission for each user based on the number of dimensions that different users are allowed to update and modify.

[0113] Anomaly Analysis Module: This module divides the time periods into sections and determines the degree of data modification anomaly for each user in each time period based on the difference in the number of occurrences of each user's data modification in adjacent time periods and the correlation between elements in adjacent time periods in the data sets of all dimensions.

[0114] Security sharing module: Based on the degree of data modification anomalies of each user in each time period and the degree of risk of each user's modified data transmission, the modification transmission priority of each user is updated to obtain the modification transmission update priority of each user. Combined with the fire acceptance specifications of each dimension and the difference in the updated modification content of each user's updated data each time, it is determined whether the updated modification content of each user's current updated data is uploaded and shared.

[0115] The present invention also provides a fire data security sharing device based on a cloud platform, including a memory, a processor, and a computer program stored in the memory and runnable on the processor. The processor executes the computer program stored in the memory to implement the steps of the aforementioned cloud platform-based fire data security sharing method.

[0116] So far, the present invention is completed.

[0117] In summary, in an embodiment of the present invention, the risk level of data transmission modification for each user is obtained, and time periods are divided. Based on the difference in the number of occurrences of each user's data modification time in adjacent time periods, combined with the correlation of elements in adjacent time periods in the data set of all dimensions, the abnormality level of each user's data modification in each time period is determined, thereby updating the modification transmission priority of each user, and combining the difference between the fire acceptance specifications of each dimension and the updated modification content of each user's updated data to determine whether the updated modification content of each user's current data modification is uploaded and shared. The present invention updates the modification transmission priority by analyzing the user's authority and data sensitivity, and then combines the difference between the fire acceptance specifications and the updated modification data to ensure the security of the data transmission sharing process.

[0118] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A fire protection data security sharing method based on a cloud platform, characterized in that: The method comprises the following steps: For several dimensions in a building project, obtain the fire acceptance standards for each dimension, the data set for each dimension, the modification transmission priority of each user, the time and content of each update and modification by each user, and the number of dimension types each user is allowed to update and modify; Determine the risk level of each user's modified data transmission based on the number of dimensions that different users are allowed to update and modify. Divide the time periods and determine the degree of abnormality of each user's data modification in each time period based on the difference in the number of times each user updates and modifies data in adjacent time periods, combined with the correlation of elements in adjacent time periods in the data sets of all dimensions; According to the abnormal degree of data modification of each user in each time period and the risk degree of each user's modification data transmission, the modification transmission priority of each user is updated to obtain the modification transmission update priority of each user. Combined with the fire acceptance specifications of each dimension and the difference between the updated modification content of each user's updated data each time, it is determined whether the updated modification content of each user's current updated data is uploaded and shared.

2. The fire protection data security sharing method based on the cloud platform according to claim 1 is characterized in that: The specific steps of determining the risk level of data transmission modification for each user include the following: Each element in the data set of each dimension is divided into a presence modification element and a non-presence modification element, and the presence modification element corresponds to a number of users; The ratio of the number of dimension types that the i-th user is allowed to update and modify to the number of all dimension types is recorded as the i-th user's modification permission range for project data; In the data set of the g-th dimension, obtain the ratio of the number of modified elements corresponding to the i-th user to the number of all elements, and record it as the data transmission status of the i-th user in the g-th dimension; Determine the data transmission duplication between the i-th user and the j-th user based on the difference in the scope of the project data modification permissions between the i-th user and the j-th user, as well as the difference in the data transmission status between the i-th user and the j-th user in each dimension; Obtain the mean of the data transmission repeatability between the i-th user and all other users, and record it as the risk level of data transmission modification of the i-th user.

3. The fire protection data security sharing method based on the cloud platform according to claim 2 is characterized in that: The specific steps of determining the data transmission repetitiveness between the i-th user and the j-th user are as follows: Obtain an inversely proportional normalized value of the absolute value of the difference between the scope of modification permissions of the i-th user and the j-th user for project data, calculate the absolute value of the difference between the data transmission conditions of the i-th user and the j-th user in the g-th dimension, and then calculate the inversely proportional normalized value of the sum of the absolute values ​​of the difference between the data transmission conditions of the i-th user and the j-th user in all dimensions, and record the product of the inversely proportional normalized value and the inversely proportional normalized value as the data transmission repeatability between the i-th user and the j-th user.

4. The fire protection data security sharing method based on the cloud platform according to claim 1 is characterized in that: The specific steps of determining the abnormality of data modification for each user in each time period are as follows: The first time duration C is preset, and starting from the current time, a number of non-repeating time periods of duration C are divided in reverse chronological order; Based on the time when the i-th user updates and modifies the data each time, count the number of times the i-th user updates and modifies the data in the x-th time period. In chronological order, take the absolute value of the difference between the number of times the i-th user updates and modifies the data in the x-1th time period and the x-th time period, and record it as the difference value of the number of information modifications and updates for the i-th user in the x-th time period; Each element in the data set of each dimension corresponds to a timestamp. In the data sets of all dimensions, based on the timestamp of each element, the set consisting of all elements in the x-th time period is counted and recorded as the total set of the x-th time period; Determine the degree of change in information modification and update performed by the i-th user in the x-th time period based on the correlation between the total set of the x-1-th time period and the x-th time period and the difference in the number of information modification and update times of the i-th user in the x-th time period; Obtain the intersection and union of the total set of the x-1th time period and the xth time period respectively, and record the ratio of the number of elements in the intersection to the number of elements in the union as the data modification and update overlap process in the xth time period; The abnormality degree of the data modification of the i-th user in the x-th time period is determined based on the change degree of the information modification and update performed by the i-th user in the x-th time period and the overlap degree of the data modification and update in the x-th time period.

5. The fire protection data security sharing method based on the cloud platform according to claim 4 is characterized in that: The specific steps of determining the degree of change of information modification and update performed by the i-th user in the x-th time period include the following: Using the Jaccard similarity measurement method, the correlation between the total set of the x-1th time period and the xth time period is obtained, and the inverse proportional value of the correlation between the total set of the x-1th time period and the xth time period is recorded as the project data dissimilarity of the xth time period; Obtain the minimum value among the difference values ​​of the number of information modifications and updates of the i-th user in all time periods, subtract the difference of the number of information modifications and updates of the i-th user in the x-th time period from the minimum value, and record it as the first difference value; multiply the first difference value by the dissimilarity of the project data in the x-th time period, and record it as the degree of change of the information modification and update performed by the i-th user in the x-th time period.

6. The fire protection data security sharing method based on the cloud platform according to claim 4 is characterized in that: The specific steps of determining the abnormality degree of data modification of the i-th user in the x-th time period include the following: Get the mean of the degree of change in the information modification and update performed by the i-th user in all time periods, recorded as the first mean. Then, obtain the inversely proportional normalized value of the absolute value of the difference between the degree of change in the information modification and update performed by the i-th user in the x-th time period and the first mean, recorded as the consistency of the information modification and update performed by the i-th user in the x-th time period. Obtain the absolute value of the consistency difference between the information modification and update of the i-th user in the x-1th time period and the x-th time period, and record it as the first absolute value of the difference. Take the inverse proportional normalized value of the ratio of the degree of overlap of data modification and update in the x-th time period to the first absolute value of the difference, and record it as the degree of data modification anomaly of the i-th user in the x-th time period.

7. The fire protection data security sharing method based on the cloud platform according to claim 4 is characterized in that: The specific steps of obtaining the modification transmission update priority of each user include the following: A second duration H is preset, and starting from the current moment, a number of non-repeating update time periods of duration H are sequentially divided in reverse chronological order; H is greater than the preset first duration C, and H is an integer multiple of C; In the yth update time period, obtain the average of the data modification abnormality levels of the i-th user in all time periods of length C, and record it as the data modification abnormality level of the i-th user in the yth update time period; The average of the absolute values ​​of the differences in the abnormal degree of data modification of the i-th user in all two adjacent update time periods is recorded as the data sensitivity of the i-th user; The product of the normalized value of the data sensitivity of the i-th user and the risk level of the i-th user's modified data transmission is recorded as the attention level of the i-th user's data transmission; The ratio of the modification transmission priority of the i-th user to the attention level of the data transmission of the i-th user is recorded as the modification transmission update priority of the i-th user.

8. The fire protection data security sharing method based on cloud platform according to claim 1 is characterized in that: The specific steps of determining whether the updated and modified content of the data currently updated and modified by each user is uploaded and shared include the following: Based on the fire acceptance standards of all dimensions, use difference analysis to obtain the degree of deviation between the updated and modified content of each user and the fire acceptance standards; The inversely proportional normalized value of the product of the i-th user's modification transmission update priority and the degree of deviation between the i-th user's current update content and the fire protection acceptance specification is recorded as the credibility of the i-th user's current update data; If the credibility of the data updated and modified by the i-th user is greater than the preset credibility threshold, the updated and modified content of the data updated and modified by the i-th user will be uploaded and shared; If the credibility of the data updated and modified by the i-th user at the current time is less than or equal to the preset credibility threshold, the updated and modified content of the data updated and modified by the i-th user at the current time will not be uploaded and shared.

9. A fire protection data security sharing system based on a cloud platform, adopting a fire protection data security sharing method based on a cloud platform as claimed in any one of claims 1 to 8, characterized in that: The system includes the following modules: Data collection module: For several dimensions in a construction project, it obtains the fire protection acceptance specifications for each dimension, the data set for each dimension, the modification transmission priority of each user, the time and content of each data update by each user, and the number of dimension types each user is allowed to update and modify; Transmission risk analysis module: Determines the degree of risk of data transmission for each user based on the number of dimensions that different users are allowed to update and modify. Anomaly Analysis Module: This module divides the time periods into sections and determines the degree of data modification anomaly for each user in each time period based on the difference in the number of occurrences of each user's data modification in adjacent time periods and the correlation between elements in adjacent time periods in the data sets of all dimensions. Security sharing module: Based on the degree of data modification anomalies of each user in each time period and the degree of risk of each user's modified data transmission, the modification transmission priority of each user is updated to obtain the modification transmission update priority of each user. Combined with the fire acceptance specifications of each dimension and the difference in the updated modification content of each user's updated data each time, it is determined whether the updated modification content of each user's current updated data is uploaded and shared.

10. A fire protection data security sharing device based on a cloud platform, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the computer program is executed by a processor, the steps of the cloud platform-based fire data security sharing method as described in any one of claims 1 to 8 are implemented.

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