Internet of Things equipment safety management platform
By utilizing the data collection, analysis, and strategy formulation modules of the IoT device security management platform, the shortcomings of existing management platforms are addressed, enabling comprehensive and personalized security management of devices, improving protection accuracy, and reducing costs.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-28
- Publication Date
- 2026-03-13
Smart Images
Figure CN121664490A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of information technology, specifically to a security management platform for Internet of Things (IoT) devices. Background Technology
[0002] In the current field of IoT technology, with the widespread application of IoT devices, the security management of IoT devices has become a critical issue. The rapid increase in the number of IoT devices and their widespread use in different fields and scenarios have significantly increased the security risks of IoT devices. However, existing IoT device security management methods and technologies are often insufficient and cannot meet the needs for comprehensive, efficient and personalized management of IoT devices.
[0003] Existing IoT device security management platforms typically only monitor the basic operating status of devices, lacking in-depth analysis of key device characteristics and potential risk factors. This limits the platform's ability to predict and prevent IoT device security risks. Furthermore, existing management platforms often lack specificity and flexibility in formulating security strategies, failing to develop personalized security strategies based on the actual situation and risk level of the devices. To address these issues, we propose an IoT device security management platform. Summary of the Invention
[0004] To address the aforementioned technical issues and provide an IoT device security management platform, this technical solution resolves the problems described above.
[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:
[0006] The IoT device security management platform includes: a data acquisition module, a data analysis module, a security policy formulation module, and a security execution module;
[0007] The data acquisition module is used to collect status data from IoT devices;
[0008] The data analysis module is used to analyze the collected data and extract key features and potential risk factors;
[0009] The security policy formulation module is used to formulate personalized security policies based on the analysis results;
[0010] The security execution module is used to implement security policies and provide security protection for IoT devices.
[0011] Preferably, the data acquisition module specifically includes:
[0012] Obtain the distribution area of each IoT device within the management area. Let P be the set of areas where IoT devices are located, and construct an electronic map covering the entire area.
[0013] Based on the location of IoT devices within the area, the area P is divided into several sub-areas on an electronic map. Monitoring points are set up within the sub-areas, and sensors are deployed at each monitoring point to ensure that the sensors can cover the key indicators of all IoT devices within the sub-area. The key indicators include: physical status, operating performance, and security protection.
[0014] Sensors should be installed in locations that can accurately capture the status of the equipment, and monitoring nodes should be set at equal intervals to ensure that data is collected evenly throughout the entire cycle.
[0015] A monitoring period is set, during which there are several equally spaced monitoring nodes. At each monitoring node, the status of IoT devices located in each sub-region is monitored, the status data of IoT devices located in the sub-region is collected, and the data is aggregated to build a device status set.
[0016] Preferably, the expression for the set of device states is:
[0017] In the formula, S represents the set of device states, i represents the sub-region, j represents the detection node, k represents the IoT device number, and d represents the operating status data. This represents the operational status data of IoT device k collected at monitoring node j within the operational status data sub-region i. Preferably, the data analysis module specifically includes
[0018] Based on the equipment operation data collected by the data acquisition module, the collected data is preprocessed, including data cleaning, data merging and normalization.
[0019] Feature extraction is performed on the preprocessed data to extract feature data that affects the safe operation of IoT devices. The feature data includes: device characteristics, operating status characteristics, and operating environment characteristics.
[0020] Based on the extracted key features, a risk factor assessment model is established to predict potential risk factors;
[0021] The extracted key features and potential risk factors are output to the security policy formulation module;
[0022] The expression for the risk factor assessment model is as follows:
[0023]
[0024] In the formula, R represents the risk factor assessment value. , , These represent the weighting coefficients for the equipment's inherent characteristics, operating status characteristics, and operating environment characteristics, respectively. This represents the device's own feature vector. Represents the feature vector of the running state. Represents the feature vector of the runtime environment. , , represents the weight coefficients of each specific feature in the equipment's own characteristics, operating status characteristics, and operating environment characteristics, respectively; i, j, and k represent the dimensions of the equipment's own characteristics, operating status characteristics, and operating environment characteristics, respectively; and n, m, and p represent the total number of dimensions of the equipment's own characteristics, operating status characteristics, and operating environment characteristics, respectively.
[0025] Preferably, the security policy formulation module specifically includes:
[0026] The data analysis module receives key features and potential risk factors, determines the risk level based on the risk factor assessment value, and sets different threshold ranges to classify low, medium and high risk levels.
[0027] The characteristics of the equipment itself, its operating status, and its operating environment are analyzed separately, and corresponding safety strategies are formulated for different risk levels and key characteristics.
[0028] Low risk; conduct regular equipment status monitoring and software update reminders; strengthen user safety awareness training; and increase users' awareness of equipment safety.
[0029] For medium-risk situations, in addition to low-risk strategies, increase data encryption strength, optimize network configuration, improve device connection stability, and perform regular security scans on devices to promptly identify potential security issues.
[0030] High risk. Take immediate emergency safety measures, conduct a comprehensive inspection of the equipment's safety settings, carry out in-depth security reinforcement, activate the emergency plan, and notify relevant personnel for emergency handling.
[0031] Regularly evaluate and update security strategies to adapt to the ever-changing security needs and environment of IoT devices.
[0032] Preferably, the risk level calculation formula is as follows:
[0033] Let the risk level be X, the risk factor assessment value be R, and the low-risk threshold be... The high-risk threshold is ;
[0034] when At that time, X = low risk;
[0035] when At that time, X = medium risk;
[0036] when At that time, X = high risk.
[0037] Preferably, the data acquisition module includes:
[0038] The regional division unit is responsible for obtaining the distribution area of each IoT device within the management area.
[0039] The monitoring point setting unit is used to set up monitoring points in the divided sub-areas and deploy sensors in each monitoring point;
[0040] The data collection unit is used to monitor the status of IoT devices located in each sub-area at each monitoring node and collect status data of IoT devices located in each sub-area.
[0041] Preferably, the data analysis module includes:
[0042] The data preprocessing unit is responsible for cleaning, merging, and normalizing the collected data.
[0043] The feature extraction unit is used to extract feature data that affects the safe operation of IoT devices from the preprocessed data.
[0044] The risk assessment unit is used to build a risk factor assessment model based on the extracted key features and predict potential risk factors.
[0045] The results output unit is used to output the extracted key features and potential risk factors to the security policy formulation module, providing a basis for formulating personalized security policies.
[0046] Preferably, the security policy formulation module includes:
[0047] The risk assessment receiving unit is responsible for receiving key features and potential risk factors extracted from the data analysis module, as well as risk factor assessment values.
[0048] The risk level determination unit is used to classify low, medium and high risk levels based on the risk factor assessment value and by using different set threshold ranges.
[0049] The feature analysis unit is used to perform in-depth analysis of the equipment's own features, operating status features, and operating environment features, and to identify the safety issues and risk points in each feature.
[0050] The strategy formulation unit is used to formulate corresponding security strategies for different risk levels and key characteristics.
[0051] Preferably, the secure execution module includes:
[0052] The policy receiving unit is responsible for receiving personalized security policies formulated by the security policy formulation module.
[0053] The policy execution unit is used to execute the personalized security policies formulated by the security policy formulation module.
[0054] Compared with the prior art, the beneficial effects of the present invention are as follows:
[0055] The IoT device security management platform proposed in this invention can comprehensively and accurately collect the status data of IoT devices through a data acquisition module. The data analysis module performs in-depth analysis on this data to extract key features and potential risk factors, providing strong support for subsequent security strategy formulation. Based on the results of the data analysis module, the security strategy formulation module can formulate personalized security strategies for each IoT device based on its specific characteristics and risk factors. This customized strategy formulation method not only improves the accuracy of security protection but also effectively reduces unnecessary security costs, providing a new solution for the security management of IoT devices. Attached Figure Description
[0057] Figure 1 This is a framework diagram of the present invention. Detailed Implementation
[0059] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.
[0060] Reference Figure 1 The IoT device security management platform shown has a highly professional and systematic architecture, including four key modules: data acquisition, data analysis, security policy formulation, and security execution.
[0061] The data acquisition module is responsible for collecting IoT device status data, providing a foundation for subsequent analysis and decision-making. The data analysis module uses advanced algorithms to extract key features and potential risk factors. The security strategy formulation module formulates personalized strategies based on the analysis results, improving the accuracy of security protection and reducing costs. The security execution module implements personalized strategies to ensure the security of the IoT system. In the implementation process, the distribution area of IoT devices within the management area is first obtained to construct an electronic map. Then, sub-areas are divided, monitoring points are set, and sensors are deployed, covering physical status, operational performance, and security protection. Sensors are installed in accurate locations and equidistant monitoring nodes are set. By monitoring the device status and summarizing the data within the monitoring period, a device status set is constructed, providing data resources for subsequent analysis and strategy formulation.
[0062] The expression for the set of device states is:
[0063]
[0064] In the formula, S represents the set of device states, i represents the sub-region, j represents the detection node, k represents the IoT device number, and d represents the operating status data. This represents the operational status data of IoT device k collected at monitoring node j within the operational status data sub-region i.
[0065] The equipment operation data collected by the data acquisition module needs to undergo preprocessing operations including data cleaning, data merging and normalization.
[0066] Data cleaning removes undesirable factors to ensure accuracy and reliability; data merging and integration from different sources ensures consistency and integrity; normalization makes data with different characteristics comparable; feature extraction is performed on the preprocessed data, mainly including device characteristics, operating status characteristics, and operating environment characteristics; a risk factor assessment model is established based on the extracted key features; machine learning algorithms can be used to predict potential risk factors; finally, the key features and potential risk factors are output to the security policy formulation module to formulate personalized security policies to ensure the safe operation of IoT devices.
[0067] The expression for the risk factor assessment model is as follows:
[0068]
[0069] In the formula, R represents the risk factor assessment value. , , These represent the weighting coefficients for the equipment's inherent characteristics, operating status characteristics, and operating environment characteristics, respectively. This represents the device's own feature vector. Represents the feature vector of the running state. Represents the feature vector of the runtime environment. , , represents the weight coefficients of each specific feature in the equipment's own characteristics, operating status characteristics, and operating environment characteristics, respectively; i, j, and k represent the dimensions of the equipment's own characteristics, operating status characteristics, and operating environment characteristics, respectively; and n, m, and p represent the total number of dimensions of the equipment's own characteristics, operating status characteristics, and operating environment characteristics, respectively.
[0070] The data analysis module receives key features and potential risk factors, determines the risk level based on the risk factor assessment value, and sets different threshold ranges to classify low, medium and high risk levels.
[0071] The characteristics of the equipment itself, its operating status, and its operating environment are analyzed separately, and corresponding safety strategies are formulated for different risk levels and key characteristics.
[0072] Low risk; conduct regular equipment status monitoring and software update reminders; strengthen user safety awareness training; and increase users' awareness of equipment safety.
[0073] For medium-risk situations, in addition to low-risk strategies, increase data encryption strength, optimize network configuration, improve device connection stability, and perform regular security scans on devices to promptly identify potential security issues.
[0074] High risk. Take immediate emergency safety measures, conduct a comprehensive inspection of the equipment's safety settings, carry out in-depth security reinforcement, activate the emergency plan, and notify relevant personnel for emergency handling.
[0075] Regularly evaluate and update security strategies to adapt to the ever-changing security needs and environment of IoT devices.
[0076] The formula for calculating risk level is:
[0077] Let the risk level be X, the risk factor assessment value be R, and the low-risk threshold be... The high-risk threshold is ;
[0078] when At that time, X = low risk;
[0079] when At that time, X = medium risk;
[0080] when At that time, X = high risk.
[0081] Reference Figure 1 As shown, the data acquisition module includes:
[0082] The regional division unit is responsible for obtaining the distribution area of each IoT device within the management area.
[0083] The monitoring point setting unit is used to set up monitoring points in the divided sub-areas and deploy sensors in each monitoring point;
[0084] The data collection unit is used to monitor the status of IoT devices located in each sub-area at each monitoring node and collect status data of IoT devices located in each sub-area.
[0085] Reference Figure 1The data analysis module has a clear architecture and plays a crucial role. The data preprocessing unit cleans, merges, and normalizes the collected data to ensure its accuracy, reliability, consistency, completeness, and comparability. The feature extraction unit extracts key feature data affecting the safe operation of IoT devices from the preprocessed data, providing support for subsequent steps. The risk assessment unit builds an assessment model based on the extracted key features to predict potential risk factors. The results output unit outputs the key features and potential risk factors to the security strategy formulation module.
[0086] The security strategy formulation module also plays an important role. The risk assessment receiving unit receives the output results of the data analysis module, the risk level determination unit divides the risk level into low, medium and high risk levels based on the risk factor assessment value, the feature analysis unit deeply analyzes the characteristics of the equipment itself, its operating status and operating environment, and identifies security problems and risk points, and the strategy formulation unit formulates corresponding security strategies for different risk levels and key characteristics.
[0087] The security execution module plays a crucial role. The policy receiving unit receives personalized security policies from the security policy formulation module, and the policy execution unit executes these policies. Through efficient mechanisms and technical means, it ensures the security of IoT devices and transforms security policies into actual actions.
[0088] The process of using this invention is as follows: collect status data of IoT devices, analyze the collected data, extract key features and potential risk factors, formulate personalized security strategies based on the analysis results, implement the security strategies, and provide security protection for IoT devices.
[0089] In summary, the advantages of this invention are as follows: the data acquisition module collects IoT device status data, including key indicators; the data analysis module deeply analyzes the data, extracts key features and potential risk factors, provides support for security strategy formulation, formulates personalized strategies based on the analysis results, improves the accuracy of security protection, reduces security costs, the security execution module implements personalized security strategies to ensure that devices are effectively protected when facing risks, and safeguards the overall security of the system; threshold ranges are set to classify risk levels, and corresponding strategies are formulated for different levels, which facilitates the response of security management personnel; the platform is highly adaptable and can regularly evaluate and update security strategies according to security needs and environmental changes to maintain the best protection effect.
[0090] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.
Claims
1. An IoT device security management platform, characterized in that, include: Data acquisition module, data analysis module, security policy formulation module, and security execution module; The data acquisition module is used to collect status data from IoT devices; The data analysis module is used to analyze the collected data and extract key features and potential risk factors; The security policy formulation module is used to formulate personalized security policies based on the analysis results; The security execution module is used to implement security policies and provide security protection for IoT devices.
2. The IoT device security management platform according to claim 1, characterized in that, The data acquisition module specifically includes: Obtain the distribution area of each IoT device within the management area. Let P be the set of areas where IoT devices are located, and construct an electronic map covering the entire area. Based on the location of IoT devices within the area, the area P is divided into several sub-areas on an electronic map. Monitoring points are set up within the sub-areas, and sensors are deployed at each monitoring point to ensure that the sensors can cover the key indicators of all IoT devices within the sub-area. The key indicators include: physical status, operating performance, and security protection. Sensors should be installed in locations that can accurately capture the status of the equipment, and monitoring nodes should be set at equal intervals to ensure that data is collected evenly throughout the entire cycle. A monitoring period is set, during which there are several equally spaced monitoring nodes. At each monitoring node, the status of IoT devices located in each sub-region is monitored, the status data of IoT devices located in the sub-region is collected, and the data is aggregated to build a device status set.
3. The IoT device security management platform according to claim 2, characterized in that, The expression for the set of device states is: In the formula, S represents the set of device states, i represents the sub-region, j represents the detection node, k represents the IoT device number, and d represents the operating status data. This represents the operational status data of IoT device k collected at monitoring node j within the operational status data sub-region i.
4. The IoT device security management platform according to claim 1, characterized in that, The data analysis module specifically includes: Based on the equipment operation data collected by the data acquisition module, the collected data is preprocessed, including data cleaning, data merging and normalization. Feature extraction is performed on the preprocessed data to extract feature data that affects the safe operation of IoT devices. The feature data includes: device characteristics, operating status characteristics, and operating environment characteristics. Based on the extracted key features, a risk factor assessment model is established to predict potential risk factors; The extracted key features and potential risk factors are output to the security policy formulation module; The expression for the risk factor assessment model is as follows: In the formula, R represents the risk factor assessment value. , , These represent the weighting coefficients for the equipment's inherent characteristics, operating status characteristics, and operating environment characteristics, respectively. This represents the device's own feature vector. Represents the feature vector of the running state. Represents the feature vector of the runtime environment. , , represents the weight coefficients of each specific feature in the equipment's own characteristics, operating status characteristics, and operating environment characteristics, respectively; i, j, and k represent the dimensions of the equipment's own characteristics, operating status characteristics, and operating environment characteristics, respectively; and n, m, and p represent the total number of dimensions of the equipment's own characteristics, operating status characteristics, and operating environment characteristics, respectively.
5. The IoT device security management platform according to claim 1, characterized in that, The security policy formulation module specifically includes: The data analysis module receives key features and potential risk factors, determines the risk level based on the risk factor assessment value, and sets different threshold ranges to classify low, medium and high risk levels. The characteristics of the equipment itself, its operating status, and its operating environment are analyzed separately, and corresponding safety strategies are formulated for different risk levels and key characteristics. Low risk; conduct regular equipment status monitoring and software update reminders; strengthen user safety awareness training; and increase users' awareness of equipment safety. For medium-risk situations, in addition to low-risk strategies, increase data encryption strength, optimize network configuration, improve device connection stability, and perform regular security scans on devices to promptly identify potential security issues. High risk. Take immediate emergency safety measures, conduct a comprehensive inspection of the equipment's safety settings, carry out in-depth security reinforcement, activate the emergency plan, and notify relevant personnel for emergency handling. Regularly evaluate and update security strategies to adapt to the ever-changing security needs and environment of IoT devices.
6. The IoT device security management platform according to claim 5, characterized in that, The formula for calculating risk level is: Let the risk level be X, the risk factor assessment value be R, and the low-risk threshold be... The high-risk threshold is ; when At that time, X = low risk; when At that time, X = medium risk; when At that time, X = high risk.
7. The IoT device security management platform according to claim 1, characterized in that, The data acquisition module includes: The regional division unit is responsible for obtaining the distribution area of each IoT device within the management area. The monitoring point setting unit is used to set up monitoring points in the divided sub-areas and deploy sensors in each monitoring point; The data collection unit is used to monitor the status of IoT devices located in each sub-area at each monitoring node and collect status data of IoT devices located in each sub-area.
8. The IoT device security management platform according to claim 1, characterized in that, The data analysis module includes: The data preprocessing unit is responsible for cleaning, merging, and normalizing the collected data. The feature extraction unit is used to extract feature data that affects the safe operation of IoT devices from the preprocessed data. The risk assessment unit is used to build a risk factor assessment model based on the extracted key features and predict potential risk factors. The results output unit is used to output the extracted key features and potential risk factors to the security policy formulation module, providing a basis for formulating personalized security policies.
9. The IoT device security management platform according to claim 1, characterized in that, The security policy formulation module includes: The risk assessment receiving unit is responsible for receiving key features and potential risk factors extracted from the data analysis module, as well as risk factor assessment values. The risk level determination unit is used to classify low, medium and high risk levels based on the risk factor assessment value and by using different set threshold ranges. The feature analysis unit is used to perform in-depth analysis of the equipment's own features, operating status features, and operating environment features, and to identify the safety issues and risk points in each feature. The strategy formulation unit is used to formulate corresponding security strategies for different risk levels and key characteristics.
10. The IoT device security management platform according to claim 1, characterized in that, The secure execution module includes: The policy receiving unit is responsible for receiving personalized security policies formulated by the security policy formulation module. The policy execution unit is used to execute the personalized security policies formulated by the security policy formulation module.