CN111538501B - Artificial intelligence-based multivariate heterogeneous network data visualization method and system - Google Patents
Artificial intelligence-based multivariate heterogeneous network data visualization method and system Download PDFInfo
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Abstract
The invention provides a multivariate heterogeneous network data visualization method and a multivariate heterogeneous network data visualization system based on artificial intelligence, wherein the method comprises the following steps: step S1: constructing a three-dimensional multi-element heterogeneous network topological graph; step S2: acquiring multi-element heterogeneous network data; step S3: analyzing the multi-element heterogeneous network data, and determining first visual data and data content; step S4: inputting the data content into a pre-stored neural network model to obtain second visual data; step S5: and labeling in the three-dimensional multi-element heterogeneous network topological graph based on the first visual data and the second visual data. The multivariate heterogeneous network data visualization method based on artificial intelligence realizes that a user can visually observe the data flow direction between heterogeneous data sources, the data type representing data characterization information and the data risk.
Description
Technical Field
The invention relates to the technical field of network data visualization, in particular to a multivariate heterogeneous network data visualization method based on artificial intelligence.
Background
At present, in the process of enterprise information construction, due to the influence of factors such as the stage, the technology, other economic factors, human factors and the like of each business system construction and implementation of a data management system, a large amount of business data adopting different storage modes are accumulated in the development process of an enterprise, the adopted data management systems are quite different, and the business data form a heterogeneous data source of the enterprise from a simple file database to a complex network database;
how to observe data flow direction and data representation information among heterogeneous data sources in a straight pipe is a problem which needs to be solved urgently.
Disclosure of Invention
One of the purposes of the invention is to provide an artificial intelligence-based multivariate heterogeneous network data visualization method, so that a user can visually observe data flow direction between heterogeneous data sources, data types representing data characterization information and data risk.
The embodiment of the invention provides a multivariate heterogeneous network data visualization method based on artificial intelligence, which comprises the following steps: step S1: constructing a three-dimensional multi-element heterogeneous network topological graph;
step S2: acquiring multi-element heterogeneous network data;
step S3: analyzing the multi-element heterogeneous network data, and determining first visual data and data content;
step S4: inputting the data content into a pre-stored neural network model to obtain second visual data;
step S5: and labeling in the three-dimensional multi-element heterogeneous network topological graph based on the first visual data and the second visual data.
Preferably, the first visualization data comprises: one or more combinations of a sending address, a target address, a data type and data content;
the second visualization data includes: one or more combinations of data name and data risk;
step S1: the method for constructing the three-dimensional multi-element heterogeneous network topological graph specifically comprises the following steps:
step S11: acquiring position information and connection relation of each device accessed to the three-dimensional multi-element heterogeneous network;
step S12: establishing a three-dimensional coordinate system by taking any equipment as an origin;
step S13: mapping each device to a three-dimensional coordinate system based on the position information and the connection relation;
step S14: marking the equipment by using a preset virtual icon at the position where the equipment is mapped to the three-dimensional coordinate system; presetting a virtual icon corresponding to the type of the equipment;
step S15: and adjusting the size of the virtual icon according to the ratio of the parameters of the equipment to the standard parameters.
Preferably, step S5: labeling in the three-dimensional multi-element heterogeneous network topological graph based on the first visual data and the second visual data, specifically comprising:
step S51: taking the position of the equipment corresponding to the sending address in the three-dimensional coordinate system as a starting point; taking the position of equipment corresponding to a target address in a three-dimensional coordinate system as an end point, and adopting a plurality of dynamically flowing line segments between the start point and the end point to represent the flow direction of the multi-element heterogeneous network data;
step S52: acquiring the data transmission speed of the multi-element heterogeneous network data, and adjusting the flow speed of the line segment according to the data transmission speed;
step S53: analyzing the first visual data and the second visual data to obtain the data type, the data name and the data risk; step S54: adjusting the color of the line segment according to the data type;
step S55: arranging a suspension frame beside the line segment, and displaying the data name in the suspension frame;
step S56: and arranging a virtual slideway on the outer side of the line segment, and setting the color of the virtual slideway according to the data risk.
Preferably, the artificial intelligence based visualization method for the data of the multivariate heterogeneous network further comprises:
step S6: acquiring a coordinate area of a display window in a three-dimensional coordinate system;
step S7: mapping a three-dimensional multi-element heterogeneous network topological graph in a view of a display window to the display window for display;
step S8: receiving an operation instruction of a user for the display window, wherein the operation instruction comprises moving or zooming;
step S9: based on the operation instruction, re-determining the coordinate area of the display window in the three-dimensional coordinate system, and re-mapping the three-dimensional multivariate heterogeneous network topological graph in the view field of the display window to the display window for display;
wherein, step S7: mapping a three-dimensional multi-element heterogeneous network topological graph in a view field of a display window to the display window for displaying, which specifically comprises the following steps:
step S71: acquiring the position relation between the left eye and the right eye of a user and a display screen corresponding to a display window;
step S72: determining a first viewpoint and a second viewpoint which correspond to the left eye and the right eye of the user in the three-dimensional coordinate system respectively based on the position relation and the coordinate area;
step S73: determining a first view boundary of the display window by using the first view point and the edge of the coordinate area;
step S74: taking the position of a connecting line of a first viewpoint and the position of equipment corresponding to the three-dimensional multi-element heterogeneous network topological graph positioned in the first view boundary, which passes through the coordinate area, as the mapping position of the equipment on the display window; forming a first mapping image;
step S75: determining a second view boundary of the display window by using the second view point and the edge of the coordinate area;
step S76: taking the position of a connecting line of the second viewpoint and the position of the corresponding equipment of the three-dimensional multi-element heterogeneous network topological graph positioned in the second view boundary passing through the coordinate area as the mapping position of the equipment on the display window; a second mapping image is formed.
Step S77: and displaying the first mapping image and the second mapping image on the display screen in an interleaving manner.
Preferably, step S74: taking the position of a connecting line of a first viewpoint and the position of equipment corresponding to the three-dimensional multi-element heterogeneous network topological graph positioned in the first view boundary, which passes through the coordinate area, as the mapping position of the equipment on the display window; forming a first mapping image; the method specifically comprises the following steps:
determining the size of the mapping icon corresponding to the preset icon on the display window based on the size of the preset icon of the equipment, the distance between the position corresponding to the equipment and the mapping position and the distance between the mapping position and the first viewpoint, wherein the specific calculation formula is as follows:
wherein the content of the first and second substances,
representing the size of the mapping icon;
representing the size of a preset icon;
representing a distance of the mapped location to the first viewpoint;
representing a distance of the location of the corresponding device from the mapped location;
when the size of the mapping icon is smaller than a preset threshold value, replacing the mapping icon with a preset mark in the first mapping image;
determining the width of the display window mapped by the starting point end of the line segment based on the size of the preset icon of the device corresponding to the starting point of the line segment, the distance between the position of the corresponding device and the mapping position, and the distance from the mapping position to the first viewpoint
The specific calculation formula is as follows:
wherein the content of the first and second substances,
is a preset standard icon size and is,
is a preset standard width.
The invention also provides a multivariate heterogeneous network data visualization system based on artificial intelligence, which comprises the following components: the three-dimensional construction module is used for constructing a three-dimensional multi-element heterogeneous network topological graph;
the data acquisition module is used for acquiring the multi-element heterogeneous network data;
the first visual data determining module is used for analyzing the multi-element heterogeneous network data and determining first visual data and data content;
the second visual data determining module is used for inputting data contents into a pre-stored neural network model to obtain second visual data;
and the labeling module is used for labeling the three-dimensional multi-element heterogeneous network topological graph based on the first visual data and the second visual data.
Preferably, the first visualization data comprises: one or more combinations of a sending address, a target address, a data type and data content;
the second visualization data includes: one or more combinations of data name and data risk;
the three-dimensional building block comprises:
the parameter acquisition module is used for acquiring the position information and the connection relation of each device accessed to the three-dimensional multi-element heterogeneous network;
the three-dimensional coordinate system establishing module is used for establishing a three-dimensional coordinate system by taking any equipment as an origin;
the first mapping module is used for mapping each device to a three-dimensional coordinate system based on the position information and the connection relation;
the icon determining module is used for marking the equipment by using a preset virtual icon at the position where the equipment is mapped to the three-dimensional coordinate system; presetting a virtual icon corresponding to the type of the equipment;
and the icon adjusting module is used for adjusting the size of the integer preset virtual icon according to the ratio of the parameter of the equipment to the standard parameter.
Preferably, the marking module performs the following operations:
taking the position of the equipment corresponding to the sending address in the three-dimensional coordinate system as a starting point; taking the position of equipment corresponding to a target address in a three-dimensional coordinate system as an end point, and adopting a plurality of dynamically flowing line segments between the start point and the end point to represent the flow direction of the multi-element heterogeneous network data;
acquiring the data transmission speed of the multi-element heterogeneous network data, and adjusting the flow speed of the line segment according to the data transmission speed;
analyzing the first visual data and the second visual data to obtain the data type, the data name and the data risk; adjusting the color of the line segment according to the data type;
arranging a suspension frame beside the line segment, and displaying the data name in the suspension frame;
and arranging a virtual slideway on the outer side of the line segment, and setting the color of the virtual slideway according to the data risk.
Preferably, the artificial intelligence based multiple heterogeneous network data visualization system further comprises:
the display window positioning module is used for acquiring a coordinate area of the display window in a three-dimensional coordinate system;
the second mapping module is used for mapping the three-dimensional multi-element heterogeneous network topological graph in the view field of the display window to the display window for displaying;
the instruction receiving module is used for receiving an operation instruction of a user for the display window, wherein the operation instruction comprises moving or zooming;
the display window adjusting module is used for re-determining the coordinate area of the display window in the three-dimensional coordinate system based on the operation instruction, and re-mapping the three-dimensional multi-element heterogeneous network topological graph in the view field of the display window to the display window for display;
wherein the second mapping module performs operations comprising:
acquiring the position relation between the left eye and the right eye of a user and a display screen corresponding to a display window;
determining a first viewpoint and a second viewpoint which correspond to the left eye and the right eye of the user in the three-dimensional coordinate system respectively based on the position relation and the coordinate area of the display window in the three-dimensional coordinate system;
determining a first view boundary of the display window by using the first view point and the edge of the coordinate area;
taking the position of a connecting line of a first viewpoint and the position of equipment corresponding to the three-dimensional multi-element heterogeneous network topological graph positioned in the first view boundary, which passes through the coordinate area, as the mapping position of the equipment on the display window; forming a first mapping image;
determining a second view boundary of the display window by using the second view point and the edge of the coordinate area;
taking the position of a connecting line of the second viewpoint and the position of the corresponding equipment of the three-dimensional multi-element heterogeneous network topological graph positioned in the second view boundary passing through the coordinate area as the mapping position of the equipment on the display window; a second mapping image is formed.
And displaying the first mapping image and the second mapping image on the display screen in an interleaving manner.
Preferably, a connection line between the first viewpoint and a position of equipment corresponding to the three-dimensional multi-element heterogeneous network topological graph located in the view boundary passes through the position of the coordinate region to serve as a mapping position of the equipment on the display window; forming a first mapping image; the method specifically comprises the following steps:
determining the size of the mapping icon corresponding to the preset icon on the display window based on the size of the preset icon of the equipment, the distance between the position corresponding to the equipment and the mapping position and the distance between the mapping position and the first viewpoint, wherein the specific calculation formula is as follows:
wherein the content of the first and second substances,
representing the size of the mapping icon;
representing the size of a preset icon;
representing a distance of the mapped location to the first viewpoint;
representing a distance of the location of the corresponding device from the mapped location;
when the size of the mapping icon is smaller than a preset threshold value, replacing the mapping icon with a preset mark in the first mapping image;
determining the width of the display window mapped by the starting point end of the line segment based on the size of the preset icon of the device corresponding to the starting point of the line segment, the distance between the position of the corresponding device and the mapping position, and the distance from the mapping position to the first viewpoint
The specific calculation formula is as follows:
wherein the content of the first and second substances,
is a preset standard icon size and is,
is a preset standard width.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic diagram of a multivariate heterogeneous network data visualization method based on artificial intelligence in an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
The embodiment of the invention provides a multivariate heterogeneous network data visualization method based on artificial intelligence, which comprises the following steps of: step S1: constructing a three-dimensional multi-element heterogeneous network topological graph;
step S2: acquiring multi-element heterogeneous network data;
step S3: analyzing the multi-element heterogeneous network data, and determining first visual data and data content;
step S4: inputting the data content into a pre-stored neural network model to obtain second visual data;
step S5: and labeling in the three-dimensional multi-element heterogeneous network topological graph based on the first visual data and the second visual data.
The working principle and the beneficial effects of the technical scheme are as follows:
in order to realize data monitoring of heterogeneous data sources of a multi-element heterogeneous network formed by enterprises; firstly, constructing a three-dimensional multi-element heterogeneous network topological graph, and finding out the spatial position relation among various heterogeneous data sources (equipment) from the three-dimensional topological graph; then acquiring multi-element heterogeneous network data in real time; analyzing the obtained multi-element heterogeneous network data for the first time, and separating first visual data from data content, wherein the first visual data mainly comprises a sending address, a target address and the like which are obtained according to sending address data and target address data which are added for data transmission; bringing the separated data content into a pre-stored neural network model for system discrimination and determining the threat of the data content to obtain second visual data; marking the first visual data and the second visual data in a three-dimensional multi-element heterogeneous network topological graph, and enabling a user to visually observe data flow direction between heterogeneous data sources, data types representing data representation information and data risk through the marked three-dimensional multi-element heterogeneous network topological graph; factors involved in the risk of data include: data assets, data threats, and data vulnerabilities. The pre-stored neural network model can be obtained by adopting historical data content through reinforcement learning training, or can be a trained neural network model stored in a server.
In one embodiment, the first visualization data comprises: one or more combinations of a sending address, a target address, a data type and data content;
the second visualization data includes: one or more combinations of data name and data risk;
step S1: the method for constructing the three-dimensional multi-element heterogeneous network topological graph specifically comprises the following steps:
step S11: acquiring position information and connection relation of each device accessed to the three-dimensional multi-element heterogeneous network;
step S12: establishing a three-dimensional coordinate system by taking any equipment as an origin;
step S13: mapping each device to a three-dimensional coordinate system based on the position information and the connection relation;
step S14: marking the equipment by using a preset virtual icon at the position where the equipment is mapped to the three-dimensional coordinate system; presetting a virtual icon corresponding to the type of the equipment;
step S15: and adjusting the size of the virtual icon according to the ratio of the parameters of the equipment to the standard parameters.
The working principle and the beneficial effects of the technical scheme are as follows:
drawing a topological graph according to the position information of the representative space position of each device and the connection relation, so that a user can visually see the position of each device on the three-dimensional topological graph; the virtual icon corresponding to the type of the equipment realizes that a user can intuitively determine the type of the equipment from the virtual icon; and the parameter difference between the device and other devices of the same type is visually compared through the size of the preset icon. The data name corresponding to the data content can be determined based on the data name corresponding to the characteristic value in the database by extracting the characteristic value and comparing the characteristic value with the characteristic value stored in the database; for example: the data names include: the data of personnel's card punching, the business turn over account data of financial affairs, the monitoring data of the equipment in workshop etc.. The data types include: character data, array data, etc.
In one embodiment, step S5: labeling in the three-dimensional multi-element heterogeneous network topological graph based on the first visual data and the second visual data, specifically comprising:
step S51: taking the position of the equipment corresponding to the sending address in the three-dimensional coordinate system as a starting point; taking the position of equipment corresponding to a target address in a three-dimensional coordinate system as an end point, and adopting a plurality of dynamically flowing line segments between the start point and the end point to represent the flow direction of the multi-element heterogeneous network data;
step S52: acquiring the data transmission speed of the multi-element heterogeneous network data, and adjusting the flow speed of the line segment according to the data transmission speed;
step S53: analyzing the first visual data and the second visual data to obtain the data type, the data name and the data risk; step S54: adjusting the color of the line segment according to the data type;
step S55: arranging a suspension frame beside the line segment, and displaying the data name in the suspension frame;
step S56: and arranging a virtual slideway on the outer side of the line segment, and setting the color of the virtual slideway according to the data risk.
The working principle and the beneficial effects of the technical scheme are as follows:
by adopting the dynamically flowing line segment, a user can intuitively obtain data from which device to which device when viewing; by observing the flowing speed of the line segment, the speed of data transmission can be visually observed; the type of the data can be seen according to the color emission of the line segment, and the name of the data can be seen in the suspension frame. The risk of the data can be seen from the color emission of the outer-layer wrapped slideway; and further, the user can visually see the data flow direction, the data transmission speed, the data type, the data name and the data risk.
In one embodiment, the artificial intelligence based multivariate heterogeneous network data visualization method further comprises:
step S6: acquiring a coordinate area of a display window in a three-dimensional coordinate system;
step S7: mapping a three-dimensional multi-element heterogeneous network topological graph in a view of a display window to the display window for display;
step S8: receiving an operation instruction of a user for the display window, wherein the operation instruction comprises moving or zooming;
step S9: based on the operation instruction, re-determining the coordinate area of the display window in the three-dimensional coordinate system, and re-mapping the three-dimensional multivariate heterogeneous network topological graph in the view field of the display window to the display window for display;
wherein, step S7: mapping a three-dimensional multi-element heterogeneous network topological graph in a view field of a display window to the display window for displaying, which specifically comprises the following steps:
step S71: acquiring the position relation between the left eye and the right eye of a user and a display screen corresponding to a display window;
step S72: determining a first viewpoint and a second viewpoint which correspond to the left eye and the right eye of the user in the three-dimensional coordinate system respectively based on the position relation and the coordinate area of the display window in the three-dimensional coordinate system;
step S73: determining the view boundary of the display window by the first view and the edge of the coordinate area;
step S74: taking the position of a connecting line of a first viewpoint and the position of equipment corresponding to the three-dimensional multi-element heterogeneous network topological graph positioned in the view boundary, which passes through the coordinate area, as the mapping position of the equipment on the display window; forming a first mapping image;
step S75: determining the view boundary of the display window by the second view and the edge of the coordinate area;
step S76: taking the position of a connecting line of the second viewpoint and the position of the corresponding equipment of the three-dimensional multi-element heterogeneous network topological graph positioned in the view boundary passing through the coordinate area as the mapping position of the equipment on the display window; forming a second mapping image;
step S77: and displaying the first mapping image and the second mapping image on the display screen in an interleaving manner.
The working principle and the beneficial effects of the technical scheme are as follows:
through the difference that the left eye and the right eye of people's eye received, first mapping image adopts first display light show, and second mapping image adopts the second display light show, receives the back respectively via left eye and right eye, realizes bore hole 3D effect to improve user's visual experience. Wherein the first mapping image and the second mapping image are displayed on the display screen in an interlaced manner; the other mode is that the adjacent two frames respectively display the first mapping image and the second mapping image. Further, AR glasses may be employed, and the display screen for the left eye position displays the first mapping image and the display screen for the right eye position displays the second mapping image.
In one embodiment, step S74, the position of the device on the display window is taken as the position of the connection line of the first viewpoint and the position of the corresponding device of the three-dimensional multi-element heterogeneous network topological graph positioned in the view boundary, which passes through the coordinate area; forming a first mapping image; the method specifically comprises the following steps:
determining the size of the mapping icon corresponding to the preset icon on the display window based on the size of the preset icon of the equipment, the distance between the position corresponding to the equipment and the mapping position and the distance between the mapping position and the first viewpoint, wherein the specific calculation formula is as follows:
wherein the content of the first and second substances,
representing the size of the mapping icon;
representing the size of a preset icon;
representing a distance of the mapped location to the first viewpoint;
representing a distance of the location of the corresponding device from the mapped location;
when the size of the mapping icon is smaller than a preset threshold value, replacing the mapping icon with a preset mark in the first mapping image;
determining the width of the display window mapped by the starting point end of the line segment based on the size of the preset icon of the device corresponding to the starting point of the line segment, the distance between the position of the corresponding device and the mapping position, and the distance from the mapping position to the first viewpoint
The specific calculation formula is as follows:
wherein the content of the first and second substances,
is a preset standard icon size and is,
is a preset standard width.
The working principle and the beneficial effects of the technical scheme are as follows:
when the three-dimensional multi-element heterogeneous topological graph is projected to a display window, the size of a mapping icon corresponding to a preset icon on the display window is determined based on the size of the preset icon of equipment, the distance between the position corresponding to the equipment and the mapping position and the distance between the mapping position and a first viewpoint; the spatial layering is ensured. Similarly, the width of the line segment starting point end mapped to the display window is determined based on the size of the preset icon of the equipment corresponding to the line segment starting point, the distance between the position of the corresponding equipment and the mapping position and the distance from the mapping position to the first viewpoint, and the spatial layering after the line segment is projected is ensured. Similarly, the second mapping image is also subjected to such processing during the projection process.
The invention also provides a multivariate heterogeneous network data visualization system based on artificial intelligence, which comprises the following components: the three-dimensional construction module is used for constructing a three-dimensional multi-element heterogeneous network topological graph;
the data acquisition module is used for acquiring the multi-element heterogeneous network data;
the first visual data determining module is used for analyzing the multi-element heterogeneous network data and determining first visual data and data content;
the second visual data determining module is used for inputting data contents into a pre-stored neural network model to obtain second visual data;
and the labeling module is used for labeling the three-dimensional multi-element heterogeneous network topological graph based on the first visual data and the second visual data.
The working principle and the beneficial effects of the technical scheme are as follows:
in order to realize data monitoring of heterogeneous data sources of a multi-element heterogeneous network formed by enterprises; firstly, constructing a three-dimensional multi-element heterogeneous network topological graph, and finding out the spatial position relation among various heterogeneous data sources (equipment) from the three-dimensional topological graph; then acquiring multi-element heterogeneous network data in real time; analyzing the obtained multi-element heterogeneous network data for the first time, and separating first visual data from data content, wherein the first visual data mainly comprises a sending address, a target address and the like which are obtained according to sending address data and target address data which are added for data transmission; bringing the separated data content into a pre-stored neural network model for system discrimination and determining the threat of the data content to obtain second visual data; the first visual data and the second visual data are marked in the three-dimensional multi-element heterogeneous network topological graph, and a user can visually observe the data flow direction between heterogeneous data sources, the data type representing data representation information and the data risk through the marked three-dimensional multi-element heterogeneous network topological graph.
In one embodiment, the first visualization data comprises: one or more combinations of a sending address, a target address, a data type and data content;
the second visualization data includes: one or more combinations of data name and data risk;
the three-dimensional building block comprises:
the parameter acquisition module is used for acquiring the position information and the connection relation of each device accessed to the three-dimensional multi-element heterogeneous network;
the three-dimensional coordinate system establishing module is used for establishing a three-dimensional coordinate system by taking any equipment as an origin;
the first mapping module is used for mapping each device to a three-dimensional coordinate system based on the position information and the connection relation;
the icon determining module is used for marking the equipment by using a preset virtual icon at the position where the equipment is mapped to the three-dimensional coordinate system; presetting a virtual icon corresponding to the type of the equipment;
and the icon adjusting module is used for adjusting the size of the integer in the preset virtual icon according to the ratio of the parameter of the equipment to the standard parameter.
The working principle and the beneficial effects of the technical scheme are as follows:
drawing a topological graph according to the position information of the representative space position of each device and the connection relation, so that a user can visually see the position of each device on the three-dimensional topological graph; the virtual icon corresponding to the type of the equipment realizes that a user can intuitively determine the type of the equipment from the virtual icon; and the parameter difference between the device and other devices of the same type is visually compared through the size of the preset icon.
In one embodiment, the annotating module performs operations comprising:
taking the position of the equipment corresponding to the sending address in the three-dimensional coordinate system as a starting point; taking the position of equipment corresponding to a target address in a three-dimensional coordinate system as an end point, and adopting a plurality of dynamically flowing line segments between the start point and the end point to represent the flow direction of the multi-element heterogeneous network data;
acquiring the data transmission speed of the multi-element heterogeneous network data, and adjusting the flow speed of the line segment according to the data transmission speed;
analyzing the first visual data and the second visual data to obtain the data type, the data name and the data risk; adjusting the color of the line segment according to the data type;
arranging a suspension frame beside the line segment, and displaying the data name in the suspension frame;
and arranging a virtual slideway on the outer side of the line segment, and setting the color of the virtual slideway according to the data risk.
The working principle and the beneficial effects of the technical scheme are as follows:
by adopting the dynamically flowing line segment, a user can intuitively obtain data from which device to which device when viewing; by observing the flowing speed of the line segment, the speed of data transmission can be visually observed; the type of the data can be seen according to the color emission of the line segment, and the name of the data can be seen in the suspension frame. The risk of the data can be seen from the color emission of the outer-layer wrapped slideway; and further, the user can visually see the data flow direction, the data transmission speed, the data type, the data name and the data risk.
In one embodiment, the artificial intelligence based multiple heterogeneous network data visualization system further comprises:
the display window positioning module is used for acquiring a coordinate area of the display window in a three-dimensional coordinate system;
the second mapping module is used for mapping the three-dimensional multi-element heterogeneous network topological graph in the view field of the display window to the display window for displaying;
the instruction receiving module is used for receiving an operation instruction of a user for the display window, wherein the operation instruction comprises moving or zooming;
the display window adjusting module is used for re-determining the coordinate area of the display window in the three-dimensional coordinate system based on the operation instruction, and re-mapping the three-dimensional multi-element heterogeneous network topological graph in the view field of the display window to the display window for display;
wherein the second mapping module performs operations comprising:
acquiring the position relation between the left eye and the right eye of a user and a display screen corresponding to a display window;
determining a first viewpoint and a second viewpoint which correspond to the left eye and the right eye of the user in the three-dimensional coordinate system respectively based on the position relation and the coordinate area of the display window in the three-dimensional coordinate system;
determining the view boundary of the display window by the first view and the edge of the coordinate area;
taking the position of a connecting line of a first viewpoint and the position of equipment corresponding to the three-dimensional multi-element heterogeneous network topological graph positioned in the view boundary, which passes through the coordinate area, as the mapping position of the equipment on the display window; forming a first mapping image;
determining the view boundary of the display window by the second view and the edge of the coordinate area;
taking the position of a connecting line of the second viewpoint and the position of the corresponding equipment of the three-dimensional multi-element heterogeneous network topological graph positioned in the view boundary passing through the coordinate area as the mapping position of the equipment on the display window; a second mapping image is formed.
And displaying the first mapping image and the second mapping image on the display screen in an interleaving manner.
The working principle and the beneficial effects of the technical scheme are as follows:
through the difference that the left eye and the right eye of people's eye received, first mapping image adopts first display light show, and second mapping image adopts the second display light show, receives the back respectively via left eye and right eye, realizes bore hole 3D effect to improve user's visual experience. Wherein the first mapping image and the second mapping image are displayed on the display screen in an interlaced manner; the other mode is that the adjacent two frames respectively display the first mapping image and the second mapping image. Further, AR glasses may be employed, and the display screen for the left eye position displays the first mapping image and the display screen for the right eye position displays the second mapping image.
In one embodiment, the position of a connection line of the first viewpoint and the position of a corresponding device of the three-dimensional multi-element heterogeneous network topological graph located in the view boundary passing through the coordinate area is used as the mapping position of the device on the display window; forming a first mapping image; the method specifically comprises the following steps:
determining the size of the mapping icon corresponding to the preset icon on the display window based on the size of the preset icon of the equipment, the distance between the position corresponding to the equipment and the mapping position and the distance between the mapping position and the first viewpoint, wherein the specific calculation formula is as follows:
wherein the content of the first and second substances,
representing the size of the mapping icon;
representing the size of a preset icon;
representing a distance of the mapped location to the first viewpoint;
representing a distance of the location of the corresponding device from the mapped location;
when the size of the mapping icon is smaller than a preset threshold value, replacing the mapping icon with a preset mark in the first mapping image;
determining the width of the display window mapped by the starting point end of the line segment based on the size of the preset icon of the device corresponding to the starting point of the line segment, the distance between the position of the corresponding device and the mapping position, and the distance from the mapping position to the first viewpoint
The specific calculation formula is as follows:
wherein the content of the first and second substances,
is a preset standard icon size and is,
is a preset standard width.
The working principle and the beneficial effects of the technical scheme are as follows:
when the three-dimensional multi-element heterogeneous topological graph is projected to a display window, the size of a mapping icon corresponding to a preset icon on the display window is determined based on the size of the preset icon of equipment, the distance between the position corresponding to the equipment and the mapping position and the distance between the mapping position and a first viewpoint; the spatial layering is ensured. Similarly, the width of the line segment starting point end mapped to the display window is determined based on the size of the preset icon of the equipment corresponding to the line segment starting point, the distance between the position of the corresponding equipment and the mapping position and the distance from the mapping position to the first viewpoint, and the spatial layering after the line segment is projected is ensured. Similarly, the second mapping image is also subjected to such processing during the projection process.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (8)
1. A multivariate heterogeneous network data visualization method based on artificial intelligence is characterized by comprising the following steps:
step S1: constructing a three-dimensional multi-element heterogeneous network topological graph;
step S2: acquiring multi-element heterogeneous network data;
step S3: analyzing the multi-element heterogeneous network data, and determining first visual data and data content;
step S4: inputting the data content into a pre-stored neural network model to obtain second visual data;
step S5: labeling in the three-dimensional multi-element heterogeneous network topological graph based on the first visual data and the second visual data;
further comprising:
step S6: acquiring a coordinate area of a display window in a three-dimensional coordinate system;
step S7: mapping the three-dimensional multivariate heterogeneous network topological graph in the view field of the display window to the display window for displaying;
wherein the step S7: mapping the three-dimensional multi-element heterogeneous network topological graph in the view field of the display window to the display window for displaying, specifically comprising:
step S71: acquiring the position relation between the left eye and the right eye of a user and a display screen corresponding to the display window;
step S72: determining a first viewpoint and a second viewpoint which correspond to the left eye and the right eye of the user in the three-dimensional coordinate system respectively based on the position relation and the coordinate area;
step S73: determining a first view boundary of the display window with the first view point and the edge of the coordinate area;
step S74: taking the position of a connecting line of the first viewpoint and the position of the corresponding equipment of the three-dimensional multi-element heterogeneous network topological graph positioned in the first view boundary, which passes through the coordinate area, as the mapping position of the equipment on the display window; forming a first mapping image;
step S75: determining a second view boundary of the display window with the second view point and an edge of the coordinate area;
step S76: taking the position of a connecting line of the second viewpoint and the position of the corresponding equipment of the three-dimensional multi-element heterogeneous network topological graph positioned in the second view boundary, which passes through the coordinate area, as the mapping position of the equipment on the display window; forming a second mapping image;
step S77: the first mapping image and the second mapping image are displayed on the display screen in an interlaced mode;
the step S74: taking the position of a connecting line of the first viewpoint and the position of the corresponding equipment of the three-dimensional multi-element heterogeneous network topological graph positioned in the first view boundary, which passes through the coordinate area, as the mapping position of the equipment on the display window; forming a first mapping image; the method specifically comprises the following steps:
determining the size of the mapping icon corresponding to the preset icon on the display window based on the size of the preset icon of the equipment, the distance between the position of the corresponding equipment and the mapping position and the distance between the mapping position and the first viewpoint, wherein a specific calculation formula is as follows:
wherein the content of the first and second substances,
representing the size of the mapping icon;
representing the size of a preset icon;
representing a distance of the mapped location to the first viewpoint;
representing a distance of the location of the corresponding device from the mapped location;
when the size of the mapping icon is smaller than a preset threshold value, replacing the mapping icon with a preset mark in the first mapping image;
determining the width of the starting point end of the line segment mapped to the display window based on the size of a preset icon of a device corresponding to the starting point of the line segment, the distance between the position of the corresponding device and the mapping position and the distance between the mapping position and the first viewpoint
The specific calculation formula is as follows:
wherein the content of the first and second substances,
is a preset standard icon size and is,
is a preset standard width.
2. The artificial intelligence based multi-element heterogeneous network data visualization method according to claim 1,
the first visualization data comprises: one or more combinations of a sending address, a target address, a data type and data content;
the second visualization data comprises: one or more combinations of data name and data risk;
the step S1: the method for constructing the three-dimensional multi-element heterogeneous network topological graph specifically comprises the following steps:
step S11: acquiring position information and connection relation of each device accessed to the three-dimensional multi-element heterogeneous network;
step S12: establishing a three-dimensional coordinate system by taking any one device as an origin;
step S13: mapping each of the devices to the three-dimensional coordinate system based on the location information and the connection relationship;
step S14: marking the equipment by using a preset virtual icon at the position where the equipment is mapped to the three-dimensional coordinate system; the preset virtual icon corresponds to the type of the equipment;
step S15: and adjusting the size of the preset virtual icon according to the ratio of the parameters of the equipment to the standard parameters.
3. The artificial intelligence based multivariate heterogeneous network data visualization method according to claim 2, wherein the step S5: labeling in the three-dimensional multi-element heterogeneous network topological graph based on the first visual data and the second visual data, specifically comprising:
step S51: taking the position of the equipment corresponding to the sending address in the three-dimensional coordinate system as a starting point; taking the position of the device corresponding to the target address in the three-dimensional coordinate system as an end point, and adopting a plurality of dynamically flowing line segments between the start point and the end point to represent the flow direction of the multi-element heterogeneous network data;
step S52: acquiring the data transmission speed of the multi-element heterogeneous network data, and adjusting the flow speed of the line segment according to the data transmission speed;
step S53: analyzing the first visual data and the second visual data to obtain a data type, a data name and data risk;
step S54: adjusting the color of the line segment according to the data type;
step S55: arranging a suspension frame beside the line segment, and displaying the data name in the suspension frame;
step S56: and arranging a virtual slideway on the outer side of the line segment, and setting the color of the virtual slideway according to the data risk.
4. The artificial intelligence based multi-element heterogeneous network data visualization method according to claim 3,
step S8: receiving an operation instruction of a user for the display window, wherein the operation instruction comprises moving or zooming;
step S9: and based on the operation instruction, re-determining the coordinate area of the display window in the three-dimensional coordinate system, and re-mapping the three-dimensional multi-element heterogeneous network topological graph in the view field of the display window to the display window for display.
5. A multivariate heterogeneous network data visualization system based on artificial intelligence is characterized by comprising: the three-dimensional construction module is used for constructing a three-dimensional multi-element heterogeneous network topological graph;
the data acquisition module is used for acquiring the multi-element heterogeneous network data;
the first visual data determining module is used for analyzing the multi-element heterogeneous network data and determining first visual data and data content;
the second visual data determining module is used for inputting the data content into a pre-stored neural network model to obtain second visual data;
the labeling module is used for labeling the three-dimensional multi-element heterogeneous network topological graph based on the first visual data and the second visual data;
further comprising:
the display window positioning module is used for acquiring a coordinate area of the display window in a three-dimensional coordinate system;
the second mapping module is used for mapping the three-dimensional multi-element heterogeneous network topological graph in the view field of the display window to the display window for displaying;
wherein the second mapping module performs operations comprising:
acquiring the position relation between the left eye and the right eye of a user and a display screen corresponding to the display window;
determining a first viewpoint and a second viewpoint which correspond to the left eye and the right eye of the user in the three-dimensional coordinate system respectively based on the position relation and the coordinate area;
determining a first view boundary of the display window with the first view point and the edge of the coordinate area;
taking the position of a connecting line of the first viewpoint and the position of the corresponding equipment of the three-dimensional multi-element heterogeneous network topological graph positioned in the first view boundary, which passes through the coordinate area, as the mapping position of the equipment on the display window; forming a first mapping image;
determining a second view boundary of the display window with the second view point and an edge of the coordinate area;
taking the position of a connecting line of the second viewpoint and the position of the corresponding equipment of the three-dimensional multi-element heterogeneous network topological graph positioned in the second view boundary, which passes through the coordinate area, as the mapping position of the equipment on the display window; forming a second mapping image;
the first mapping image and the second mapping image are displayed on the display screen in an interlaced mode;
the position of the coordinate area passing through the connecting line of the first viewpoint and the position of the corresponding equipment of the three-dimensional multi-element heterogeneous network topological graph positioned in the first view boundary is used as the mapping position of the equipment on the display window; forming a first mapping image; the method specifically comprises the following steps:
determining the size of the mapping icon corresponding to the preset icon on the display window based on the size of the preset icon of the equipment, the distance between the position of the corresponding equipment and the mapping position and the distance between the mapping position and the first viewpoint, wherein a specific calculation formula is as follows:
wherein the content of the first and second substances,
representing the size of the mapping icon;
representing the size of a preset icon;
representing a distance of the mapped location to the first viewpoint;
representing a distance of the location of the corresponding device from the mapped location;
when the size of the mapping icon is smaller than a preset threshold value, replacing the mapping icon with a preset mark in the first mapping image;
determining the width of the starting point end of the line segment mapped to the display window based on the size of a preset icon of a device corresponding to the starting point of the line segment, the distance between the position of the corresponding device and the mapping position and the distance between the mapping position and the first viewpoint
The specific calculation formula is as follows:
wherein the content of the first and second substances,
is a preset standard icon size and is,
is a preset standard width.
6. The artificial intelligence based multivariate heterogeneous network data visualization system of claim 5,
the first visualization data comprises: one or more combinations of a sending address, a target address, a data type and data content;
the second visualization data comprises: one or more combinations of data name and data risk;
the three-dimensional building block comprises:
the parameter acquisition module is used for acquiring the position information and the connection relation of each device accessed to the three-dimensional multi-element heterogeneous network;
the three-dimensional coordinate system establishing module is used for establishing a three-dimensional coordinate system by taking any one device as an origin;
a first mapping module, configured to map each device to the three-dimensional coordinate system based on the location information and the connection relationship;
the icon determining module is used for marking the equipment by using a preset virtual icon at the position where the equipment is mapped to the three-dimensional coordinate system; the preset virtual icon corresponds to the type of the equipment;
and the icon adjusting module is used for adjusting the size of the preset virtual icon according to the ratio of the parameter of the equipment to the standard parameter.
7. The artificial intelligence based heterogeneous network data visualization system of claim 6, wherein the tagging module performs operations comprising:
taking the position of the equipment corresponding to the sending address in the three-dimensional coordinate system as a starting point; taking the position of the device corresponding to the target address in the three-dimensional coordinate system as an end point, and adopting a plurality of dynamically flowing line segments between the start point and the end point to represent the flow direction of the multi-element heterogeneous network data;
acquiring the data transmission speed of the multi-element heterogeneous network data, and adjusting the flow speed of the line segment according to the data transmission speed;
analyzing the first visual data and the second visual data to obtain a data type, a data name and data risk; adjusting the color of the line segment according to the data type;
arranging a suspension frame beside the line segment, and displaying the data name in the suspension frame;
and arranging a virtual slideway on the outer side of the line segment, and setting the color of the virtual slideway according to the data risk.
8. The artificial intelligence based multivariate heterogeneous network data visualization system of claim 7,
the instruction receiving module is used for receiving an operation instruction of a user for the display window, wherein the operation instruction comprises movement or zooming;
and the display window adjusting module is used for re-determining the coordinate area of the display window in the three-dimensional coordinate system based on the operation instruction, and re-mapping the three-dimensional multi-element heterogeneous network topological graph in the view field of the display window to the display window for display.
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