A situation awareness system fusing multi-source data

Abstract

The application discloses a kind of situation awareness systems of fusion multi-source data, it is related to information processing technical field, including risk association snapshot module, dynamic association module, risk diffusion analysis module, propagation path reconstruction module and risk situation output module: risk association snapshot module, for the situation awareness process of fusion multi-source data, collection enterprise operation data, supply performance data, fund flow data, order execution data and external event data, the influence frequency between risk object, influence duration and influence interval are calculated according to one minute statistical window, and the risk association snapshot of corresponding statistical window is generated.The application can continuously update risk propagation relationship, form real-time risk propagation path, and adjust risk attention priority according to dynamic diffusion intensity, generate enterprise current risk situation chart, make risk propagation process and enterprise current risk evolution state consistent, provide continuous and reliable situation basis for risk monitoring and risk early warning.

Description

Technical Field

[0001] This invention relates to the field of information processing technology, and more specifically to a situational awareness system that integrates multi-source data. Background Technology

[0002] A situational awareness system integrating multi-source data refers to a system designed for enterprise risk monitoring and early warning scenarios. It involves the unified collection, correlation, integration, dynamic analysis, and comprehensive assessment of heterogeneous data from multiple sources, including internal operational data, business data, equipment operation data, personnel behavior data, and financial data, as well as external market environment data, policy and regulatory data, public opinion data, supply chain data, meteorological environment data, and cybersecurity data. This constructs a global situational awareness model reflecting the enterprise's operational status and risk evolution trends. The system continuously identifies enterprise operational risks, supply chain risks, safety production risks, cybersecurity risks, market volatility risks, credit risks, and compliance risks. Furthermore, it combines risk correlations, risk propagation paths, risk impact scope, and risk change trends to form a dynamic risk profile. This enables real-time monitoring, anomaly identification, trend prediction, risk early warning, and decision support for enterprise risks. It provides data support for enterprise risk prevention and control, resource allocation, emergency response, and business management, thereby enhancing the enterprise's ability to perceive, analyze, predict, and comprehensively prevent complex risk events.

[0003] Existing technologies have the following shortcomings: During the continuous evolution of an enterprise's risk posture, some risk relationships dynamically change due to business adjustments, operational strategies, and changes in the external environment. The original risk propagation paths gradually deviate from the current risk propagation characteristics. When the situational awareness system still relies on historical risk relationships for risk analysis, the updating of risk propagation relationships lags behind. This makes it difficult to incorporate newly formed risk propagation paths into the situational analysis process in a timely manner, further reducing the accuracy of enterprise risk propagation trend analysis and affecting the ability to identify major risks in advance.

[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide a situational awareness system that integrates multi-source data to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a situational awareness system integrating multi-source data, comprising a risk correlation snapshot module, a dynamic correlation module, a risk diffusion analysis module, a propagation path reconstruction module, and a risk situation output module.

[0007] The risk association snapshot module is designed for the situational awareness process that integrates multi-source data. It collects enterprise operation data, supply fulfillment data, capital flow data, order execution data, and external event data. It calculates the frequency, duration, and interval of impact between risk objects according to a one-minute statistical window and generates a risk association snapshot for the corresponding statistical window.

[0008] The dynamic association module reads the impact frequency, impact duration and impact interval from the risk association snapshot, performs association migration magnitude calculation on the risk objects corresponding to adjacent statistical windows, and remaps the risk objects whose association migration magnitude exceeds the set value to the new association position to construct a dynamic association map.

[0009] The risk diffusion analysis module, based on the migration amplitude and new location of the association in the dynamic association map, counts the number of times the association location changes, tracks the risk diffusion trajectory according to the continuous migration direction, and marks the risk objects whose migration direction changes more than three times as propagation inflection nodes to obtain the risk diffusion trajectory.

[0010] The propagation path reconstruction module obtains the propagation turning points, migration direction change frequency, and risk propagation span in the risk diffusion trajectory. It adjusts the order of risk impact according to the occurrence time of the propagation turning points, determines the real-time risk propagation path, and promotes the risk propagation relationship to be synchronized with the current risk evolution status.

[0011] The risk situation output module calls upon the risk impact order, propagation turning points, and risk diffusion span in the real-time risk propagation path, calculates the dynamic diffusion intensity corresponding to each risk object, adjusts the risk attention priority according to the dynamic diffusion intensity, generates the current risk situation map of the enterprise, and continuously reflects the changing process of risk propagation relationships.

[0012] Preferably, the steps for generating a risk-related snapshot are as follows:

[0013] Acquire enterprise operation data, supply fulfillment data, cash flow data, order execution data, and external event data to identify risk objects and establish corresponding relationships, and record the occurrence time of each risk object;

[0014] Organize risk objects according to a unified time benchmark, statistically analyze the impact relationships between risk objects, obtain the frequency of impact, duration of impact, and interval of impact, and save the corresponding correlation characteristics;

[0015] Based on the frequency of impact, duration of impact, and interval of impact, organize the statistical window identifier, statistical start time, statistical end time, risk object identifier, and associated risk object identifier to obtain the risk association snapshot of the corresponding statistical window;

[0016] By combining the risk-related snapshots corresponding to each statistical window, and maintaining the continuous correspondence between the risk object identifier, the associated risk object identifier, and the statistical window order, the dynamic changes in the risk-related relationships are obtained, and risk-related snapshots are generated.

[0017] Preferably, for the risk association snapshots corresponding to each statistical window, the changes in the set of associated risk objects corresponding to the same risk object are compared, the newly added associations, the disappeared associations and the continuous associations are recorded, and the frequency of impact, the duration of impact and the interval of impact are respectively associated to obtain the status of changes in risk associations.

[0018] The preferred dynamic association graph construction process is as follows:

[0019] Read the risk association snapshots corresponding to adjacent statistical windows, extract the frequency of impact, duration of impact and interval of impact, establish a continuous correspondence relationship according to the risk object identifier, and obtain the risk association status corresponding to the continuous statistical windows;

[0020] Based on the risk association status corresponding to the continuous statistical window, the association migration range is determined. For risk objects whose association migration range exceeds the set value, the original association position correspondence is terminated and mapped to a new association position.

[0021] By utilizing the new associated locations to organize the relationships between all risk objects, we can obtain statistical window identifiers, risk object identifiers, associated risk object identifiers, migration magnitudes, new associated locations, and the time sequence corresponding to the associated locations, and construct a dynamic association map.

[0022] Preferably, when the migration magnitude exceeds a set value, the original associated position correspondence of the risk object is terminated, and the risk object is mapped to a new associated position according to the latest associated status of the risk object in the current statistical window. The new associated position corresponds to the current associated risk object and the arrangement of associated relationships, and the dynamic association map maintains the continuous change of risk association relationships.

[0023] Preferably, the risk diffusion trajectory acquisition process is as follows:

[0024] Read the migration magnitude and new location of associations in the dynamic association map, establish a continuous time sequence correspondence according to the risk object identifier, and count the number of times the association location changes;

[0025] Determine the continuous migration direction corresponding to the number of times the associated position changes, and maintain a consistent correspondence between the associated migration amplitude, the new associated position, and the continuous migration direction;

[0026] Obtain the development process corresponding to continuous migration directions, organize the initial associated positions, continuous migration directions, number of changes in associated positions, associated migration magnitude, propagation order, and statistical window time order to obtain the risk diffusion trajectory;

[0027] The number of consecutive changes in migration direction corresponding to the statistical risk diffusion trajectory is used to divide the propagation stage, and risk objects whose migration direction changes three or more times consecutively are marked as propagation inflection nodes.

[0028] By combining the transmission turning points to continuously organize the risk diffusion trajectory, the transmission stages, transmission turning points and statistical window time sequence are obtained to obtain the risk diffusion trajectory.

[0029] Preferably, the propagation phase corresponds to a development process in which the continuous migration direction remains consistent. When the migration direction changes, the number of changes in the migration direction is recorded, and a new propagation phase is entered. When the continuous changes in the migration direction reach the set conditions, the corresponding risk object is marked as a propagation turning point.

[0030] The preferred method for determining real-time risk propagation paths is as follows:

[0031] Read the propagation turning points, continuous migration directions, propagation stages, and statistical window time sequence in the risk diffusion trajectory to obtain the frequency of change in migration direction and the span of risk diffusion;

[0032] The propagation stages were reorganized according to the time of the propagation inflection point, the order of risk impact corresponding to each propagation stage was adjusted, and the frequency of change in migration direction and the span of risk diffusion were mapped to each propagation stage.

[0033] By connecting each stage of the propagation using the adjusted risk impact order, and combining the propagation turning points, the frequency of changes in migration direction, and the span of risk diffusion, the real-time risk propagation path is determined.

[0034] Record the changes in the propagation status corresponding to the newly added propagation turning points, adjust the order of risk impact in sync with the changes in the propagation stages, and update the real-time risk propagation path.

[0035] The updated real-time risk propagation path is used to reorganize the risk propagation relationships, ensuring that the propagation turning points, propagation stages, risk impact order, migration direction change frequency, and risk diffusion span are continuously corresponded, and the real-time risk propagation path is determined.

[0036] Preferably, the real-time risk propagation path includes propagation turning points, propagation stages, risk impact order, frequency of migration direction changes, risk diffusion span, propagation order, and statistical window time order; when a new propagation turning point enters the propagation stage, the propagation stages are reorganized, the risk impact order is adjusted, and the real-time risk propagation path is updated.

[0037] Preferably, the process for generating the current risk profile of an enterprise is as follows:

[0038] Read the order of risk impact, inflection points, risk spread span, propagation stages and statistical window time sequence in the real-time risk propagation path, establish a unified correspondence according to the risk object identifier, and obtain the current propagation status set of each risk object;

[0039] By combining the current propagation status set of each risk object, the dynamic diffusion intensity is obtained, and the dynamic diffusion intensity is kept consistent with the order of risk impact, propagation turning points, and risk diffusion span.

[0040] The dynamic diffusion intensity is used to reorganize the attention relationships among all risk objects, adjust the risk attention priority, and arrange the current attention order of risk objects;

[0041] The adjusted risk focus priority is used to organize the current propagation status of all risk objects, obtain the risk object identification, risk focus priority, dynamic diffusion intensity, risk impact order, propagation turning point, propagation stage, risk diffusion span and statistical window time sequence, and generate the current risk situation map of the enterprise.

[0042] The system continuously updates the enterprise's current risk situation map, including risk focus priorities, dynamic diffusion intensity, propagation stages, propagation turning points, and risk diffusion span. It also continuously records the changing process of risk propagation relationships and generates the enterprise's current risk situation map.

[0043] The technical effects and advantages provided by the present invention in the above technical solution are as follows:

[0044] This invention constructs risk association snapshots and combines them with dynamic association graphs to continuously record the changing processes of relationships between risk objects, enabling risk propagation relationships to be continuously updated with the statistical window. Furthermore, it reconstructs risk association positions based on the magnitude of association migration, and then continuously adjusts risk propagation relationships by combining risk diffusion trajectories and real-time risk propagation paths. This allows risk propagation analysis to align with the current risk evolution status of the enterprise, thereby enhancing the continuous representation of the risk propagation process and improving the timeliness of enterprise risk propagation trend analysis.

[0045] This invention calculates the dynamic diffusion intensity of each risk object based on the real-time risk propagation path, and then adjusts the risk focus priority according to the dynamic diffusion intensity to form a current risk situation map of the enterprise. This allows the enterprise's risk situation to continuously reflect the changing process of risk propagation relationships. The current risk situation map of the enterprise can be updated synchronously with the risk propagation status, ensuring that the propagation relationships and propagation impacts between risk objects remain dynamically corresponding. This helps enterprises to identify changes in risk propagation trends in a timely manner and provides a situational basis for risk monitoring and risk early warning that is consistent with the current risk evolution status. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0047] Figure 1 This is a schematic diagram of a situational awareness system that integrates multi-source data according to the present invention. Detailed Implementation

[0048] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0049] This invention provides, for example Figure 1 The situational awareness system shown includes a risk correlation snapshot module, a dynamic correlation module, a risk diffusion analysis module, a propagation path reconstruction module, and a risk situation output module.

[0050] The risk association snapshot module is designed for the situational awareness process that integrates multi-source data. It collects enterprise operation data, supply fulfillment data, capital flow data, order execution data, and external event data. It calculates the frequency, duration, and interval of impact between risk objects according to a one-minute statistical window and generates a risk association snapshot for the corresponding statistical window.

[0051] For the situational awareness process involving the integration of multi-source data, it is necessary to continuously acquire information from multiple sources generated during enterprise operations and organize risk association status according to a unified time scale. This ensures that data from different sources can be mapped to the same risk object, while maintaining continuous recording of risk association relationships over time. This provides a continuous data foundation for subsequent calculations of the migration magnitude of risk object associations. Therefore, risk association snapshots are generated according to a one-minute statistical window. The specific steps are as follows:

[0052] To address the situational awareness process that integrates multi-source data, we continuously collect enterprise operational data, supply fulfillment data, cash flow data, order execution data, and external event data, and identify risk targets and establish corresponding relationships according to a unified time benchmark. Enterprise operational data includes business plans, business execution status, and changes in operational indicators; supply fulfillment data includes supplier fulfillment status, delivery progress, and material supply information; cash flow data includes payment and receipt status, cash flow direction, and cash change information; order execution data includes order creation, execution, transfer, and completion status information; and external event data includes changes in the market environment, policy and regulatory changes, industry dynamics, and public event information.

[0053] After data collection, data with the same associated carriers are mapped to corresponding risk objects, using enterprise entities, business objects, supply chain nodes, order identifiers, funding objects, or event objects as association carriers. This ensures that each risk object corresponds to risk information in the same business activity, and data from different sources can establish corresponding relationships around the same risk object. At the same time, the occurrence time of each data point is recorded according to a unified time benchmark, so that all risk objects have continuous time attributes, providing a unified data source for the description of risk relationships in subsequent statistical windows.

[0054] Using a fixed statistical window of one minute, risk objects that have completed the establishment of corresponding relationships are organized. The association status between risk objects is described according to the statistical window range, and the frequency, duration and interval of the impact between risk objects are calculated.

[0055] The one-minute statistical windows are arranged sequentially according to continuous time. Each statistical window corresponds to a fixed start and end time. The same risk object maintains a consistent identifier across different statistical windows, ensuring continuous correspondence between adjacent statistical windows. When two risk objects correspond to the same enterprise entity, the same business object, the same order process, the same supply chain node, or have a continuous business flow relationship within the same statistical window, an influence relationship between the two risk objects is recorded. When the influence relationship appears multiple times within the statistical window, the cumulative number of occurrences is recorded as the influence frequency. When the influence relationship persists within the statistical window, the cumulative duration is recorded as the influence duration. When there is a time interval between two consecutive influence relationships, the corresponding time distance is recorded as the influence interval.

[0056] When the same risk object has an impact relationship with multiple risk objects, the frequency, duration and interval of the impact are recorded respectively, so that each statistical window can save all the relationships and corresponding relationship characteristics between risk objects.

[0057] The relationships and characteristics among all risk objects within a statistical window are organized into risk association snapshots for that window, providing a complete description of the risk association status within the window. Each risk association snapshot includes the statistical window identifier, start time, end time, risk object identifier, associated risk object identifier, impact frequency, impact duration, and impact interval. These elements collectively correspond to the association status among risk objects within the statistical window. Risk association snapshots record the relationships and changes in association among all risk objects within a given statistical window. They not only preserve the existence of associations but also simultaneously save the impact frequency, duration, and interval corresponding to those associations, allowing for a description of the risk association status within the same statistical window from multiple perspectives, including the occurrence, persistence, and pace of association changes.

[0058] Each statistical window corresponds to an independent risk association snapshot. Each risk association snapshot maintains the risk association status within the corresponding statistical window without change, thus ensuring that each statistical window has an independent and complete risk association record.

[0059] Risk-related snapshots are generated continuously according to the time sequence of the statistical window, and the continuous correspondence between risk object identifiers, associated risk object identifiers, and statistical window order between adjacent risk-related snapshots is maintained, so that multiple risk-related snapshots can jointly describe the dynamic changes in risk-related relationships during the situational awareness process of integrating multi-source data.

[0060] As enterprise operating data, supply fulfillment data, cash flow data, order execution data, and external event data continue to enter new statistical windows, only the impact frequency, impact duration, and impact interval corresponding to the current statistical window are updated. The newly generated risk association snapshot corresponds to the risk association status within the current statistical window, while the risk association snapshots that have already been generated maintain the association relationship and association characteristics within the corresponding statistical window without change.

[0061] Since the risk objects in adjacent statistical windows maintain a unified identifier, and the statistical windows can be arranged continuously in chronological order, the multiple risk association snapshots generated consecutively together constitute a complete record sequence of risk association relationships changing over time. This allows the development, change, and evolution of the association relationships between risk objects to be expressed in continuous chronological order. At the same time, it provides a unified data foundation and a continuous state foundation for subsequently calculating the magnitude of risk object association migration using the risk association snapshots corresponding to adjacent statistical windows.

[0062] The dynamic association module reads the impact frequency, impact duration and impact interval from the risk association snapshot, performs association migration magnitude calculation on the risk objects corresponding to adjacent statistical windows, and remaps the risk objects whose association migration magnitude exceeds the set value to the new association position to construct a dynamic association map.

[0063] Reading the association features from risk association snapshots requires maintaining a continuous correspondence between risk association states between adjacent statistical windows. This ensures that the association states of risk objects within consecutive statistical windows can be continuously expressed in a unified time sequence. Furthermore, changes in risk association states are converted into changes in association positions, thus continuously recording the evolution of risk association relationships. The magnitude of association migration is used to describe the degree of change in the association state of risk objects, and then the association positions are updated according to the magnitude of association migration. Finally, a dynamic association map is constructed, providing a continuously changing basis for subsequent risk diffusion trajectory tracking. The specific implementation steps are as follows:

[0064] The system reads risk association snapshots corresponding to adjacent statistical windows, extracts the frequency, duration, and interval of impact from these snapshots, and establishes a continuous correspondence based on the risk object identifier, ensuring a consistent correspondence of risk association states within consecutive statistical windows. Risk association snapshots are arranged sequentially according to the time order of the statistical windows, with each snapshot corresponding to the association state among all risk objects within a given window. Risk association snapshots corresponding to adjacent statistical windows record the association changes of the same risk object over a continuous time range.

[0065] During the reading process, the risk object identifier is used as the basis for continuous correspondence. The risk object in the current statistical window is uniquely matched with the corresponding risk object in the previous statistical window. At the same time, the frequency of impact, duration of impact, and interval of impact recorded between the corresponding risk object and the associated risk object are read, so that the same risk object retains a complete association status in the continuous statistical window.

[0066] When the same risk object corresponds to multiple associated risk objects, the corresponding relationship is maintained continuously, and the frequency, duration, and interval of each impact are read separately, so that each group of relationships has an independent relationship status. When associated risk objects are added, reduced, or replaced, the corresponding relationship status changes are recorded synchronously, so that the risk relationship status in the continuous statistics window not only includes whether the relationship exists, but also fully reflects the number of times the relationship occurs, its duration, and its time distribution. This maintains the continuous expression of the risk relationship status along the time direction, providing a unified relationship basis for subsequent description of relationship migration.

[0067] The degree of association change of risk objects between adjacent statistical windows is described by continuous corresponding risk association states. The association migration magnitude is determined by the frequency of influence, duration of influence, and interval of influence. Risk objects with association migration magnitudes exceeding a set value are remapped to new association positions. The association migration magnitude is used to represent the degree of change in the association state of risk objects between consecutive statistical windows. It corresponds to the association change result generated by the changes in the frequency of influence, duration of influence, and interval of influence, rather than a single change in association relationship.

[0068] When the frequency of influence changes, it indicates a new rhythm of change in the relationship between risk objects; when the duration of influence changes, it indicates a change in the continuity of the relationship between risk objects; when the interval between influences changes, it indicates a new temporal distribution pattern in the relationship between risk objects. The above-mentioned relationship states collectively reflect the migration of the relationship between risk objects along the time direction. Therefore, the magnitude of the migration of the relationship can fully express the degree of change in the relationship between risk objects.

[0069] The set value is used to distinguish between the normal fluctuation state and the migration state of risk associations within the statistical window. When the migration amplitude does not exceed the set value, the original association position of the risk object is maintained, ensuring continuous association between corresponding risk objects in consecutive statistical windows. When the migration amplitude exceeds the set value, the original association position of the risk object is terminated, and it is remapped to a new association position according to the latest association state of the risk object within the current statistical window. The new association position describes the actual association state of the risk object in all associations within the current statistical window. It corresponds not only to the current associated risk objects but also to the current arrangement of associations, ensuring that the new association position accurately reflects the development state of risk object associations within the current statistical window, while maintaining continuous change of association positions between adjacent statistical windows over time.

[0070] The relationships between all risk objects are organized using the newly remapped associated positions, constructing a dynamic association graph. This dynamic association graph continuously records the migration status of risk associations. The dynamic association graph describes the evolving relationship between all risk objects within a continuous statistical window over time. It includes the statistical window identifier, risk object identifier, associated risk object identifier, association migration magnitude, new associated position, and the time sequence corresponding to the associated position. All these elements collectively describe the dynamic evolution of risk associations. Each risk object in the dynamic association graph maintains a unique identifier, and each new associated position corresponds to the actual association status of a risk object within the current statistical window. Adjacent statistical windows maintain a continuous mapping relationship between corresponding risk objects. When a risk object undergoes another association migration, only the new associated position and migration magnitude of the corresponding risk object are updated; the remaining risk objects retain their current associated positions, ensuring that the dynamic association graph always maintains a continuously changing state of risk associations.

[0071] Because the dynamic association map continuously organizes multiple new association locations according to the statistical window time sequence, it can completely preserve the development process of the risk object association relationship from the original association location to the new association location. At the same time, it continuously reflects the range, order and status of the association relationship changes. This allows the dynamic changes of risk association relationships in the situational awareness process of integrating multi-source data to be continuously expressed in a unified time sequence. This provides a continuous and consistent basis for expressing association relationships for subsequent tracking of risk diffusion trajectory, identification of propagation turning points and construction of real-time risk propagation paths according to the new association locations.

[0072] The risk diffusion analysis module, based on the migration amplitude and new location of the association in the dynamic association map, counts the number of times the association location changes, tracks the risk diffusion trajectory according to the continuous migration direction, and marks the risk objects whose migration direction changes more than three times as propagation inflection nodes to obtain the risk diffusion trajectory.

[0073] To address the changes in relationships within a dynamic correlation graph, it is necessary to identify the development path of risk relationships along the time axis and continuously record the expansion of risk object relationships from one correlation position to another, enabling the risk propagation status to be expressed in a continuous temporal sequence. The evolution of risk relationships is characterized by the magnitude of correlation migration, new correlation positions, and continuous migration directions. Transmission inflection points are identified based on changes in propagation direction, ultimately yielding the risk diffusion trajectory. This provides a continuous propagation basis for subsequent adjustments to the order of risk impact. The specific implementation steps are as follows:

[0074] The dynamic association graph reads the migration magnitude and new association positions from the data, establishes a continuous time-series correspondence based on the risk object identifier, and counts the number of association position changes for each risk object. The dynamic association graph is organized continuously according to the time sequence of statistical windows. Each statistical window stores the migration magnitude and new association position of the corresponding risk object. The same risk object maintains a consistent risk object identifier within consecutive statistical windows, ensuring that the new association positions of risk objects in different statistical windows can be continuously correlated.

[0075] During the statistical process, the new associated position is used as the continuous recording object. When the new associated position of the risk object changes in the adjacent statistical window, the corresponding change is recorded as a change in associated position. When the new associated position remains the same, the number of changes in the current associated position is kept continuous and no new change is added.

[0076] At the same time, each change in the associated position corresponds synchronously to the migration range of the associated position in the current statistical window. This ensures that the number of changes in the associated position not only reflects the number of times the associated position of the risk object has changed, but also reflects the degree of change in the corresponding associated status. As a result, the risk object always maintains a complete record of changes in the associated position within the continuous statistical window, providing a continuous basis for describing the development direction of the associated relationship of the risk object.

[0077] The evolution of association relationships is based on the number of changes in associated positions. The continuous migration direction is determined according to the order of changes in new associated positions within the continuous statistical window, and this direction is used to describe the development direction of the association relationships of risk objects. The continuous migration direction represents the development direction of a risk object within the continuous statistical window, from a new associated position in the previous statistical window to a new associated position in the current statistical window. It signifies the continuous expansion of the corresponding risk association relationship over time, rather than a change in associated position within a single statistical window.

[0078] When a risk object corresponds to multiple new associated positions sequentially over time, these new associated positions connect to form a continuous migration direction, allowing for a continuous expression of the development process of the risk object's association relationships. As the magnitude of the association migration changes continuously, the corresponding continuous migration direction continues to extend. When the magnitude of the association migration undergoes a new change, the continuous migration direction adjusts its corresponding development direction synchronously, ensuring that the magnitude of the association migration, the new associated positions, and the continuous migration direction always maintain a consistent correspondence. Because the continuous change in the associated positions of a risk object indicates that the risk object's association relationships are continuously expanding towards new associated objects, the continuous migration direction can continuously reflect the development and expansion direction of risk association relationships, providing a continuous directional basis for identifying the risk propagation process.

[0079] Using the continuous migration direction as the basis for risk propagation, the development process of the association between risk objects is continuously organized along the continuous migration direction to obtain the risk diffusion trajectory. The risk diffusion trajectory describes the development path of the association between risk objects gradually expanding along the continuous migration direction within a continuous statistical window. It includes the initial association position, continuous migration direction, number of changes in association position, association migration magnitude, propagation order, and the corresponding statistical window time order. All these elements together describe the development process of the risk association.

[0080] Each segment of the risk diffusion trajectory corresponds to the continuous migration direction of the risk object's association relationship within a continuous statistical window. Adjacent diffusion paths maintain a continuous temporal correspondence, ensuring that the development process of the risk object's association relationship gradually expanding from its initial associated position to multiple new associated positions can be fully preserved. At the same time, the risk diffusion trajectory not only reflects the expansion range of the risk object's association relationship but also continuously expresses the chronological order of risk propagation, providing a complete trajectory basis for subsequent identification of changes in the propagation direction.

[0081] The system continuously records changes in the direction of migration along the risk diffusion trajectory, counting the number of consecutive changes in migration direction for each risk object. The system then divides the diffusion process into stages based on these changes, marking risk objects with three or more consecutive changes in migration direction as inflection points. A diffusion stage represents a development process where the direction of migration remains consistent throughout the risk diffusion trajectory, with the corresponding point between adjacent stages indicating a change in the direction of migration. An inflection point represents a point where the direction of migration is continuously adjusted during the risk diffusion process, corresponding to the transition from one diffusion stage to another.

[0082] When the continuous migration direction remains consistent, the current propagation stage continues. When the continuous migration direction changes, a change in migration direction is recorded, and a new propagation stage begins. When the migration direction changes continuously again, the number of corresponding changes in migration direction continues to accumulate. When the migration direction changes continuously three times or more, the corresponding risk object is marked as a propagation inflection point. Three consecutive changes indicate that the risk association has undergone multiple propagation stages, distinguishing between normal changes in the association within the statistical window and the development state of continuous adjustment in the propagation direction. Therefore, the propagation inflection point can accurately reflect the position of continuous adjustment in the propagation direction during the risk propagation process, while maintaining a consistent correspondence between the propagation inflection point and the magnitude of the association migration, the number of changes in the association position, the continuous migration direction, and the propagation stage.

[0083] Using propagation inflection points as the basis for dividing risk propagation stages, the risk diffusion trajectory is continuously organized to obtain the final risk diffusion trajectory, ensuring that the trajectory continuously reflects the development process of risk relationships. Propagation inflection points divide the risk diffusion trajectory into multiple continuous propagation stages. Each propagation stage corresponds to a development process where the continuous migration direction remains consistent, while adjacent propagation stages correspond to a development process where the propagation direction continuously adjusts. Therefore, the final risk diffusion trajectory not only includes the risk object identification, initial association location, continuous migration direction, association migration magnitude, number of association location changes, propagation sequence, propagation stages, propagation inflection points, and statistical window time sequence, but also maintains a continuous correspondence between these elements. This allows the risk diffusion trajectory to fully describe the development process of risk relationships from the initial diffusion state to subsequent diffusion states.

[0084] As the dynamic correlation map is continuously updated, the risk diffusion trajectory is updated synchronously with the corresponding propagation stages and propagation turning points. This ensures that the development direction, diffusion order, propagation stages, and propagation changes of risk correlations during the situational awareness process involving multi-source data are always continuously expressed. It also provides a continuous and consistent data foundation and propagation basis for adjusting the order of risk impact according to propagation turning points and constructing real-time risk propagation paths.

[0085] The propagation path reconstruction module obtains the propagation turning points, migration direction change frequency, and risk propagation span in the risk diffusion trajectory. It adjusts the order of risk impact according to the occurrence time of the propagation turning points, determines the real-time risk propagation path, and promotes the risk propagation relationship to be synchronized with the current risk evolution status.

[0086] To address the propagation status within a risk diffusion trajectory, it is necessary to further integrate propagation inflection points, the frequency of changes in migration direction, and the span of risk diffusion to continuously organize the risk propagation relationships. This ensures that the risk propagation sequence remains consistent with the current risk evolution and forms a development path that continuously reflects the current propagation status. Therefore, obtaining propagation inflection points, the frequency of changes in migration direction, and the span of risk diffusion within the risk diffusion trajectory, adjusting the order of risk impacts according to the occurrence time of propagation inflection points, determining the real-time risk propagation path, and ensuring that the risk propagation relationships synchronously align with the current risk evolution status involves the following specific steps:

[0087] The system reads the propagation inflection points, continuous migration directions, propagation stages, and statistical window time sequence from the risk diffusion trajectory. It then obtains the frequency of migration direction changes based on the changes in continuous migration directions and the risk diffusion span based on the coverage of the continuous migration directions. The risk diffusion trajectory stores propagation inflection points, propagation stages, continuous migration directions, associated migration amplitudes, number of associated location changes, and statistical window time sequence, maintaining a continuous correspondence between these elements.

[0088] The frequency of migration direction changes indicates the density of changes in migration direction within a continuous statistical window. It is formed by the number of migration direction changes within the continuous statistical window and the corresponding distribution of the statistical window, ensuring that the frequency of migration direction changes continuously reflects the development status of risk propagation direction. The risk diffusion span indicates the range of associated locations covered by the risk object as it expands along the continuous migration direction from its initial associated location to its current associated location. It corresponds to the development range of risk propagation, ensuring that the risk diffusion span continuously reflects the risk propagation coverage status. Propagation turning points, migration direction change frequency, and risk diffusion span correspond to the risk propagation direction conversion state, propagation direction change state, and propagation coverage state, respectively, maintaining a consistent temporal correspondence and providing a continuous propagation characteristic basis for subsequent adjustments to the risk impact order.

[0089] Using the occurrence time of the inflection point as the time basis for risk propagation, the propagation stages are reorganized according to the occurrence time of the inflection point, and the order of risk impact corresponding to each propagation stage is adjusted simultaneously to maintain the continuity and consistency of the chronological relationship of risk propagation. The propagation inflection point corresponds to the position where the direction of risk propagation undergoes continuous adjustment. Different propagation inflection points form a continuous time series according to the statistical window time sequence, with each propagation inflection point corresponding to a transition position in the propagation stage. The order of risk impact is used to represent the chronological relationship of risk propagation development among multiple risk objects, describing the temporal order of the expansion of the influence of each risk object during the risk propagation process.

[0090] When a propagation inflection point occurs within a preceding statistical window, its corresponding propagation stage is prioritized, and its risk impact order remains prioritized. When a propagation inflection point occurs within a subsequent statistical window, its corresponding propagation stage is sequentially connected to the preceding propagation stage, allowing the risk impact order to be continuously adjusted with each propagation stage. Simultaneously, the frequency of changes in migration direction and the span of risk diffusion are mapped to each propagation stage, ensuring that changes in propagation direction and propagation coverage are synchronously integrated into the risk impact order, forming a continuous propagation organizational relationship that aligns with the risk propagation development process.

[0091] The development relationships between each propagation stage are reconnected using the adjusted risk impact order to form a continuous propagation sequence. This sequence, combined with propagation inflection points, frequency of migration direction changes, and risk diffusion span, determines the real-time risk propagation path. The real-time risk propagation path describes the actual propagation development path of the risk object under the current propagation state within the statistical window. It includes propagation inflection points, propagation stages, risk impact order, frequency of migration direction changes, risk diffusion span, propagation sequence, and statistical window time sequence. All these elements collectively describe the current development state of risk propagation.

[0092] Each stage of the real-time risk propagation path corresponds to an adjusted order of risk impact. Adjacent propagation stages are continuously connected based on the timing of propagation inflection points, ensuring that the propagation sequence fully reflects the chronological relationship of risk propagation development. The frequency of migration direction changes continuously reflects the state of propagation direction changes, and the risk diffusion span continuously reflects the coverage of risk propagation. Each propagation stage maintains a continuous correspondence. Therefore, the real-time risk propagation path is not a fixed propagation route, but rather a continuously evolving path based on the current statistical window's propagation status, providing a continuous expression basis for the continuous updating of risk propagation relationships.

[0093] The system continuously records the changes in the propagation status corresponding to new propagation inflection points along the real-time risk propagation path, and adjusts the order of risk impact synchronously based on changes in the propagation stage to ensure that the risk propagation relationship remains consistent with the current propagation status. As the risk diffusion trajectory is continuously updated, new propagation inflection points enter existing propagation stages, the frequency of changes in migration direction synchronously reflects new changes in the propagation direction, and the risk diffusion span synchronously reflects the development of the risk propagation coverage.

[0094] When a new inflection point in the spread is formed, the corresponding spread stage is reorganized, and the order of risk impact is adjusted synchronously with the spread stage; when the frequency of changes in the direction of migration changes, the development status of the corresponding spread stage is updated synchronously; when the span of risk diffusion changes, the spread coverage of each spread stage is continuously updated.

[0095] Because the real-time risk propagation path is continuously updated and adjusted in sync with the risk diffusion trajectory, the real-time risk propagation path always corresponds to the risk propagation status within the current statistical window, rather than a fixed propagation path. This ensures that there is always a continuous correspondence between the propagation turning point, propagation stage, risk impact order, frequency of change in migration direction, and risk diffusion span.

[0096] The risk propagation path is continuously updated to reorganize risk propagation relationships, ensuring that these relationships align with the current state of risk evolution. The real-time risk propagation path continuously adjusts the propagation stages and the order of risk impact based on the timing of propagation inflection points. When new propagation changes occur in the risk diffusion trajectory, new inflection points are added, re-dividing the propagation stages, reorganizing the propagation order, and simultaneously adjusting the order of risk impact. The real-time risk propagation path is updated accordingly, and the risk propagation relationships are adjusted accordingly, thus forming a complete dynamic propagation organization process.

[0097] The resulting real-time risk propagation path continuously preserves the correspondence between propagation turning points, propagation stages, propagation order, risk impact order, frequency of migration direction changes, risk diffusion span, and statistical window time sequence. This ensures that the risk propagation relationship remains synchronized with the current risk evolution state, continuously reflecting the development direction, propagation order, propagation coverage, and propagation evolution state of risk propagation during the process of integrating multi-source data for situational awareness. It also provides continuous, complete, and consistent propagation basis for generating the enterprise's current risk situation map.

[0098] To fully understand the specific implementation of this process, the following example illustrates it in more detail: Assume there are five risk objects in the enterprise's risk diffusion trajectory: risk object A, risk object B, risk object C, and risk object D. The statistical windows are 09:00, 09:01, 09:02, 09:03, 09:04, and 09:05, respectively. In the risk diffusion trajectory, the propagation turning points occur at 09:01, 09:03, and 09:05. Between 09:01 and 09:03, the migration direction changes twice consecutively, forming a migration direction change frequency within the three statistical windows. Between 09:03 and 09:05, the migration direction changes four times consecutively, forming another migration direction change frequency within the three statistical windows. Therefore, the latter corresponds to a more frequent change in propagation direction.

[0099] Simultaneously, risk object A migrates along the continuous direction, passing through associated locations P1, P2, P3, P4, and P5 in sequence, covering a total of 5 associated locations, thus the risk diffusion span is 5; risk object B migrates along the continuous direction, passing through associated locations Q1, Q2, and Q3 in sequence, covering a total of 3 associated locations, thus the risk diffusion span is 3. Subsequently, the propagation stages are reorganized according to the time of the propagation inflection points, with 09:01 corresponding to propagation stage one, 09:03 corresponding to propagation stage two, and 09:05 corresponding to propagation stage three. The order of risk impact is also adjusted accordingly, so that the risk impact order of risk object A, risk object C, risk object B, and risk object D is adjusted to first, second, third, and fourth, respectively.

[0100] Based on the adjusted risk impact order, the propagation stages are reconnected to form a real-time risk propagation path: Risk Object A - Risk Object C - Risk Object B - Risk Object D. This real-time path includes not only the times of the propagation turning points (09:01, 09:03, 09:05) but also the frequency of migration direction changes, risk spread span, propagation stages, and risk impact order. When a new propagation turning point is added to the statistics window at 09:06, and Risk Object C is added to a new associated position P6, the risk spread span expands from 5 to 6, and the cumulative number of migration direction changes reaches 6. The corresponding propagation stages are then reorganized, and the risk impact order is adjusted to Risk Object C, Risk Object A, Risk Object B, Risk Object D. The real-time risk propagation path is simultaneously updated to Risk Object C - Risk Object A - Risk Object B - Risk Object D, ensuring that the risk propagation relationship always aligns with the current risk evolution.

[0101] The risk situation output module calls the risk impact order, propagation turning point and risk diffusion span in the real-time risk propagation path, calculates the dynamic diffusion intensity of each risk object, adjusts the risk attention priority according to the dynamic diffusion intensity, generates the current risk situation map of the enterprise, and continuously reflects the changing process of risk propagation relationship.

[0102] To assess the current risk propagation status reflected in the real-time risk propagation path, it is necessary to combine the chronological order of risk propagation development, changes in propagation direction, and propagation coverage to continuously express the current propagation impact of each risk object. Based on this current propagation impact, the attention relationships between risk objects should be reorganized to form a current risk situation map that continuously reflects the evolution of enterprise risks. Therefore, by calling upon the risk impact order, propagation turning points, and risk diffusion span in the real-time risk propagation path, the dynamic diffusion intensity corresponding to each risk object is calculated. The risk attention priority is adjusted according to the dynamic diffusion intensity to generate the current risk situation map of the enterprise, continuously reflecting the changing process of risk propagation relationships. The specific steps are as follows:

[0103] Read the order of risk impact, inflection points, risk spread span, spread stages and statistical window time sequence in the real-time risk propagation path, and establish a unified correspondence according to the risk object identifier to form a set of the current propagation status of each risk object.

[0104] The real-time risk propagation path stores the risk impact order, propagation inflection points, propagation stages, frequency of migration direction changes, risk diffusion span, propagation sequence, and statistical window time sequence, with all items maintaining a consistent correspondence. During the reading process, each risk object retains a unique risk object identifier and corresponds to the current risk impact order, propagation stage, corresponding propagation inflection point, and corresponding risk diffusion span, ensuring that each risk object forms a complete propagation state within the current statistical window. The risk impact order indicates the propagation sequence of the risk object in the current risk propagation state; the propagation inflection point indicates the location where the risk propagation direction continuously adjusts; the risk diffusion span indicates the range of associated locations covered by the risk object as it expands along the continuous migration direction from the initial associated location to the current associated location. All propagation states together form the current propagation state set of the risk object, ensuring that the subsequent dynamic diffusion intensity is always based on a unified propagation state and maintains a continuous correspondence with the real-time risk propagation path.

[0105] The dynamic diffusion intensity is formed by using the current propagation status set of risk objects as the basis for expressing propagation impact, and combining the risk impact order, propagation inflection points, and risk diffusion span. This allows each risk object to correspond to its current propagation impact status. The dynamic diffusion intensity comprehensively describes the degree of risk propagation impact corresponding to a risk object within the current statistical window. It is continuously updated as the risk impact order changes, propagation inflection points change, and the risk diffusion span changes, rather than being fixed to a single risk object. When the risk impact order changes, the dynamic diffusion intensity synchronously reflects the change in the sequence of risk propagation; when propagation inflection points are added, removed, or their positions change, the dynamic diffusion intensity synchronously reflects the change in the direction of propagation conversion; and when the risk diffusion span changes, the dynamic diffusion intensity synchronously reflects the change in the coverage area of ​​risk propagation.

[0106] The risk objects are continuously corresponded between adjacent statistical windows. The dynamic diffusion intensity is updated only for risk objects whose propagation status changes in the current statistical window. The dynamic diffusion intensity of other risk objects is continuously maintained in the previous statistical window, so that the dynamic diffusion intensity always continuously expresses the current propagation impact status of each risk object and keeps it synchronized with the real-time risk propagation path.

[0107] The attention relationships among all risk objects are reorganized based on the dynamic diffusion intensity corresponding to each risk object. The risk attention priority is adjusted according to the dynamic diffusion intensity, and the risk objects are then rearranged according to the adjusted risk attention priority to form the current risk attention order. The risk attention priority indicates the order of attention corresponding to multiple risk objects in the current risk propagation state, reflecting the current development position of the risk object's propagation impact. When the dynamic diffusion intensity changes, the risk attention priority of the corresponding risk object is adjusted synchronously; when the dynamic diffusion intensity remains continuously corresponding, the risk attention priority maintains its current arrangement; when the dynamic diffusion intensity corresponding to multiple risk objects changes simultaneously, the risk attention priority of each risk object is rearranged according to the current dynamic diffusion intensity.

[0108] The dynamic diffusion intensity continuously reflects the current propagation and impact status of risk objects. Therefore, the risk focus order is reorganized based on the dynamic diffusion intensity to ensure that the risk focus priority always remains consistent with the current propagation status. After adjusting the risk focus priority, the current arrangement of all risk objects is reorganized according to the adjusted risk focus priority to ensure that the current propagation and impact order of risk objects is continuously updated, providing a unified risk focus basis for generating the enterprise's current risk situation map.

[0109] The current propagation status of all risk objects is organized according to the reorganized risk object arrangement, generating a current risk situation map for the enterprise, and maintaining synchronization between the current risk situation map and the real-time risk propagation path. The current risk situation map describes the propagation status of all risk objects and the development status of risk attention relationships within the current statistical window. It includes risk object identification, risk attention priority, dynamic diffusion intensity, risk impact order, propagation turning point, propagation stage, risk diffusion span, and statistical window time sequence. All these elements together describe the current risk propagation status of the enterprise.

[0110] In the current risk situation map of an enterprise, each risk object is arranged according to the reorganized risk attention priority, and the propagation relationship between adjacent risk objects is continuously corresponding. The dynamic diffusion intensity corresponds to the current propagation impact status of the risk object, the propagation turning point corresponds to the state of the change in propagation direction, the propagation stage corresponds to the propagation development process, and the risk diffusion span corresponds to the propagation coverage. All the propagation statuses together form the current risk situation map of the enterprise, so that the current risk situation map of the enterprise always corresponds to the risk propagation status within the current statistical window, rather than the propagation status corresponding to the historical statistical window.

[0111] The system continuously records changes in risk propagation relationships using the enterprise's current risk posture map, ensuring that the map is updated synchronously with real-time risk propagation paths and continuously reflects these changes. As real-time risk propagation paths are continuously updated, the order of risk impact, propagation turning points, propagation stages, and risk diffusion span change simultaneously. The dynamic diffusion intensity corresponding to each risk object is adjusted accordingly, risk attention priorities are reorganized, and the arrangement of risk objects is readjusted. The enterprise's current risk posture map is updated synchronously with the corresponding propagation status.

[0112] Because the current risk situation map of an enterprise is always formed based on the real-time risk propagation path corresponding to the current statistical window, it can continuously record changes in risk attention priority, propagation stage, propagation turning point, dynamic diffusion intensity, and risk diffusion span. This ensures that the process of risk propagation relationship changes is continuously preserved along the time sequence of the statistical window and always remains synchronized with the current risk evolution state. Thus, it continuously reflects the development direction, propagation sequence, propagation coverage, and propagation evolution state of risk propagation relationships during the process of integrating multi-source data for situational awareness. This provides a continuous, complete, and consistent risk situation expression basis for enterprise risk monitoring, risk early warning, and risk disposal that is consistent with the current risk evolution state.

[0113] This invention constructs risk association snapshots and combines them with dynamic association graphs to continuously record the changing processes of relationships between risk objects, enabling risk propagation relationships to be continuously updated with the statistical window. Furthermore, it reconstructs risk association positions based on the magnitude of association migration, and then continuously adjusts risk propagation relationships by combining risk diffusion trajectories and real-time risk propagation paths. This allows risk propagation analysis to align with the current risk evolution status of the enterprise, thereby enhancing the continuous representation of the risk propagation process and improving the timeliness of enterprise risk propagation trend analysis.

[0114] This invention calculates the dynamic diffusion intensity of each risk object based on the real-time risk propagation path, and then adjusts the risk focus priority according to the dynamic diffusion intensity to form a current risk situation map of the enterprise. This allows the enterprise's risk situation to continuously reflect the changing process of risk propagation relationships. The current risk situation map of the enterprise can be updated synchronously with the risk propagation status, ensuring that the propagation relationships and propagation impacts between risk objects remain dynamically corresponding. This helps enterprises to identify changes in risk propagation trends in a timely manner and provides a situational basis for risk monitoring and risk early warning that is consistent with the current risk evolution status.

[0115] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A situational awareness system that integrates multi-source data, characterized in that, It includes a risk association snapshot module, a dynamic association module, a risk diffusion analysis module, a propagation path reconstruction module, and a risk situation output module: The risk association snapshot module is designed for the situational awareness process that integrates multi-source data. It collects enterprise operation data, supply fulfillment data, capital flow data, order execution data, and external event data. It calculates the frequency, duration, and interval of impact between risk objects according to a one-minute statistical window and generates a risk association snapshot for the corresponding statistical window. The dynamic association module reads the impact frequency, impact duration and impact interval from the risk association snapshot, performs association migration magnitude calculation on the risk objects corresponding to adjacent statistical windows, and remaps the risk objects whose association migration magnitude exceeds the set value to the new association position to construct a dynamic association map. The risk diffusion analysis module, based on the migration amplitude and new location of the association in the dynamic association map, counts the number of times the association location changes, tracks the risk diffusion trajectory according to the continuous migration direction, and marks the risk objects whose migration direction changes more than three times as propagation inflection nodes to obtain the risk diffusion trajectory. The propagation path reconstruction module obtains the propagation turning points, migration direction change frequency, and risk propagation span in the risk diffusion trajectory. It adjusts the order of risk impact according to the occurrence time of the propagation turning points, determines the real-time risk propagation path, and promotes the risk propagation relationship to be synchronized with the current risk evolution status. The risk situation output module calls upon the risk impact order, propagation turning points, and risk diffusion span in the real-time risk propagation path, calculates the dynamic diffusion intensity corresponding to each risk object, adjusts the risk attention priority according to the dynamic diffusion intensity, generates the current risk situation map of the enterprise, and continuously reflects the changing process of risk propagation relationships.

2. The situational awareness system that integrates multi-source data according to claim 1, characterized in that, The steps for generating a risk-related snapshot are as follows: Acquire enterprise operation data, supply fulfillment data, cash flow data, order execution data, and external event data to identify risk objects and establish corresponding relationships, and record the occurrence time of each risk object; Organize risk objects according to a unified time benchmark, statistically analyze the impact relationships between risk objects, obtain the frequency of impact, duration of impact, and interval of impact, and save the corresponding correlation characteristics; Based on the frequency of impact, duration of impact, and interval of impact, organize the statistical window identifier, statistical start time, statistical end time, risk object identifier, and associated risk object identifier to obtain the risk association snapshot of the corresponding statistical window; By combining the risk-related snapshots corresponding to each statistical window, and maintaining the continuous correspondence between the risk object identifier, the associated risk object identifier, and the statistical window order, the dynamic changes in the risk-related relationships are obtained, and risk-related snapshots are generated.

3. A situational awareness system integrating multi-source data according to claim 2, characterized in that, For each statistical window, compare the changes in the set of associated risk objects corresponding to the same risk object, record the newly added associations, the disappearance of associations, and the continuous associations, and associate the frequency of impact, duration of impact, and interval of impact to obtain the status of changes in risk associations.

4. A situational awareness system integrating multi-source data according to claim 2, characterized in that, The process of constructing a dynamic association graph is as follows: Read the risk association snapshots corresponding to adjacent statistical windows, extract the frequency of impact, duration of impact and interval of impact, establish a continuous correspondence relationship according to the risk object identifier, and obtain the risk association status corresponding to the continuous statistical windows; Based on the risk association status corresponding to the continuous statistical window, the association migration range is determined. For risk objects whose association migration range exceeds the set value, the original association position correspondence is terminated and mapped to a new association position. By utilizing the new associated locations to organize the relationships between all risk objects, we can obtain statistical window identifiers, risk object identifiers, associated risk object identifiers, migration magnitudes, new associated locations, and the time sequence corresponding to the associated locations, and construct a dynamic association map.

5. A situational awareness system integrating multi-source data according to claim 4, characterized in that, When the migration magnitude exceeds the set value, the original associated position correspondence of the risk object is terminated, and the risk object is mapped to a new associated position according to the latest associated status of the risk object in the current statistical window. The new associated position corresponds to the current associated risk object and the arrangement status of the associated relationship. The dynamic association map maintains the continuous change of risk association relationship.

6. A situational awareness system that integrates multi-source data according to claim 4, characterized in that, The process of obtaining the risk diffusion trajectory is as follows: Read the migration magnitude and new location of associations in the dynamic association map, establish a continuous time sequence correspondence according to the risk object identifier, and count the number of times the association location changes; Determine the continuous migration direction corresponding to the number of times the associated position changes, and maintain a consistent correspondence between the associated migration amplitude, the new associated position, and the continuous migration direction; Obtain the development process corresponding to continuous migration directions, organize the initial associated positions, continuous migration directions, number of changes in associated positions, associated migration magnitude, propagation order, and statistical window time order to obtain the risk diffusion trajectory; The number of consecutive changes in migration direction corresponding to the statistical risk diffusion trajectory is used to divide the propagation stage, and risk objects whose migration direction changes three or more times consecutively are marked as propagation inflection nodes. By combining the transmission turning points to continuously organize the risk diffusion trajectory, the transmission stages, transmission turning points and statistical window time sequence are obtained to obtain the risk diffusion trajectory.

7. A situational awareness system integrating multi-source data according to claim 6, characterized in that, The propagation phase corresponds to a development process in which the continuous migration direction remains consistent. When the migration direction changes, the number of changes in the migration direction is recorded, and a new propagation phase is entered. When the continuous changes in the migration direction reach the set conditions, the corresponding risk object is marked as a propagation turning point.

8. A situational awareness system that integrates multi-source data according to claim 6, characterized in that, The process of determining real-time risk propagation paths is as follows: Read the propagation turning points, continuous migration directions, propagation stages, and statistical window time sequence in the risk diffusion trajectory to obtain the frequency of change in migration direction and the span of risk diffusion; The propagation stages were reorganized according to the time of the propagation inflection point, the order of risk impact corresponding to each propagation stage was adjusted, and the frequency of change in migration direction and the span of risk diffusion were mapped to each propagation stage. By connecting each stage of the propagation using the adjusted risk impact order, and combining the propagation turning points, the frequency of changes in migration direction, and the span of risk diffusion, the real-time risk propagation path is determined. Record the changes in the propagation status corresponding to the newly added propagation turning points, adjust the order of risk impact in sync with the changes in the propagation stages, and update the real-time risk propagation path. The updated real-time risk propagation path is used to reorganize the risk propagation relationships, ensuring that the propagation turning points, propagation stages, risk impact order, migration direction change frequency, and risk diffusion span are continuously corresponded, and the real-time risk propagation path is determined.

9. A situational awareness system that integrates multi-source data according to claim 8, characterized in that, The real-time risk propagation path includes propagation inflection points, propagation stages, risk impact order, frequency of migration direction changes, risk diffusion span, propagation order, and statistical window time order. When a new propagation inflection point enters the propagation stage, the propagation stages are reorganized, the risk impact order is adjusted, and the real-time risk propagation path is updated.

10. A situational awareness system that integrates multi-source data according to claim 8, characterized in that, The process of generating the current risk profile of an enterprise is as follows: Read the order of risk impact, inflection points, risk spread span, propagation stages and statistical window time sequence in the real-time risk propagation path, establish a unified correspondence according to the risk object identifier, and obtain the current propagation status set of each risk object; By combining the current propagation status set of each risk object, the dynamic diffusion intensity is obtained, and the dynamic diffusion intensity is kept consistent with the order of risk impact, propagation turning points, and risk diffusion span. The dynamic diffusion intensity is used to reorganize the attention relationships among all risk objects, adjust the risk attention priority, and arrange the current attention order of risk objects; The adjusted risk focus priority is used to organize the current propagation status of all risk objects, obtain the risk object identification, risk focus priority, dynamic diffusion intensity, risk impact order, propagation turning point, propagation stage, risk diffusion span and statistical window time sequence, and generate the current risk situation map of the enterprise. The system continuously updates the enterprise's current risk situation map, including risk focus priorities, dynamic diffusion intensity, propagation stages, propagation turning points, and risk diffusion span. It also continuously records the changing process of risk propagation relationships and generates the enterprise's current risk situation map.

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