Account behavior determination method and apparatus, computer device, readable storage medium, and program product

Abstract

The present application relates to the technical field of computers, and relates to an account behavior determination method and apparatus, a computer device, a computer-readable storage medium, and a computer program product, which can improve the accuracy of account behavior identification. The method comprises: acquiring gateway interaction data corresponding to a gateway of a gateway deployment entity, and device location data of a device account, the gateway interaction data describing interactions between the device account and the gateway; determining a gateway physical location of the gateway; on the basis of the gateway physical location and the device location data, determining a first account behavior corresponding to the device account returning to or departing from the gateway deployment entity, and, on the basis of the gateway interaction data, determining a second account behavior corresponding to the device account returning to or departing from the gateway deployment entity; and on the basis of the first account behavior and the second account behavior, determining a trusted account behavior of the device account with respect to the gateway deployment entity.

Description

Methods, apparatus, computer equipment, readable storage media, and program products for determining account behavior Technical Field

[0001] This application relates to the field of computer technology, and in particular to a method, apparatus, computer device, computer-readable storage medium, and computer program product for determining account behavior. Background Technology

[0002] With the rapid development of IoT and big data technologies, the amount of account behavior data generated has increased dramatically, and the types of data have become increasingly diverse.

[0003] In related technologies, account behavior can be analyzed using data provided by a specific data source. However, the inventors found in practice that the accuracy of account behavior analysis results obtained through this method is poor, and the accuracy of account behavior identification still needs to be improved. Summary of the Invention

[0004] Therefore, it is necessary to provide a method, apparatus, computer device, computer-readable storage medium, and computer program product for determining account behavior in response to the above-mentioned technical problems.

[0005] Firstly, this application provides a method for determining account behavior, including:

[0006] Obtain the gateway interaction data corresponding to the gateway of the gateway deployment object, and the device location data of the device account; the gateway interaction data describes the interaction between the device account and the gateway;

[0007] Determine the physical location of the gateway;

[0008] Based on the gateway's physical location and the device's location data, determine a first account behavior of the device account returning to or leaving the gateway deployment object; and based on the gateway interaction data, determine a second account behavior of the device account returning to or leaving the gateway deployment object.

[0009] Based on the first account behavior and the second account behavior, the trusted account behavior of the device account for the gateway deployment object is determined.

[0010] In one embodiment, determining the gateway's physical location includes:

[0011] The device's stopping location is determined based on the device location data; the device's stopping location is a location where the stopping time and number of stops meet preset stopping conditions.

[0012] Based on the device location data and the gateway interaction data, the gateway interaction location of the device account is determined; the gateway interaction location is the location of the device account when the device account interacts with the gateway.

[0013] When the gateway interaction location matches the device's location, the gateway's physical location is determined based on the device's location.

[0014] In one embodiment, determining the gateway's physical location includes:

[0015] Based on the device location data and the gateway interaction data, multiple gateway interaction locations of the device account are determined; the gateway interaction location is the location of the device account when the device account interacts with the gateway.

[0016] If the number of the multiple gateway interaction locations is greater than a threshold and the multiple gateway interaction locations match, then the gateway's physical location is determined based on the multiple gateway interaction locations.

[0017] In one embodiment, determining the first account behavior of the device account returning to or leaving the gateway deployment object based on the gateway physical location and the device location data includes:

[0018] Based on the gateway's physical location and the device's location data, determine the change in distance between the device account and the gateway's physical location;

[0019] If, based on the distance change, it is determined that the device account leaves the physical location of the gateway by a preset distance and then returns to the physical location of the gateway, then the first account behavior of the device account returning to the gateway deployment object is determined;

[0020] If, based on the distance change, it is determined that the device account has moved a preset distance from the physical location of the gateway, then the first account behavior of the device account leaving the gateway deployment object is determined.

[0021] In one embodiment, determining the distance change between the device account and the physical location of the gateway based on the gateway physical location and the device location data includes:

[0022] If it is determined from the gateway interaction data that the device account performs an online operation on the gateway, the online time corresponding to the online operation and the return time of the last time the device account returned to the gateway deployment object are determined.

[0023] Based on the device location data between the time of the action and the time of the online event, and the physical location of the gateway, a first distance change between the device account and the physical location of the gateway is determined; the first distance change is used to determine whether the device account has performed a first account action of returning to the gateway deployment object;

[0024] If it is determined from the gateway interaction data that the device account performs a shutdown operation on the gateway, the shutdown time corresponding to the shutdown operation is determined;

[0025] Based on the device location data within a preset time after the offline time, and the physical location of the gateway, a second distance change between the device account and the physical location of the gateway is determined; the second distance change is used to determine whether the device account has engaged in a first account behavior of leaving the gateway deployment object.

[0026] In one embodiment, determining the second account behavior of the device account returning to or leaving the gateway deployment object based on the gateway interaction data includes:

[0027] If, based on the gateway interaction data, it is determined that the device account performs an online operation on the gateway, and the device account maintains the online state for a preset time threshold, then it is determined that the device account returns the second account behavior of the gateway deployment object.

[0028] If, based on the gateway interaction data, it is determined that the device account performs an offline operation on the gateway, and the device account remains offline for a preset time threshold, then the second departure behavior of the device account leaving the gateway deployment object is determined.

[0029] Secondly, this application also provides an account behavior determination device, comprising:

[0030] The multi-source data acquisition module is used to acquire gateway interaction data corresponding to the gateway of the gateway deployment object, as well as device location data of the device account; the gateway interaction data describes the interaction between the device account and the gateway;

[0031] A gateway location determination module is used to determine the physical location of the gateway.

[0032] The behavior analysis module is used to determine, based on the physical location of the gateway and the location data of the device, a first account behavior of the device account returning to or leaving the gateway deployment object, and a second account behavior of the device account returning to or leaving the gateway deployment object based on the gateway interaction data.

[0033] A trusted behavior determination module is used to determine the trusted account behavior of the device account for the gateway deployment object based on the first account behavior and the second account behavior.

[0034] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0035] Obtain the gateway interaction data corresponding to the gateway of the gateway deployment object, and the device location data of the device account; the gateway interaction data describes the interaction between the device account and the gateway;

[0036] Determine the physical location of the gateway;

[0037] Based on the gateway's physical location and the device's location data, determine a first account behavior of the device account returning to or leaving the gateway deployment object; and based on the gateway interaction data, determine a second account behavior of the device account returning to or leaving the gateway deployment object.

[0038] Based on the first account behavior and the second account behavior, the trusted account behavior of the device account for the gateway deployment object is determined.

[0039] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0040] Obtain the gateway interaction data corresponding to the gateway of the gateway deployment object, and the device location data of the device account; the gateway interaction data describes the interaction between the device account and the gateway;

[0041] Determine the physical location of the gateway;

[0042] Based on the gateway's physical location and the device's location data, determine a first account behavior of the device account returning to or leaving the gateway deployment object; and based on the gateway interaction data, determine a second account behavior of the device account returning to or leaving the gateway deployment object.

[0043] Based on the first account behavior and the second account behavior, the trusted account behavior of the device account for the gateway deployment object is determined.

[0044] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0045] Obtain the gateway interaction data corresponding to the gateway of the gateway deployment object, and the device location data of the device account; the gateway interaction data describes the interaction between the device account and the gateway;

[0046] Determine the physical location of the gateway;

[0047] Based on the gateway's physical location and the device's location data, determine a first account behavior of the device account returning to or leaving the gateway deployment object; and based on the gateway interaction data, determine a second account behavior of the device account returning to or leaving the gateway deployment object.

[0048] Based on the first account behavior and the second account behavior, the trusted account behavior of the device account for the gateway deployment object is determined.

[0049] The aforementioned method, apparatus, computer device, computer-readable storage medium, and computer program product for determining account behavior can acquire gateway interaction data corresponding to the gateway of the gateway deployment object, as well as device location data of the device account. The gateway interaction data describes the interaction between the device account and the gateway. Then, the physical location of the gateway is determined, and based on the gateway physical location and device location data, a first account behavior (returning to or leaving the gateway deployment object) is determined, and a second account behavior (returning to or leaving the gateway deployment object) is determined based on the gateway interaction data. Furthermore, based on the first and second account behaviors, the trusted account behavior of the device account towards the gateway deployment object is determined. Compared to related technologies that identify account behavior based on a single data source, this method combines the gateway interaction data of the gateway deployment object and the device location data of the device account to determine the first and second account behaviors respectively. Then, by integrating the first and second account behaviors, the trusted account behavior is determined. This breaks the limitations of a single data source, helps correct the account behavior identification error of a single data source, and also enables the complementarity and enhancement of multi-source data during the account behavior identification process, effectively improving the accuracy of the account behavior identification results. Attached Figure Description

[0050] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0051] Figure 1 is a flowchart illustrating an account behavior determination method in one embodiment;

[0052] Figure 2 is a flowchart illustrating another method for determining account behavior in one embodiment;

[0053] Figure 3a is a schematic diagram of a method for recognizing homecoming behavior in one embodiment;

[0054] Figure 3b is a schematic diagram of one embodiment for identifying away-from-home behavior;

[0055] Figure 4 is a structural block diagram of an account behavior determination device in one embodiment;

[0056] Figure 5 is an internal structure diagram of a computer device in one embodiment. Detailed Implementation

[0057] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0058] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0059] To enable those skilled in the art to better understand this application, the relevant technologies are first introduced below.

[0060] With the rapid development of IoT and big data technologies, the amount of account behavior data generated has increased dramatically, and the types of data have become increasingly diverse.

[0061] In related technologies, account behavior can be analyzed using data provided by a data source. In some possible implementations, one approach is to utilize only base station location data, analyzing the account's movement trajectories at different times and locations to obtain account behavior analysis results. Another approach is to collect and analyze network usage data, which can include device connectivity, data traffic usage, application access records, etc., reflecting the account's network activity habits.

[0062] However, the inventors found in practice that while the former (data on account movement) can capture the characteristics of account movement, its analysis results are often rather crude due to the lack of data related to indoor activities, making it difficult to accurately identify the account's true intentions and preferences. The latter (data on account behavior) is limited to fixed network usage scenarios and has limitations in analyzing overall account behavior patterns. It is evident that related technologies often rely on a single data source when identifying account behavior, resulting in one-sided analysis results that cannot fully reflect the account's true behavior, and the accuracy of account behavior identification still needs improvement.

[0063] Therefore, it is necessary to provide a method, apparatus, computer device, computer-readable storage medium, and computer program product for determining account behavior in response to the above-mentioned technical problems.

[0064] In one embodiment, as shown in Figure 1, a method for determining account behavior is provided. This embodiment illustrates the application of this method to a server. It is understood that this method can also be applied to a terminal, or to a system including both a terminal and a server, and is implemented through interaction between the terminal and the server. In this embodiment, the method includes the following steps:

[0065] S101, obtain the gateway interaction data corresponding to the gateway of the gateway deployment object, and the device location data of the device account; the gateway interaction data describes the interaction between the device account and the gateway.

[0066] In this context, the gateway deployment object can be a location where a gateway is deployed and has a specific physical location. In some examples, the gateway deployment object can be classified according to the type of location. For example, a specific home or enterprise can be used as the gateway deployment object, such as Company A located at a certain address.

[0067] A device account can be an account corresponding to a terminal device. In some examples, the device account can be determined based on the device identifier, or the account logged in on the terminal device can be used as the device account.

[0068] In this step, on the one hand, gateway interaction data corresponding to the gateway of the gateway deployment object can be obtained. This gateway interaction data can characterize the interaction between the device account and the gateway. Specifically, it can record the type of interaction operation between the device account and the gateway, as well as the time when the interaction occurred. On the other hand, device location data can be obtained. This device location data can characterize the location of the device account. It can also record the location of the device account and its corresponding time. In some exemplary embodiments, the device location data can include historical location data collected in the past (i.e., existing device location data), or it can include current location data collected in real time (i.e., incremental device location data).

[0069] In some embodiments, if the gateway deployment target is a home, the gateway of the deployment target can be a home gateway. As an access device for smart homes and broadband, the home gateway not only supports basic network access functions but also integrates various intelligent service interfaces such as smart home control and data transmission. It can collect home network usage data, such as gateway interaction data, which helps provide important evidence for data analysis. Device location data for a device account can be determined based on base station positioning data. Base station positioning data refers to the approximate location information of the device calculated by combining signal interaction data (such as signal strength, transmission delay, etc.) between the device and the base station with a preset specific algorithm. It should be emphasized that the gateway interaction data and device location data involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of related data must comply with relevant regulations.

[0070] In an exemplary embodiment, gateway interaction data and base station location data for the gateway deployment object can be collected from the gateway and communication network of the gateway deployment object, respectively. Then, data preprocessing is performed on the gateway interaction data and base station location data. This preprocessing may include one or more operations such as cleaning, noise reduction, and timestamp alignment to ensure data quality. For example, gateway interaction data can be used to obtain gateway device online / offline data. Frequent online / offline actions may occur due to network fluctuations, signal fluctuations, terminal reconnection, or other scenarios. Such data is useless for determining whether a device is returning to or leaving the gateway deployment object and can be filtered out. Similarly, for base station location data, the approximate location information of the device can be calculated using a specific algorithm based on signal interaction between the device and the base station (such as signal strength and transmission delay). The calculated location information may have varying degrees of deviation; data that deviates within a short period and then reverts, but whose deviation exceeds a reasonable range, is filtered out. Furthermore, a data quality assessment mechanism can be introduced to evaluate the quality of the preprocessed data, ensuring the smooth progress of the fusion process. Through the above data preprocessing and data quality control assessment, the impact of erroneous data on the analysis results is effectively reduced, improving the efficiency and accuracy of data fusion. Compared with existing technologies, this application can better address data quality issues and lay a solid foundation for subsequent user behavior analysis.

[0071] S102, Determine the physical location of the gateway.

[0072] In a practical implementation, the physical location of the gateway can be obtained. In some exemplary embodiments, the physical location of the gateway can be recorded when setting up the gateway for the gateway deployment object.

[0073] In other embodiments, if the gateway's physical location is not pre-recorded, it can be determined based on gateway interaction data and device location data. Specifically, device location data can record the location of the device account, and gateway interaction data can record the interaction between the device account and the gateway, such as whether the device account interacted with the gateway. By associating device location data and gateway interaction data, the device location of the device account when interacting with the gateway can be determined, thereby determining the physical location of the gateway, i.e., the gateway's physical location.

[0074] In some embodiments, device location data records the location of the device account and the time when the device account is at that location. Gateway interaction data can record the interaction between the device account and the gateway and the time when the device account interacts with the gateway. Then, the device location data and gateway interaction data can be aligned by time to determine the location of the device account when the device account interacts with the gateway, and the gateway's physical location can be obtained based on that location.

[0075] S103, based on the gateway physical location and device location data, determine the first account behavior of the device account returning to or leaving the gateway deployment object, and based on the gateway interaction data, determine the second account behavior of the device account returning to or leaving the gateway deployment object.

[0076] In practical implementation, gateways are often set within a preset range of the gateway deployment object; for example, a home gateway for a household would be deployed at the location of the household. Therefore, in this step, spatial location can be introduced to perform correlation analysis on the account behavior of device accounts leaving or returning to the gateway deployment object. Simultaneously, based on the gateway's physical location and device location data, the account behavior of the device account returning to or leaving the gateway deployment object is determined. For ease of distinction, the account behavior obtained from the analysis of the gateway's physical location and device location data is referred to as the first account behavior. In some embodiments, the device account location can be determined based on the device location data, and then the first account behavior of the device account returning to or leaving the gateway deployment object can be identified based on the distance between the device location data and the gateway's physical location.

[0077] On the other hand, the interaction between the device account and the gateway can also be used to predict the device account's subsequent account behavior towards the gateway deployment object. For example, when a device account goes offline, it may be leaving the gateway deployment object; when a device account goes online, it may be returning to the gateway deployment object. Based on this, the account behavior of the device account returning to or leaving the gateway deployment object can be determined according to the gateway interaction data. For ease of distinction, this account behavior is referred to as the second account behavior.

[0078] S104, Based on the first account behavior and the second account behavior, determine the trusted account behavior of the device account for the gateway deployment object.

[0079] Since the first account behavior and the second account behavior are determined based on different data source analyses, after obtaining the first account behavior and the second account behavior, it is possible to identify whether the account has engaged in account behavior targeting the gateway deployment object based on the first account behavior and the second account behavior. For example, the first account behavior and the second account behavior determined based on different data sources can be integrated to obtain the account behavior identification result of the device account targeting the gateway deployment object. For ease of distinction, the account behavior determined based on the first account behavior and the second account behavior in this application is referred to as trusted account behavior.

[0080] In this embodiment, by combining device location data and gateway interaction data, first account behavior and second account behavior are identified respectively. Then, by combining the first and second account behaviors, trusted account behavior is determined. This helps to overcome the limitations of a single data source, correct data errors from a single data source, eliminate useless data from a single data source, and achieve complementarity and enhancement of multi-source data. Simultaneously, the integration of gateway interaction data and device location data can more comprehensively reflect the device account's behavioral activities in different dimensions (such as network activity, movement trajectory, etc.), providing a rich data source for accurately identifying account behavior. In some embodiments, after obtaining trusted account behavior, feature extraction can be performed based on various trusted account behaviors of the device account to obtain the behavioral characteristics of the device account.

[0081] In some exemplary embodiments, in step S104, determining the trusted account behavior of the device account for the gateway deployment object based on the first account behavior and the second account behavior may include:

[0082] If the first account behavior and the second account behavior match, the first account behavior and / or the second account behavior are identified as trusted account behaviors of the device account for the gateway deployment object.

[0083] In practical applications, when the first account behavior and the second account behavior are the same or similar, at least one of the first account behavior and the second account behavior can be identified as a trusted account behavior of the device account towards the gateway deployment object. For example, when the first account behavior is an account behavior that returns to the gateway deployment object, and the second account behavior is an account behavior that returns to the gateway deployment object, it can be determined that the device account has performed a trusted account behavior that returns to the gateway deployment object.

[0084] In other embodiments, if the first account behavior and the second account behavior do not match, it can be determined that there is an anomaly in the account behavior discrimination result. The first account behavior and the second account behavior can be further analyzed to determine the trustworthy account behavior. For example, the trustworthiness of the first account behavior and the second account behavior can be further determined based on device location data or other data sources. From the first account behavior and the second account behavior, the account behavior with higher trustworthiness is determined as the trustworthy account behavior.

[0085] For example, the interaction between the device account and the gateway can be used as a trigger for determining specific account behavior. When the following conditions are met simultaneously, it is identified as the corresponding trusted account behavior: ① The specific behavior is reflected in the gateway data; ② The specific behavior is reflected in the location data; ③ The reflection in both types of data can eliminate their respective useless data or correct errors in the data.

[0086] Compared to related technologies, this application can effectively solve the problem of data anomalies in special scenarios caused by a single data source, such as noise in gateway online / offline data caused by power-saving strategies of terminal devices, and device offline behavior that may not be captured when multiple routers automatically switch under a single gateway. By complementing multi-source data through this application, the first account behavior and the second account behavior are determined, and then the final trusted account behavior is determined by combining the first account behavior and the second account behavior, which improves the comprehensiveness and accuracy of account behavior analysis.

[0087] The aforementioned method for determining account behavior can obtain gateway interaction data corresponding to the gateway of the gateway deployment object, and device location data of the device account. The gateway interaction data describes the interaction between the device account and the gateway. Then, the physical location of the gateway is determined, and based on the gateway physical location and device location data, a first account behavior of the device account returning to or leaving the gateway deployment object is determined. Furthermore, based on the gateway interaction data, a second account behavior of the device account returning to or leaving the gateway deployment object is determined. Finally, based on the first and second account behaviors, the trusted account behavior of the device account towards the gateway deployment object is determined. Compared to related technologies that identify account behavior based on a single data source, this embodiment combines the gateway interaction data of the gateway deployment object and the device location data of the device account to determine the first and second account behaviors respectively. Then, by integrating the first and second account behaviors, the trusted account behavior is determined. This breaks the limitation of a single data source, helps to correct the account behavior identification error of a single data source, and also enables the complementarity and enhancement of multi-source data during the account behavior identification process, effectively improving the accuracy of the account behavior identification results.

[0088] Furthermore, while a large amount of behavioral data (such as device location data obtained from mobile communication and gateway interaction data obtained from gateway deployment) has been accumulated in the process of analyzing account behavior, differences in data format, storage method, and processing technology have created data silos between different dimensions. Related technologies that use a single data source to determine account behavior struggle to efficiently and accurately integrate data from different sources, resulting in insufficient exploration of the correlations between data. Simultaneously, analyzing network usage data or location data in isolation limits the analysis results to specific scenarios, making it difficult to conduct comprehensive cross-scenario analysis of account behavior. This embodiment effectively addresses the problems of single data sources and insufficient data fusion in related technologies for identifying account behavior. By combining gateway interaction data and device location data to determine reliable account behavior, it achieves efficient and accurate fusion of multi-source data, breaking down data silos and enabling cross-domain, cross-scenario, and multi-dimensional data fusion and account behavior analysis. This improves the comprehensiveness and accuracy of account behavior analysis and provides a comprehensive and rich data foundation for subsequent account behavior analysis.

[0089] In one embodiment, determining the physical location of the gateway in step S102 may include the following steps:

[0090] The device's dwell location is determined based on the device location data; the device's dwell location is the location where the dwell time and number of dwell times meet the preset dwell conditions; the gateway interaction location of the device account is determined based on the device location data and the gateway interaction data; the gateway interaction location is the location of the device account when it interacts with the gateway; when the gateway interaction location matches the device's dwell location, the gateway's physical location is determined based on the device's dwell location.

[0091] In practical applications, device location data can record the location of a device account and the corresponding time, such as recording that the device account was at location A at 10:20. In this embodiment, by analyzing the device location data, locations visited by the device account, with dwell time and number of dwell times meeting preset dwell conditions can be determined, and these locations can then be used as the device's dwell locations.

[0092] In some exemplary embodiments, the GeoHash algorithm can be used to aggregate the various locations contained in the device location data, and the locations in the aggregation results that have accumulated more than a number threshold or whose dwell time exceeds a preset duration threshold are identified as the device dwell locations.

[0093] On the other hand, the gateway interaction location of a device account can be determined based on device location data and gateway interaction data. For example, if an interaction between a device account and the gateway is detected, the location of the device account at this time can be obtained based on the device account data and determined as the gateway interaction location.

[0094] Furthermore, when the gateway interaction location matches the device's location, the gateway's physical location can be determined based on the device's location. For example, when the gateway interaction location matches the device's location, the gateway's location can be used as the corresponding gateway's physical location.

[0095] For example, based on the configuration rules of the GeoHash algorithm, the location code length can be pre-set to 6, and the offset tolerance to x kilometers. Different locations within x kilometers can use the same location code, while locations exceeding x kilometers are represented by different location codes. Then, device location data is aggregated using the GeoHash algorithm. Locations exceeding a certain number or duration in the aggregation results are identified as stops. Subsequently, the interaction between the terminal device and the gateway can be used as a trigger for the gateway's physical location determination executor. When a device account performs an interaction with the gateway, the device account's location data is collected, and it is determined whether the current location data is the same as any stop location. This determination is made by using the GeoHash algorithm to check if they belong to the same coding area (e.g., setting the code length to 7 and the offset tolerance to y kilometers) or by checking if the latitude and longitude distance exceeds an incentive threshold, combined with appropriate weights to determine the gateway's physical location.

[0096] In this embodiment, the device's location is determined based on the device location data. Then, when the gateway interaction location matches the device's location, the gateway's physical location is determined based on the device's location. This method can deeply integrate gateway interaction data and device location data in both time and space dimensions, and can accurately infer the gateway's physical location. Compared with other complex and costly gateway positioning technologies, this method fully integrates device location data, is relatively low-cost and easy to implement, and provides an efficient and economical method for determining the gateway location.

[0097] In one embodiment, determining the physical location of the gateway in step S102 may include the following steps:

[0098] Based on device location data and gateway interaction data, determine multiple gateway interaction locations for the device account; the gateway interaction location is the location of the device account when it interacts with the gateway; if the number of multiple gateway interaction locations is greater than the number threshold and the multiple gateway interaction locations match, then determine the gateway's physical location based on the multiple gateway interaction locations.

[0099] In practical applications, multiple gateway interaction locations of a device account can be determined based on device location data and gateway interaction data. These multiple gateway interaction locations correspond to the same interaction gateway. The specific method for determining the gateway interaction location can be found in the aforementioned embodiments, and will not be elaborated here.

[0100] After obtaining multiple gateway interaction locations, the number of these locations can be counted, and it can be determined whether the locations match. For example, it can be determined whether the distance between multiple gateway interaction locations is less than a threshold. If so, a match can be determined; otherwise, a mismatch can be determined.

[0101] If the number of multiple gateway interaction locations exceeds a threshold and the locations of these interaction locations match, the gateway's physical location can be determined based on these interaction locations. For example, one of the interaction locations can be selected as the gateway's physical location, or the average value of the interaction locations can be used to determine the physical location. Alternatively, the interaction action between the terminal device and the gateway can be used as a trigger for the gateway physical location determination actuator. When an interaction action occurs, location data is collected as the gateway interaction location, and the gateway's physical location is determined based on the multiple interaction locations and their corresponding weights.

[0102] In this embodiment, the physical location of the gateway is determined by the interaction of multiple gateways through location matching. This allows for the comprehensive assessment of information from various aspects, effectively reducing errors and uncertainties, and more accurately pinpointing the actual physical location of the gateway. At the same time, it avoids positioning deviations caused by errors or interference from a single gateway interaction location, thereby improving the overall reliability of determining the physical location of the gateway and reducing the error rate.

[0103] In one embodiment, in step S103, determining the first account behavior of a device account returning to or leaving the gateway deployment object based on the gateway physical location and device location data may include the following steps:

[0104] Based on the gateway physical location and device location data, determine the distance change between the device account and the gateway physical location; if the distance change determines that the device account leaves the gateway physical location to reach a preset distance and then returns to the gateway physical location, then determine the first account behavior of the device account returning to the gateway deployment object; if the distance change determines that the device account leaves the gateway physical location to reach a preset distance, then determine the first account behavior of the device account leaving the gateway deployment object.

[0105] Since device location data can record the location of a device account at multiple points in time and reflect the movement trajectory of the device account, after determining the physical location of the gateway, this embodiment can determine the distance change between the device account and the physical location of the gateway based on the physical location of the gateway and the device location data.

[0106] Furthermore, the account behavior of a device account returning to or leaving the gateway deployment object can be determined based on this distance change. Specifically, if the distance change indicates that the device account leaves the gateway's physical location by a preset distance and then returns to the gateway's physical location, the first account behavior is determined as returning to the gateway deployment object. Conversely, if the distance change indicates that the device account leaves the gateway's physical location by a preset distance, the first account behavior is determined as leaving the gateway deployment object. For example, with known gateway physical location and device location data preprocessed, if the device leaves the gateway's physical location by more than a distance L1 and then returns to the gateway's physical location, it is determined as returning to the gateway deployment object; if the device leaves the gateway's physical location by more than a distance L2, it is determined as leaving the gateway deployment object, where L1 is greater than L2.

[0107] In this embodiment, by determining the distance change between the device account and the gateway physical location based on the gateway physical location data and device location data, the behavior pattern of the device account can be accurately judged based on the distance change between the device location data and the gateway physical location during the process of identifying account behavior from multiple sources, thereby improving the accuracy of identifying the first account behavior.

[0108] In one embodiment, determining the distance change between a device account and the gateway's physical location based on gateway physical location and device location data may include the following steps:

[0109] When it is determined from gateway interaction data that a device account performed an online operation on the gateway, the online time corresponding to the online operation and the return time of the device account's last return to the gateway deployment object are determined. Based on the device location data between the time of the action and the online time, and the physical location of the gateway, a first distance change between the device account and the physical location of the gateway is determined. The first distance change is used to determine whether the device account has performed a first account action of returning to the gateway deployment object. When it is determined from gateway interaction data that a device account performed an offline operation on the gateway, the offline time corresponding to the offline operation is determined. Based on the device location data within a preset time after the offline time, and the physical location of the gateway, a second distance change between the device account and the physical location of the gateway is determined. The second distance change is used to determine whether the device account has performed a first account action of leaving the gateway deployment object.

[0110] In specific implementation, the distance change situation can include at least one of a first distance change situation and a second distance change situation. The first distance change situation is used to determine whether the device account has performed a first account action of returning to the gateway deployment object, and the second distance change situation is used to determine whether the device account has performed a first account action of leaving the gateway deployment object. In this embodiment, at least one of the first and second distance change situations can be triggered based on the type of interaction operation between the device account and the gateway.

[0111] Specifically, when it is determined from the gateway interaction data that the device account is performing an online operation on the gateway, it is predicted that the device account may return to the gateway deployment object. In order to more accurately identify the account behavior and avoid misjudging the noise in the online operation data and the automatic switching of multiple routers under a single gateway as the device account returning to the gateway deployment object, the online time corresponding to the online operation and the return time of the device account's last return to the gateway deployment object can be determined. Then, based on the device location data between the time of the behavior and the online time, as well as the physical location of the gateway, the first distance change between the device account and the physical location of the gateway can be determined.

[0112] On the other hand, if it is determined from the gateway interaction data that the device account has performed an offline operation on the gateway, it is predicted that the device account may leave the gateway deployment object. In order to more accurately identify the account behavior and avoid misjudging the noise of the offline operation data as the device account leaving the gateway deployment object, the offline time corresponding to the offline operation can be determined. Then, based on the device location data within a preset time after the offline time and the physical location of the gateway, the second distance change between the device account and the physical location of the gateway can be determined.

[0113] In this embodiment, device location data within a specific time period is extracted by triggering gateway interaction data. Then, based on the device location data within that specific time period, the first and second distance changes in space are determined. This enables deep fusion of gateway interaction data and device location data in both time and space dimensions, providing a reliable data foundation for the subsequent identification of the first account behavior.

[0114] In one embodiment, determining the second account behavior of a device account returning to or leaving the gateway deployment object based on gateway interaction data in step S103 may include the following steps:

[0115] If, based on gateway interaction data, it is determined that a device account performs an online operation on the gateway and maintains the online state for a preset time threshold, then the device account is determined to return to the gateway deployment object as a second account action. If, based on gateway interaction data, it is determined that a device account performs an offline operation on the gateway and maintains the offline state for a preset time threshold, then the device account is determined to leave the gateway deployment object as a second departure action.

[0116] In practice, the type of operation performed by the device at the gateway can be determined based on gateway interaction data. When an online operation is detected, the duration for which the device account remains online can be further determined based on gateway interaction data. If the device account remains online for a preset time threshold, it can be determined that the device account has performed a second account action by returning to the gateway deployment object. The online duration can be calculated from the moment of current online status or within a period prior to current online status. When an offline operation is detected, the duration for which the device account remains offline can be further determined based on gateway interaction data. If the device account remains online for a preset time threshold, it can be determined that the device account has performed a second account action by leaving the gateway deployment object.

[0117] For example, if a device account goes online at the gateway and does not go offline within a preset time period (this preset time may depend on gateway data collection errors and actual application scenario analysis; for example, a threshold of 15 minutes may be set), then the device account is determined to return to the gateway deployment object. If a device account goes offline at the gateway and does not go online within a preset time period in the future (this preset time may depend on gateway data collection errors and actual application scenario analysis; for example, a threshold of 15 minutes may be set), then the device account is determined to leave the gateway deployment object.

[0118] In this embodiment, by monitoring and judging the online and offline operations of device accounts on the gateway and the time for maintaining the corresponding state, different behavior patterns of device accounts can be accurately identified, and the behavior of device accounts returning to and leaving the gateway deployment object can be accurately distinguished.

[0119] To enable those skilled in the art to better understand the above steps, the embodiments of this application are illustrated below with some examples, but it should be understood that the embodiments of this application are not limited thereto.

[0120] In one example, as shown in Figure 2, the following steps may be included:

[0121] S201, obtain the gateway interaction data corresponding to the gateway of the gateway deployment object, and the device location data of the device account.

[0122] S202, determine the location of the equipment based on the equipment location data.

[0123] S203, determine the gateway interaction location of the device account based on the device location data and gateway interaction data; when the gateway interaction location matches the device's location, determine the gateway's physical location based on the device's location.

[0124] S204. Based on device location data and gateway interaction data, determine multiple gateway interaction locations of the device account; if the number of multiple gateway interaction locations is greater than the number threshold and the multiple gateway interaction locations match, then determine the gateway physical location based on the multiple gateway interaction locations.

[0125] S205, based on the gateway physical location and device location data, determine the change in distance between the device account and the gateway physical location.

[0126] S206, if it is determined based on the distance change that the device account leaves the gateway physical location by a preset distance and then returns to the gateway physical location, then the first account behavior of the device account returning to the gateway deployment object is determined; if it is determined based on the distance change that the device account leaves the gateway physical location by a preset distance, then the first account behavior of the device account leaving the gateway deployment object is determined.

[0127] S207, if based on the gateway interaction data, it is determined that the device account performs an online operation on the gateway and the device account maintains the online state for a preset time threshold, then the device account is determined to return the second account behavior to the gateway deployment object; if based on the gateway interaction data, it is determined that the device account performs an offline operation on the gateway and the device account maintains the offline state for a preset time threshold, then the device account is determined to leave the gateway deployment object as a second departure behavior.

[0128] S208, Based on the first account behavior and the second account behavior, determine the trusted account behavior of the device account for the gateway deployment object.

[0129] For example, as shown in Figure 3a, an example of judging device account home behavior is provided.

[0130] 1. Data collection: Obtain gateway interaction data and base station positioning data (i.e., device location data) from the home gateway.

[0131] 2. Data preprocessing: Perform preprocessing operations such as cleaning, noise reduction, and timestamp alignment on the collected data to ensure data quality.

[0132] 3. Data fusion:

[0133] (1) Feature-based fusion method for gateway physical location identification:

[0134] The device account's gateway online / offline actions, network requests, etc., are used as triggers for the gateway physical location determination actuator. When the above actions occur, the gateway location is identified if the following conditions are met:

[0135] ① By collecting location data at the moment of interaction between the device account and the gateway, geographical locations within a certain distance range (such as 0.05km) are identified as the same location.

[0136] ②When a certain amount of data is accumulated, the geographical location with the most hits is marked as the gateway location.

[0137] (2) Determining homecoming behavior based on feature fusion methods:

[0138] The gateway online action of the device account is used as the trigger for the home behavior determination executor. When the online action occurs, it is identified as home behavior if the following indicators are met:

[0139] ① Check if there has been any offline activity within a certain period of time (e.g., 15 minutes). If so, the process is considered a failure.

[0140] ② If the location data is more than a certain distance (e.g., 0.6km) from the last successful return-home action to the time of the current online action, then the return-home action is considered successful.

[0141] For example, as shown in Figure 3b, an example of judging device account away-from-home behavior is provided.

[0142] 1. Data collection: Obtain gateway interaction data and base station positioning data from the home gateway.

[0143] 2. Data preprocessing: Perform preprocessing operations such as cleaning, noise reduction, and timestamp alignment on the collected data to ensure data quality.

[0144] 3. Data fusion:

[0145] (1) Gateway physical location identification based on weighted average fusion method and feature-based fusion method:

[0146] The actions of the terminal device, such as gateway online / offline status and network requests, are used as triggers for the gateway physical location determination actuator. When the above actions occur and the following indicators are met, the gateway location is identified:

[0147] ①Location data is aggregated using the GeoHash algorithm (e.g., encoding length of 6, offset tolerance of 0.61km). The locations where the cumulative number of times exceeds a certain amount or duration are identified.

[0148] ② By collecting location data at the moment of interaction between the terminal device and the gateway, it is determined whether the current location data is the same location as any place of stay. The determination method is to use the GeoHash algorithm to determine whether it is the same coding area (e.g., coding length of 7, offset tolerance of 0.076km) or the latitude and longitude distance to determine whether it exceeds a certain distance (e.g., 0.05km). If so, the place of stay is marked as a possible location of the gateway, and the number of times is accumulated.

[0149] ③ When a certain amount of data is accumulated, the location with the most hits is marked as the physical location of the gateway.

[0150] (3) Feature-based fusion method for determining away-from-home behavior:

[0151] The gateway offline action of the terminal device is used as the trigger for the home return behavior determination executor;

[0152] The gateway online action of the terminal device is used as the terminator of the home return behavior determination executor.

[0153] When an action occurs and the following indicators are met simultaneously, it is identified as an absence from home:

[0154] ④ No online action will occur within a certain period of time (e.g., 15 minutes) after the offline action occurs.

[0155] By using cyclical delayed tasks, short-cycle detection is performed to achieve real-time analysis of behavior as much as possible.

[0156] ⑤ If, within a certain period of time (e.g., 15 minutes) after the offline action occurs, the location data is more than a certain distance (e.g., 0.1km) from the location of the gateway, then the act of leaving home is determined to have been completed.

[0157] Through the above processing, account behavior can be identified from multiple dimensions. During the identification process, by integrating home gateway interaction data and base station location data, account behavior can be reflected more comprehensively, providing a rich data source for in-depth analysis of user behavior. Simultaneously, it enhances security monitoring capabilities; through continuous monitoring and analysis of account behavior patterns, abnormal behavior can be detected in a timely manner, providing strong support for security monitoring and ensuring user information security. Furthermore, it promotes the effective utilization of data resources, facilitates cross-domain and cross-platform data sharing and integration, and drives the effective utilization and value mining of data resources, aligning with the development trend of the big data era.

[0158] In some exemplary embodiments, this application can be applied in the following scenarios:

[0159] (1) Smart Home and Security Field

[0160] With user authorization, the system uses gateway interaction data to determine the access status of home network devices, and combines this with base station location data to determine whether the relevant device account is at home, thus realizing intelligent security functions. When an unknown device is detected attempting to access the home network, the system uses the device account's location information to determine if it is an abnormal situation and triggers an alarm mechanism.

[0161] (2) Account Behavior Analysis

[0162] With user authorization, by analyzing gateway interaction data and base station location data, the daily activity patterns and travel habits of device accounts can be understood. This allows for the provision of security monitoring services to relevant family members, allowing them to monitor for any abnormalities in the user's daily activities.

[0163] (3) Location-sensitive smart home control

[0164] With user authorization, and by combining gateway interaction data and base station positioning data, remote control and automated scene settings for smart home devices can be achieved, enabling home devices to automatically adjust based on changes in the location of family members. For example, when the device account is detected leaving home, unnecessary electrical appliances in the home can be automatically turned off; when the device account is detected approaching the door, devices such as lights and air conditioners can be turned on in advance.

[0165] It is evident that this application has the following advantages and effects compared to related technologies:

[0166] 1. Improve data comprehensiveness and accuracy. Multi-source data fusion algorithms can integrate data from different sensors, devices, or algorithms, thereby providing more comprehensive and accurate information. This helps reduce information bias caused by errors from a single data source and improves data reliability. By fusing multiple types of data, the shortcomings of a single data source in terms of coverage and accuracy can be compensated for, enabling the system to obtain more comprehensive information and make more accurate decisions. Simultaneously, it can break down data barriers between different fields and platforms, achieving data sharing and integration, and promoting the effective utilization of data resources.

[0167] 2. Enhance system robustness. Multi-source data fusion reduces dependence on a single data source. Even if one data source fails, information from other data sources can still support the system, thereby improving system stability and robustness.

[0168] 3. Improve data quality. Data preprocessing improves data accuracy and completeness by removing noise, outliers, and missing values. This helps reduce errors in the modeling process and improves the accuracy and generalization ability of the model.

[0169] 4. Reduce computational complexity. Data preprocessing can normalize and reduce the dimensionality and complexity of the original data. This helps reduce the amount of computation and improve computational speed and efficiency.

[0170] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0171] Based on the same inventive concept, this application also provides an account behavior determination apparatus for implementing the account behavior determination method described above. The solution provided by this apparatus is similar to the implementation described in the above method; therefore, the specific limitations in one or more account behavior determination apparatus embodiments provided below can be found in the limitations of the account behavior determination method described above, and will not be repeated here.

[0172] In an exemplary embodiment, as shown in FIG4, an account behavior determination device is provided, comprising:

[0173] The multi-source data acquisition module 401 is used to acquire gateway interaction data corresponding to the gateway of the gateway deployment object, and device location data of the device account; the gateway interaction data describes the interaction between the device account and the gateway;

[0174] Gateway location determination module 402 is used to determine the physical location of the gateway;

[0175] The behavior analysis module 403 is used to determine a first account behavior of the device account returning to or leaving the gateway deployment object based on the gateway physical location and the device location data, and to determine a second account behavior of the device account returning to or leaving the gateway deployment object based on the gateway interaction data.

[0176] Trusted behavior determination module 404 is used to determine the trusted account behavior of the device account for the gateway deployment object based on the first account behavior and the second account behavior.

[0177] In one embodiment, the gateway location determination module 402 is configured to:

[0178] The device's stopping location is determined based on the device location data; the device's stopping location is a location where the stopping time and number of stops meet preset stopping conditions.

[0179] Based on the device location data and the gateway interaction data, the gateway interaction location of the device account is determined; the gateway interaction location is the location of the device account when the device account interacts with the gateway.

[0180] When the gateway interaction location matches the device's location, the gateway's physical location is determined based on the device's location.

[0181] In one embodiment, the gateway location determination module 402 is configured to:

[0182] Based on the device location data and the gateway interaction data, multiple gateway interaction locations of the device account are determined; the gateway interaction location is the location of the device account when the device account interacts with the gateway.

[0183] If the number of the multiple gateway interaction locations is greater than a threshold and the multiple gateway interaction locations match, then the gateway's physical location is determined based on the multiple gateway interaction locations.

[0184] In one embodiment, the behavior analysis module 403 is used for:

[0185] Based on the gateway's physical location and the device's location data, determine the change in distance between the device account and the gateway's physical location;

[0186] If, based on the distance change, it is determined that the device account leaves the physical location of the gateway by a preset distance and then returns to the physical location of the gateway, then the first account behavior of the device account returning to the gateway deployment object is determined;

[0187] If, based on the distance change, it is determined that the device account has moved a preset distance from the physical location of the gateway, then the first account behavior of the device account leaving the gateway deployment object is determined.

[0188] In one embodiment, the behavior analysis module 403 is used for:

[0189] If it is determined from the gateway interaction data that the device account performs an online operation on the gateway, the online time corresponding to the online operation and the return time of the last time the device account returned to the gateway deployment object are determined.

[0190] Based on the device location data between the time of the action and the time of the online event, and the physical location of the gateway, a first distance change between the device account and the physical location of the gateway is determined; the first distance change is used to determine whether the device account has performed a first account action of returning to the gateway deployment object;

[0191] If it is determined from the gateway interaction data that the device account performs a shutdown operation on the gateway, the shutdown time corresponding to the shutdown operation is determined;

[0192] Based on the device location data within a preset time after the offline time, and the physical location of the gateway, a second distance change between the device account and the physical location of the gateway is determined; the second distance change is used to determine whether the device account has engaged in a first account behavior of leaving the gateway deployment object.

[0193] In one embodiment, the behavior analysis module 403 is used for:

[0194] If, based on the gateway interaction data, it is determined that the device account performs an online operation on the gateway, and the device account maintains the online state for a preset time threshold, then it is determined that the device account returns the second account behavior of the gateway deployment object.

[0195] If, based on the gateway interaction data, it is determined that the device account performs an offline operation on the gateway, and the device account remains offline for a preset time threshold, then the second departure behavior of the device account leaving the gateway deployment object is determined.

[0196] The modules in the aforementioned account behavior determination device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can invoke and execute the operations corresponding to each module.

[0197] In an exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram is shown in Figure 5. The computer device includes a processor, memory, input / output interfaces (I / O), and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is connected to the system bus via the I / O interfaces. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes non-volatile storage media and internal memory. The non-volatile storage media stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device stores gateway interaction data and device location data. The I / O interfaces of the computer device are used for exchanging information between the processor and external devices. The communication interface of the computer device is used for communicating with external terminals via a network connection. When the computer program is executed by the processor, it implements an account behavior determination method.

[0198] Those skilled in the art will understand that the structure shown in Figure 5 is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or may combine certain components, or may have different component arrangements.

[0199] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0200] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps in the above method embodiments.

[0201] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0202] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0203] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0204] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0205] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for determining account behavior, characterized in that, The method includes: Obtain the gateway interaction data corresponding to the gateway of the gateway deployment object, and the device location data of the device account; the gateway interaction data describes the interaction between the device account and the gateway; Determine the physical location of the gateway; Based on the gateway's physical location and the device's location data, determine a first account behavior of the device account returning to or leaving the gateway deployment object; and based on the gateway interaction data, determine a second account behavior of the device account returning to or leaving the gateway deployment object. Based on the first account behavior and the second account behavior, the trusted account behavior of the device account for the gateway deployment object is determined.

2. The method according to claim 1, characterized in that, Determining the physical location of the gateway includes: The device's stopping location is determined based on the device location data; the device's stopping location is a location where the stopping time and number of stops meet preset stopping conditions. Based on the device location data and the gateway interaction data, the gateway interaction location of the device account is determined; the gateway interaction location is the location of the device account when the device account interacts with the gateway. When the gateway interaction location matches the device's location, the gateway's physical location is determined based on the device's location.

3. The method according to claim 1, characterized in that, Determining the physical location of the gateway includes: Based on the device location data and the gateway interaction data, multiple gateway interaction locations of the device account are determined; the gateway interaction location is the location of the device account when the device account interacts with the gateway. If the number of the multiple gateway interaction locations is greater than a threshold and the multiple gateway interaction locations match, then the gateway's physical location is determined based on the multiple gateway interaction locations.

4. The method according to claim 1, characterized in that, The step of determining the first account behavior of the device account returning to or leaving the gateway deployment object based on the gateway physical location and the device location data includes: Based on the gateway's physical location and the device's location data, determine the change in distance between the device account and the gateway's physical location; If, based on the distance change, it is determined that the device account leaves the physical location of the gateway by a preset distance and then returns to the physical location of the gateway, then the first account behavior of the device account returning to the gateway deployment object is determined; If, based on the distance change, it is determined that the device account has moved a preset distance from the physical location of the gateway, then the first account behavior of the device account leaving the gateway deployment object is determined.

5. The method according to claim 4, characterized in that, The step of determining the distance change between the device account and the physical location of the gateway based on the gateway's physical location and the device's location data includes: If it is determined from the gateway interaction data that the device account performs an online operation on the gateway, the online time corresponding to the online operation and the return time of the last time the device account returned to the gateway deployment object are determined. Based on the device location data between the time of the action and the time of the online event, and the physical location of the gateway, a first distance change between the device account and the physical location of the gateway is determined; the first distance change is used to determine whether the device account has performed a first account action of returning to the gateway deployment object; If it is determined from the gateway interaction data that the device account performs a shutdown operation on the gateway, the shutdown time corresponding to the shutdown operation is determined; Based on the device location data within a preset time after the offline time, and the physical location of the gateway, a second distance change between the device account and the physical location of the gateway is determined; the second distance change is used to determine whether the device account has engaged in a first account behavior of leaving the gateway deployment object.

6. The method according to any one of claims 1 to 5, characterized in that, The step of determining the second account behavior of the device account returning to or leaving the gateway deployment object based on the gateway interaction data includes: If, based on the gateway interaction data, it is determined that the device account performs an online operation on the gateway, and the device account maintains the online state for a preset time threshold, then it is determined that the device account returns the second account behavior of the gateway deployment object. If, based on the gateway interaction data, it is determined that the device account performs an offline operation on the gateway, and the device account remains offline for a preset time threshold, then the second departure behavior of the device account leaving the gateway deployment object is determined.

7. An account behavior determination device, characterized in that, The device includes: The multi-source data acquisition module is used to acquire gateway interaction data corresponding to the gateway of the gateway deployment object, as well as device location data of the device account; the gateway interaction data describes the interaction between the device account and the gateway; A gateway location determination module is used to determine the physical location of the gateway. The behavior analysis module is used to determine, based on the physical location of the gateway and the location data of the device, a first account behavior of the device account returning to or leaving the gateway deployment object, and a second account behavior of the device account returning to or leaving the gateway deployment object based on the gateway interaction data. A trusted behavior determination module is used to determine the trusted account behavior of the device account for the gateway deployment object based on the first account behavior and the second account behavior.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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