Big data analysis method and system based on heterogeneous monitoring security information

Abstract

The invention discloses a big data analysis method and system based on heterogeneous monitoring security and protection information, and relates to the technical field of security and protection monitoring, and the method comprises the steps: accessing multi-source heterogeneous security and protection data of a plurality of security and protection subsystems in a target security and protection region based on a unified data interface; performing standardization processing on the multi-source heterogeneous security and protection data to obtain preprocessed multi-source heterogeneous security and protection data; when the abnormal event is identified, performing cross verification on the abnormal event based on the preprocessed multi-source heterogeneous security data, and determining space coordinate information of the abnormal event; and based on the space coordinate information of the abnormal event, marking an alarm position of the abnormal event in the three-dimensional model of the target security and protection area, and performing visual display. According to the invention, the technical problem that false alarm data is easy to occur in abnormal alarm identification in the prior art is relieved.

Description

Technical Field

[0001] This invention relates to the field of security monitoring technology, specifically to a big data analysis method and system based on heterogeneous security monitoring information. Background Technology

[0002] The existing security monitoring system has the following limitations in anomaly alarm identification: alarms mainly rely on thresholds set by the device terminal, there are some false alarms, and there is a lack of dynamic anomaly pattern recognition based on big data (learning normal patterns from historical data to identify non-threshold anomalies). Summary of the Invention

[0003] The purpose of this invention is to provide a big data analysis method and system based on heterogeneous monitoring and security information in order to solve at least one of the above-mentioned technical problems.

[0004] In a first aspect, embodiments of the present invention provide a big data analysis method based on heterogeneous monitoring and security information, comprising: accessing multi-source heterogeneous security data from multiple security subsystems within a target security area via a unified data interface; standardizing the multi-source heterogeneous security data to obtain pre-processed multi-source heterogeneous security data; upon identifying an abnormal event, cross-validating the abnormal event based on the pre-processed multi-source heterogeneous security data and determining the spatial coordinate information of the abnormal event; and marking the alarm location of the abnormal event on a three-dimensional model of the target security area based on the spatial coordinate information of the abnormal event and displaying it visually.

[0005] Optionally, the multi-source heterogeneous security data includes video data, access control data, and intrusion alarm data.

[0006] Optionally, the visualization includes: in the 3D model, visualizing the alarm location of the abnormal event by highlighting it and displaying associated data of the abnormal event.

[0007] Secondly, embodiments of the present invention also provide a big data analysis system based on heterogeneous monitoring and security information, used to implement the big data analysis method based on heterogeneous monitoring and security information provided in the embodiments of the present invention; the system includes: a data access module, a preprocessing module, a verification module, and a display module; wherein, the data access module is used to access multi-source heterogeneous security data from multiple security subsystems within a target security area based on a unified data interface; the preprocessing module is used to standardize the multi-source heterogeneous security data to obtain preprocessed multi-source heterogeneous security data; the verification module is used to cross-verify the abnormal event based on the preprocessed multi-source heterogeneous security data when an abnormal event is identified, and to determine the spatial coordinate information of the abnormal event; the display module is used to mark the alarm position of the abnormal event on a three-dimensional model of the target security area based on the spatial coordinate information of the abnormal event, and to perform a visual display.

[0008] Optionally, the display module is further configured to: visualize the abnormal event in the 3D model by highlighting the alarm location of the abnormal event and displaying associated data of the abnormal event.

[0009] Thirdly, embodiments of the present invention also provide an electronic device, including: a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the method provided in the embodiments of the present invention.

[0010] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the method provided in the embodiments of the present invention.

[0011] This invention provides a big data analysis method and system based on heterogeneous monitoring and security information. It adopts unified access and conversion rules for heterogeneous data from different subsystems, and solves the analysis barriers caused by differences in data formats between different security subsystems through standardized processing. It identifies anomalies based on a big data dynamic model, breaks through fixed threshold limitations, and reduces missed and false alarms. It optimizes alarm location accuracy and efficiency, enhances alarm tracing capabilities, and alleviates the technical problem of false alarms in existing technologies. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0013] Figure 1 A flowchart illustrating a big data analysis method based on heterogeneous monitoring and security information provided in this embodiment of the invention; Figure 2 This is a schematic diagram of a big data analysis system based on heterogeneous monitoring and security information provided in an embodiment of the present invention. Detailed Implementation

[0014] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0015] Example 1 Figure 1 This is a flowchart illustrating a big data analysis method based on heterogeneous monitoring and security information according to an embodiment of the present invention. Figure 1 As shown, the method specifically includes the following steps: Step S102: Based on a unified data interface, access multi-source heterogeneous security data from multiple security subsystems within the target security area.

[0016] Step S104: Standardize the multi-source heterogeneous security data to obtain pre-processed multi-source heterogeneous security data.

[0017] Optionally, the multi-source heterogeneous security data includes video data, access control data, and intrusion alarm data. Examples include unstructured video streams, structured personnel data, and semi-structured alarm logs. This invention solves the analysis obstacles caused by data format differences in existing technologies by setting a unified data interface and standardized processing or conversion rules, such as unifying the field formats of video streams and alarm data.

[0018] Step S106: When an abnormal event is identified, the abnormal event is cross-validated based on the preprocessed multi-source heterogeneous security data, and the spatial coordinate information of the abnormal event is determined.

[0019] For example, cross-validation of abnormal events includes cross-validation between video footage of abnormal personnel, access control records, and the status of surrounding intrusion alarm devices.

[0020] Step S108: Based on the spatial coordinate information of the abnormal event, mark the alarm location of the abnormal event on the three-dimensional model of the target security area and display it visually.

[0021] Specifically, the present invention improves the positioning accuracy from the regional level to the specific device or point level by marking the alarm location in a three-dimensional model.

[0022] Preferably, the method provided in this embodiment of the invention, after marking the alarm location on the three-dimensional model, also links relevant data (such as real-time video) for auxiliary confirmation, so as to solve the problem of insufficient positioning accuracy in the prior art.

[0023] Specifically, in step S108, visualization is performed, including: in the 3D model, the alarm location of the abnormal event is highlighted and the associated data of the abnormal event is displayed for visualization.

[0024] The big data analysis method based on heterogeneous monitoring and security information provided in this invention has the following technical advantages compared with the prior art: (1) Improve the efficiency of heterogeneous data processing: By standardizing processing rules, solve the analysis barriers caused by the differences in data formats of different security subsystems, and realize that the data is "analyzable" rather than just "displayable".

[0025] (2) Improve the accuracy of anomaly alarms: Based on big data dynamic model to identify anomalies, break through the fixed threshold limit and reduce missed alarms (non-threshold anomalies) and false alarms (single data anomalies caused by environmental interference).

[0026] (3) Optimize alarm positioning accuracy and efficiency: Multi-source data cross-validation combined with spatial information improves positioning accuracy from "regional level" to "point level", and linked data assists in rapid confirmation.

[0027] (4) Enhance alarm tracing capabilities: Support historical data backtracking based on abnormal patterns to provide data support for security decision-making.

[0028] Example 2 Figure 2 This is a schematic diagram of a big data analysis system based on heterogeneous monitoring and security information according to an embodiment of the present invention. Figure 2 As shown, the system includes: a data access module 10, a preprocessing module 20, a verification module 30, and a display module 40.

[0029] Specifically, the data access module 10 is used to access multi-source heterogeneous security data from multiple security subsystems within the target security area based on a unified data interface; Preprocessing module 20 is used to standardize multi-source heterogeneous security data to obtain preprocessed multi-source heterogeneous security data; The verification module 30 is used to cross-verify the abnormal event based on the preprocessed multi-source heterogeneous security data when an abnormal event is detected, and to determine the spatial coordinate information of the abnormal event. The display module 40 is used to mark the alarm location of the abnormal event on the 3D model of the target security area based on the spatial coordinate information of the abnormal event, and to display it visually.

[0030] Specifically, the display module 40 is also used to: visualize the abnormal event in the 3D model by highlighting the alarm location of the abnormal event and displaying the associated data of the abnormal event.

[0031] The present invention also provides an electronic device, including: a memory, a processor, and a computer program stored on the memory and running on the processor, wherein the processor executes the computer program to implement the method provided in the embodiments of the present invention.

[0032] The present invention also provides a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the method provided in the embodiments of the present invention.

[0033] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0034] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A big data analysis method based on heterogeneous monitoring security information, characterized in that, The method comprises the following steps: Accessing multi-source heterogeneous security data of multiple security subsystems in a target security area based on a unified data interface; Standardizing the multi-source heterogeneous security data to obtain preprocessed multi-source heterogeneous security data; When an abnormal event is identified, cross-verifying the abnormal event based on the preprocessed multi-source heterogeneous security data and determining spatial coordinate information of the abnormal event; Based on the spatial coordinate information of the abnormal event, marking an alarm position of the abnormal event on a three-dimensional model of the target security area and performing visual display.

2. The method of claim 1, wherein: The multi-source heterogeneous security data comprises video data, access control data and intrusion alarm data.

3. The method of claim 1, wherein: The visual display comprises highlighting the alarm position of the abnormal event in the three-dimensional model and performing visual display of associated data of the abnormal event.

4. A big data analysis system based on heterogeneous monitoring security information, characterized in that, The system for implementing the method for analyzing big data based on heterogeneous monitoring security information according to any one of claims 1-3 comprises a data access module, a preprocessing module, a verification module and a display module, wherein: The data access module is configured to access multi-source heterogeneous security data of multiple security subsystems in a target security area based on a unified data interface; The preprocessing module is configured to standardize the multi-source heterogeneous security data to obtain preprocessed multi-source heterogeneous security data; The verification module is configured to, when an abnormal event is identified, cross-verify the abnormal event based on the preprocessed multi-source heterogeneous security data and determine spatial coordinate information of the abnormal event; The display module is configured to, based on the spatial coordinate information of the abnormal event, mark an alarm position of the abnormal event on a three-dimensional model of the target security area and perform visual display.

5. The system of claim 4, wherein: The display module is further configured to highlight the alarm position of the abnormal event in the three-dimensional model and perform visual display of associated data of the abnormal event.

6. An electronic device, comprising: The method comprises the following steps: A memory, a processor and a computer program stored in the memory and running on the processor, wherein the processor implements the method according to any one of claims 1-3 when executing the computer program.

7. A computer readable storage medium characterized in that, The computer readable storage medium stores computer instructions, and the computer instructions are executed by the processor to implement the method according to any one of claims 1-3.

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