Business data detection method and device, computer program product and electronic equipment

Abstract

The present disclosure provides a service data detection method and device, a computer program product and an electronic device, and relates to the technical field of communication. The service data detection method comprises: in response to receiving a user service request with AI detection demand, querying a UPF supporting AI detection capability, determining a target UPF meeting the user service request from the UPF supporting AI detection capability; and sending access information corresponding to the user service request to the target UPF, so that the target UPF uses AI detection capability to detect user message data matched with the access information. The present disclosure intelligently detects user message data requiring AI detection based on the AI detection capability of the UPF, can improve the message detection capability of the communication network, realizes targeted differentiated strategy, and further improves the service experience of the user.

Description

Technical Field

[0001] This disclosure relates to the field of communication technology, and in particular to a service data detection method, a service data detection device, a computer program product, and an electronic device. Background Technology

[0002] In the policy management framework of mobile networks, the policy management function entity usually issues relevant policies to the policy execution function entity so that the policy control function entity can support the execution of corresponding policy control based on the detection results of service flow. Service flow detection is a key link in the process of realizing differentiated service management and control.

[0003] In related technologies, deep packet inspection is typically used to analyze packet headers to identify service characteristics during service flow inspection. However, with the increasing granularity of service inspection, the growing demand, and the increasing encryption capabilities of service flows, the difficulty of service flow inspection has significantly increased, making traditional deep packet inspection technology inadequate for meeting the communication needs of user services.

[0004] It should be noted that the information disclosed in the background section above is only used 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] This disclosure provides a service data detection method, service data detection device, computer program product, and electronic device to at least partially solve the problem in related technologies where the difficulty in detecting service flows makes it difficult to meet users' service communication needs.

[0006] According to a first aspect of this disclosure, a service data detection method is provided, applied to a first network element, the first network element providing a UPF selection decision service, the method comprising: responding to receiving a user service request with an artificial intelligence (AI) detection requirement, querying UPFs that support AI detection capabilities, determining a target UPF that matches the user service request from among the UPFs that support AI detection capabilities; sending access information corresponding to the user service request to the target UPF, so that the target UPF uses the AI ​​detection capability to detect user packet data that matches the access information.

[0007] According to a second aspect of this disclosure, a service data detection device is provided, applied to a first network element, the first network element providing a UPF selection decision service. The device includes: a UPF filtering module, configured to, in response to receiving a user service request with an AI detection requirement, query UPFs that support AI detection capabilities and determine a target UPF that matches the user service request from among the UPFs that support AI detection capabilities; and an access control module, configured to send access information corresponding to the user service request to the target UPF, so that the target UPF uses the AI ​​detection capability to detect user packet data that matches the access information.

[0008] According to a third aspect of this disclosure, a computer program product is provided, including a computer program that, when executed by a processor, implements the business data detection method of the first aspect described above and its possible implementations.

[0009] According to a fourth aspect of this disclosure, an electronic device is provided, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform the business data detection method of the first aspect and its possible implementations by executing the executable instructions.

[0010] The technical solution disclosed herein has the following beneficial effects:

[0011] In the aforementioned business data detection process, in response to receiving a user business request that requires AI (Artificial Intelligence) packet detection, the system queries UPFs (User Plane Functions) that support AI detection capabilities. From these UPFs, a target UPF matching the user business request is determined. Access information corresponding to the user business request is sent to the target UPF, enabling it to use AI detection capabilities to detect user packet data matching the access information. This disclosure, by responding to a user business request with AI detection requirements and querying UPFs that support AI detection capabilities to select a target UPF for intelligent detection of user packet data, not only achieves differentiated business management and control but also improves the packet detection capabilities of the communication network to a certain extent. This makes packet data detection more intelligent, thereby meeting the more complex communication needs of user businesses and improving the user's business experience. Furthermore, since the UPF is the network element in the core network primarily responsible for routing and forwarding user plane data packets, this disclosure's implementation of AI detection capabilities for intelligent packet detection on the UPF is based on the existing communication architecture and is relatively convenient to deploy. Attached Figure Description

[0012] Figure 1 This diagram illustrates a flowchart of a business data detection method in this exemplary embodiment;

[0013] Figure 2 This example illustrates an interactive flowchart of user interface path selection in this exemplary embodiment;

[0014] Figure 3 This example illustrates an interactive flowchart of a UPF-registered AI detection capability.

[0015] Figure 4 This example illustrates an interactive flowchart of a UPF updating AI detection capability in this exemplary embodiment;

[0016] Figure 5 This diagram illustrates a system architecture for a service data stream transmission in this exemplary embodiment.

[0017] Figure 6 This diagram illustrates a structural block diagram of a business data detection device according to an exemplary embodiment of the present invention.

[0018] Figure 7 An electronic device for implementing the above-described business data detection method is shown in this exemplary embodiment. Detailed Implementation

[0019] Exemplary embodiments of this disclosure will be described more fully below with reference to the accompanying drawings.

[0020] The accompanying drawings are schematic illustrations of this disclosure and are not necessarily drawn to scale. Some block diagrams shown in the drawings may be functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in hardware modules or integrated circuits, or in networks, processors, or microcontrollers. Implementations can be carried out in various forms and should not be construed as limited to the examples set forth herein. The features, structures, or characteristics described in this disclosure can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough description of embodiments of this disclosure. However, those skilled in the art will recognize that one or more specific details may be omitted when implementing the technical solutions of this disclosure, or other methods, components, apparatuses, steps, etc., may be used to replace one or more specific details.

[0021] In related technologies, deep packet inspection is typically used to analyze packet headers to identify service characteristics during service flow inspection. However, with the increasing granularity of service inspection, the growing demand, and the increasing encryption capabilities of service flows, the difficulty of service flow inspection has significantly increased, making traditional deep packet inspection technology inadequate for meeting the communication needs of user services.

[0022] In view of the above problems, the exemplary embodiments of this disclosure provide a service data detection method, a service data detection and processing device, a computer program product and an electronic device, which can be used in intelligent agent communication scenarios of mobile networks, increase network AI detection capabilities, improve the detection capability of services, and meet the forwarding quality requirements of high-demand and encrypted services.

[0023] In one alternative implementation, refer to Figure 1 The diagram illustrates a service data detection method applied to a first network element, which may include the following steps S110 to S120:

[0024] Step S110: In response to receiving a user business request that has an artificial intelligence (AI) detection requirement, query the UPF that supports AI detection capability, and determine the target UPF that matches the user business request from the UPF that supports AI detection capability.

[0025] Step S120: Send the access information corresponding to the user service request to the target UPF so that the target UPF can use AI detection capabilities to detect the user packet data that matches the access information.

[0026] Figure 1 The method described above, in response to a user service request requiring AI detection, queries for UPFs that support AI detection capabilities. A target UPF is then selected from these UPFs for intelligent detection of user packet data. This not only enables differentiated service management and control but also enhances the packet detection capabilities of the communication network, making packet data detection more intelligent and thus meeting the more complex communication needs of user services, ultimately improving the user experience. Furthermore, since UPFs are the network elements in the core network primarily responsible for routing and forwarding user plane data packets, equipping them with AI detection capabilities for intelligent packet detection is an implementation based on the existing communication architecture, making deployment relatively convenient.

[0027] It should be noted that the first network element in this disclosure is the decision-making network element for selecting a UPF, capable of providing UPF selection decision services. Taking the first network element as an SMF (Session Management Function) entity in the core network as an example, the SMF can respond to a user service request with AI detection requirements by querying UPFs that support AI detection capabilities, determining the target UPF that matches the user service request from among the UPFs that support AI detection capabilities, and sending the access information corresponding to the user service request to the target UPF, so that the target UPF can use AI detection capabilities to detect the user packet data based on the access information.

[0028] The following is about Figure 1 Each step in the process will be explained in detail.

[0029] In step S110, in response to receiving a user business request that has an artificial intelligence (AI) detection requirement, the system queries UPFs that support AI detection capabilities and determines the target UPF that matches the user business request from among the UPFs that support AI detection capabilities.

[0030] In this context, a service request refers to a request initiated by a user device to perform a specific service, which may include, but is not limited to, user basic information, user device information, network location information, requested service type, service-specific requirements, etc. This disclosure does not specifically limit this.

[0031] Among them, AI detection requirements refer to message detection requirements that need to rely on AI detection capabilities, and AI detection capabilities refer to the ability to intelligently analyze message data.

[0032] Optionally, AI detection requirements may include any one or more of the following: requirements for distinguishing key messages, requirements for analyzing message relationships, and requirements for identifying message quality. It should be noted that in practical applications, AI detection requirements may also include other types of message detection requirements that leverage AI detection capabilities; this disclosure does not specifically limit these.

[0033] For example, when a certain service requires that critical messages be transmitted first and that they be transmitted without loss, such services can be configured as services with message detection requirements.

[0034] Optionally, AI detection capabilities may include any one or more of the following: intelligent identification of key messages, intelligent analysis of message relationships, and intelligent identification of message quality. It should be noted that in practical applications, AI detection capabilities may also include other types of capabilities capable of intelligently analyzing message data; this disclosure does not specifically limit these.

[0035] There can be a corresponding relationship between AI detection capabilities and AI detection needs, so that AI detection capabilities can specifically meet various different AI detection needs.

[0036] Among them, the UPF is the core network element for user plane data processing, responsible for efficient packet forwarding, policy enforcement, and service awareness. UPFs supporting AI detection capabilities can register through AI detection and be discovered in the network, enabling the first network element to select a suitable UPF to process user packet data.

[0037] In one optional implementation, the above-mentioned response to receiving a user business request with an AI detection requirement, querying user plane function UPFs that support AI detection capabilities, and determining the target UPF that matches the user business request from the UPFs that support AI detection capabilities, can be achieved through the following steps: In response to receiving a user business request with an AI detection requirement, determining the type of AI detection requirement corresponding to the user business request, and querying UPFs that support AI detection capabilities that match the type of AI detection requirement, so as to further determine the target UPF that matches the user business request from the UPFs that support AI detection capabilities that match the type of AI detection requirement.

[0038] By querying UPFs that support AI detection capabilities that match the type of AI detection requirement for different AI detection needs, users can meet their diverse business processing needs with high accuracy.

[0039] In one optional implementation, the above-mentioned response to receiving a user service request with AI detection requirements, querying user plane function UPFs that support AI detection capabilities, and determining the target UPF that matches the user service request from the UPFs that support AI detection capabilities, can be achieved through the following steps: in response to receiving a user service request with AI detection requirements, querying a second network element for UPFs that support AI detection capabilities; the second network element providing AI detection capability management services for each UPF in the network; and determining the target UPF that matches the user service request from the UPFs that support AI detection capabilities.

[0040] The second network element can be a network element that provides AI detection capability management services for each UPF in the network. For example, the second network element can be an NRF (networking routing function) entity in the core network or a UDM (user data management) entity in the core network. This disclosure does not specifically limit it in this regard.

[0041] The NRF entity can provide UPF service registration and discovery functions, store the identifier of UPF instances and register network functions, and support SMF to filter available UPFs by conditions.

[0042] Among them, the UDM entity can provide user subscription data to influence the selection of UPF.

[0043] In some embodiments, in response to receiving a user service request that has an artificial intelligence (AI) detection requirement, the second network element may be queried for UPFs that support AI detection capabilities and meet other requirements of the user equipment, so as to further determine the target UPF from these UPFs.

[0044] Among these, other user equipment requirements refer to requirements other than AI detection requirements, such as network slice type and UPF location. Optionally, other user equipment requirements can be determined based on user service requests.

[0045] For example, taking the first network element as SMF and the second network element as NRF or UDM, SMF can query NRF or UDM for a list of UPFs that have AI detection capabilities and meet other requirements of user equipment. NRF or UDM will then provide SMF with a list of UPFs that meet these requirements, so that SMF can make a UPF selection decision.

[0046] By querying the second network element for UPFs that support AI detection capabilities, the target UPFs that are further identified can be detected by AI, which enriches the dimensions of user plane path selection and enhances the intelligence capabilities of the mobile network.

[0047] In some embodiments, the above-mentioned determination of the target UPF that meets the user's business request from UPFs that support AI detection capability can be achieved through the following steps: determining the target UPF that meets the user's business request from UPFs that support AI detection capability based on the user's business requirements determined by the user's business request and / or the load corresponding to the UPF that supports AI detection capability.

[0048] Among them, user equipment requirements may be some data transmission requirements information attached when the user equipment initiates a user service request, such as slice type, UPF location, etc. This disclosure does not specifically limit them.

[0049] By comprehensively considering factors such as user equipment requirements and UPF load, the optimal UPF can be selected, thereby providing personalized communication services for user equipment. It should be noted that in practical applications, other factors influencing UPF selection can also be considered, but this disclosure does not impose specific limitations on this.

[0050] Here, the target UPF refers to the key network element selected to handle the routing and forwarding of user plane data packets corresponding to the target user equipment, which is the user equipment that initiates the corresponding user service request. By supporting UPF path selection based on AI capabilities, AI capabilities are introduced into the mobile network, which can improve the detection capabilities and refined management of services.

[0051] In step S120, access information corresponding to the user service request is sent to the target UPF so that the target UPF can use AI detection capabilities to detect user packet data that matches the access information.

[0052] Access information refers to relevant information used to establish connections and transmit data during network communication or system connection processes.

[0053] Once the target UPF is determined, the access information corresponding to the user service request can be sent to the corresponding target UPF in order to establish and configure the data transmission path corresponding to the user service request.

[0054] In one optional implementation, after the first network element determines the target UPF, it can also send the UPF selection result, i.e., the target UPF, to other network elements participating in the data communication connection construction, so that service data can be correctly transmitted between the core network and user equipment. For example, the UPF selection result can be sent to the AMF (Access and Mobility Management Function) entity, so that the AMF can interact with the target UPF based on the UPF selection result returned by the SMF to configure user plane resources and prepare for data transmission from the user equipment.

[0055] In one optional implementation, the aforementioned sending of access information corresponding to a user service request to the target UPF, enabling the target UPF to use AI detection capabilities to detect user packet data matching the access information, can be achieved through the following steps: sending access information corresponding to a user service request to the target UPF, so that a PDN (Public Data Network) connection is established between the target UPF and the user equipment corresponding to the access information, wherein the PDN connection is used to transmit user packet data corresponding to the access information, and the target UPF can use AI detection capabilities to detect packets after receiving the user packet data corresponding to the access information.

[0056] After receiving user packet data corresponding to the access information, the target UPF can complete the packet detection task by invoking the corresponding AI detection capabilities. For example, it can invoke the key packet intelligent recognition capability to detect key packets in the user packet data.

[0057] By introducing AI technology into mobile networks to detect complex services, the requirements for differentiated forwarding of services have been enhanced.

[0058] Optionally, AI detection capabilities can be built through the following steps: collecting data and creating models for services in various network environments, performing model matching analysis on services through AI model matching capabilities, and continuously iterating and updating the corresponding models through reinforcement learning algorithms to effectively improve the recognition accuracy of various services and achieve intelligent experience assurance for different services and users.

[0059] Taking the first network element as SMF and the second network element as NRF or UDM as an example, such as Figure 2 As shown, a user interface path selection interaction flowchart is provided, which may include the following steps:

[0060] Step S201: The UE sends a user service request with AI detection requirements to the SMF;

[0061] In step S202, upon receiving a user service request that requires AI detection, the SMF queries the NRF or UDM for a list of UPFs that support AI detection capabilities and meet other UE requirements.

[0062] Step S203: The NRF or UDM returns a list of UPFs that support AI detection capabilities and meet other UE requirements to the SMF;

[0063] Step S204: The SMF, considering factors such as UE requirements and UPF load, selects a target UPF from a list of UPFs that support AI detection capabilities and meet other UE requirements.

[0064] In step S205, the SMF returns the UPF selection result to the AMF and notifies the target UPF of the access information so that a PDN connection can be established between the target UPF and the UE.

[0065] Step S206: After receiving user message data, the target UPF invokes AI detection capabilities for intelligent detection.

[0066] In this context, UE stands for User Equipment, which can be a user terminal such as a computer, mobile phone, or wearable device. This disclosure does not impose any specific limitations on it.

[0067] Figure 2 The steps shown demonstrate that by introducing the ability to detect complex services using AI technology into the mobile network, the mobile communication network's ability to detect services can be improved, enabling targeted and differentiated strategies, thereby optimizing the network and enhancing the service experience.

[0068] In one optional implementation, the first UPF in the network that has not registered its AI detection capability registers its AI detection capability by sending an AI detection capability registration request to the third network element, so that the third network element stores the AI ​​detection capability registration information of the first UPF; the third network element provides capability registration services.

[0069] The third network element can be a network element in the core network that provides UPF service registration and discovery functions, such as an NRF. It should be noted that the third network element and the second network element in this disclosure can be the same network element or different network elements, and this disclosure does not make specific limitations in this regard.

[0070] The AI ​​detection capability registration request refers to the AI ​​detection capability registration request initiated by the first UPF to the third network element. It can carry AI detection capability registration information, such as a registration file containing the first UPF's AI detection capabilities. The third network element can store the first UPF's registration information, i.e., the first UPF's registration file, to support AI-based detection.

[0071] Taking the NRF as an example of a third network element, the first UPF can be a UPF in the network that has not registered its AI detection capabilities. It can register its AI detection capabilities by sending an AI detection capability registration request to the third network element. Supporting UPFs to register their own AI capabilities in the NRF can assist the SMF in selecting AI capabilities.

[0072] Taking the third network element as NRF as an example, such as Figure 3 As shown, an interactive flowchart for registering AI detection capabilities using a UPF is provided, which may include the following steps:

[0073] Step S301: The first UPF sends a registration request carrying AI detection capability information to the NRF to register its AI detection capability with the NRF;

[0074] Step S302: The NRF stores the registration information of the first UPF that supports AI detection capabilities;

[0075] In step S303, after the NRF successfully registers the AI ​​detection capability of the first UPF, it returns a registration response to the first UPF.

[0076] By registering UPF's AI detection capabilities in NRF to support user plane path selection based on AI detection capabilities, the intelligence of the network can be increased.

[0077] For example, during the first UPF's registration with the NRF, the AI ​​detection capability registration request can carry relevant AI detection capability information for AI detection capability registration. The format of this AI detection capability information can be shown in the information cell format in Table 1 below.

[0078] Table 1

[0079]

[0080] Here, "array(string)" indicates that the data type is a string array; P (position) is used to indicate whether the corresponding field is optional or required. When P (position) is "0", it means that the corresponding field is optional; "1..N" represents a range, with a lower limit of 1 and an upper limit of N, where N is an integer. A base of 1..N means that the number of occurrences of the corresponding field can be any integer from 1 to N. It should be noted that in practical applications, information elements can be adaptively adjusted according to communication needs, such as deleting, adding, or modifying elements in fields. This disclosure does not impose specific limitations on this.

[0081] Optionally, based on the TS29.510 protocol, the UPF's info element can be extended to carry an AI detection capability identifier to indicate the UPF's support for AI. The info element refers to a unit containing specific information within the relevant protocol message.

[0082] In one optional implementation, the second UPF, which has already registered its AI detection capability in the network, updates its AI detection capability registration information by sending an AI detection capability update request to the third network element.

[0083] The AI ​​detection capability update request refers to the AI ​​detection capability update request initiated by the second UPF to the third network element. It can carry updated AI detection capabilities, such as an updated registration file containing the AI ​​detection capabilities of the second UPF. The third network element locally updates the registration information of the second UPF stored therein, i.e., the registration file of the second UPF, to support the change in AI detection capabilities.

[0084] Taking the third network element as an example, the second UPF can be a UPF that has registered AI detection capabilities in the network. It can change its AI detection capabilities by sending an AI detection capability update request to the third network element.

[0085] Taking the third network element as NRF as an example, such as Figure 4 As shown, an interactive flowchart for updating AI detection capabilities using UPF is provided, which may include the following steps:

[0086] Step S401: The second UPF sends a registration update request to the NRF to support AI detection capabilities, and changes the AI ​​detection capabilities to the NRF.

[0087] Step S402: NRF updates the registration information of the second UPF to support AI detection capabilities;

[0088] In step S403, after the NRF successfully updates the AI ​​detection capability of the second UPF, it returns an update response to the second UPF.

[0089] By updating the AI ​​detection capabilities of UPF in NRF, the flexibility of the network can be increased to support flexible changes to the AI ​​detection capabilities of UPF in the network.

[0090] Taking wearable devices as an example, such as user equipment Figure 5 The diagram illustrates a system architecture for business data stream transmission. Wearable devices can perform related sensing and business processing. Their control data requires deterministic, high-priority transmission. When a wearable device accesses the network, if the SMF detects that the wearable device has an AI detection requirement for its business stream, it can request a list of UPFs supporting AI detection capabilities from the NRF or UDM. The NRF or UDM returns a list of UPFs supporting AI detection capabilities to the SMF, such as UPF1 and UPF2. Based on the UPF location and other needs of the user corresponding to the wearable device, the SMF can further select a UPF supporting AI detection capabilities as a forwarding node for that user, such as UPF1, to enable data communication between the wearable device and the business server. This allows for the detection of the user's business data stream during data communication and provides differentiated service assurance.

[0091] Exemplary embodiments of this disclosure also provide a service data detection device applied to a first network element, the first network element providing a User Plane Function (UPF) selection decision service. (See reference...) Figure 6 As shown, the business data detection device 600 may include the following program modules:

[0092] UPF filtering module 610 is used to respond to a user business request that has an artificial intelligence (AI) detection requirement, query UPFs that support AI detection capabilities, and determine the target UPF that meets the user business request from the UPFs that support AI detection capabilities.

[0093] The access control module 620 is used to send access information corresponding to user service requests to the target UPF, so that the target UPF can use AI detection capabilities to detect user packet data that matches the access information.

[0094] In an optional implementation, based on the aforementioned scheme, the UPF screening module 610 can be configured to: in response to receiving a user service request that has an artificial intelligence (AI) detection requirement, query the second network element for UPFs that support AI detection capabilities; the second network element provides AI detection capability management services for each UPF in the network; and determine the target UPF that meets the user service request from the UPFs that support AI detection capabilities.

[0095] In an optional implementation, based on the aforementioned scheme, the UPF screening module 610 may include a target UPF determination module, used to determine a target UPF that meets the user's business request from UPFs that support AI detection capabilities. The target UPF determination module may be configured to: determine a target UPF that meets the user's business request from UPFs that support AI detection capabilities based on the user equipment requirements determined by the user's business request and / or the load corresponding to the UPF that supports AI detection capabilities.

[0096] In an optional implementation, based on the aforementioned scheme, the access control module 620 can be configured to: send access information corresponding to the user service request to the target UPF, so that a public data network (PDN) connection is established between the target UPF and the user equipment corresponding to the access information, wherein the PDN connection is used to transmit user packet data corresponding to the access information, and the target UPF uses AI detection capabilities to perform packet detection after receiving the user packet data corresponding to the access information.

[0097] In one optional implementation, based on the aforementioned scheme, the AI ​​detection requirements include any one or more of the following: the requirement to distinguish key messages, the requirement to analyze message relationships, and the requirement to identify message quality; the AI ​​detection capabilities include any one or more of the following: the ability to intelligently identify key messages, the ability to intelligently analyze message relationships, and the ability to intelligently identify message quality.

[0098] In one optional implementation, based on the aforementioned scheme, the first UPF in the network that has not registered its AI detection capability registers its AI detection capability by sending an AI detection capability registration request to the third network element, so that the third network element stores the AI ​​detection capability registration information of the first UPF; the third network element provides capability registration services.

[0099] In one optional implementation, based on the aforementioned scheme, the second UPF, which has already registered its AI detection capability in the network, updates its AI detection capability registration information by sending an AI detection capability update request to the third network element.

[0100] The specific details of each part of the aforementioned business data detection device 600 have been described in detail in the method section of the implementation plan. Any undisclosed details can be found in the implementation plan of the method section, and therefore will not be repeated here.

[0101] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to exemplary embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0102] An exemplary embodiment of this disclosure also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the above-described business data detection method.

[0103] In one embodiment, the computer program product can be a tangible product containing a computer program, such as a computer-readable storage medium storing the computer program. The readable storage medium can be a storage medium based on electrical, magnetic, optical, electromagnetic, infrared, or other signals, including but not limited to: random access memory (RAM), read-only memory (ROM), magnetic tape, floppy disk, flash memory, hard disk drive (HDD), solid-state drive (SSD), etc. For example, the computer program product can be implemented as a non-volatile storage medium storing the computer program, such as read-only memory, NAND flash memory, etc.

[0104] In one implementation, the computer program product can be an intangible product containing a computer program. For example, the computer program product can be implemented as a virtual digital product, such as an executable file, installation package, or other digital file storing the computer program.

[0105] Computer program code can be written in one or more programming languages. Examples of programming languages ​​include C, Java, and C++. Program code can execute entirely on the user's computing device, partially on the user's computing device, or as a standalone software package. It can also execute partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, such as a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via an internet connection provided by a mobile network operator).

[0106] Computer programs can be carried or transmitted via signals such as electricity, magnetism, light, electromagnetic radiation, and infrared rays. Electronic devices can convert signals carrying computer programs into digital signals, thereby running the computer programs. When a computer program runs on an electronic device, its code causes the electronic device to execute (more specifically, its processor) the method steps of various exemplary embodiments of this disclosure, such as the methods described above, which include the following steps:

[0107] In response to receiving a user business request that requires AI detection, query the user plane function UPF that supports AI detection capabilities, and determine the target UPF that matches the user business request from the UPF that supports AI detection capabilities;

[0108] Send the access information corresponding to the user service request to the target UPF so that the target UPF can use AI detection capabilities to detect the user packet data that matches the access information.

[0109] In an optional implementation, based on the aforementioned scheme, the above-mentioned response to receiving a user service request with AI detection requirements, querying user plane function UPFs that support AI detection capabilities, and determining the target UPF that matches the user service request from the UPFs that support AI detection capabilities, can be achieved through the following steps: in response to receiving a user service request with AI detection requirements, querying the second network element for UPFs that support AI detection capabilities; the second network element providing AI detection capability management services for each UPF in the network; and determining the target UPF that matches the user service request from the UPFs that support AI detection capabilities.

[0110] In an optional implementation, based on the aforementioned scheme, the determination of the target UPF that meets the user's business request from the UPFs that support AI detection capabilities can be achieved through the following steps: determining the target UPF that meets the user's business request from the UPFs that support AI detection capabilities based on the user equipment requirements determined by the user's business request and / or the load corresponding to the UPFs that support AI detection capabilities.

[0111] In an optional implementation, based on the aforementioned scheme, the above-mentioned sending of access information corresponding to the user service request to the target UPF, so that the target UPF can use AI detection capabilities to detect user packet data matching the access information, can be achieved through the following steps: sending access information corresponding to the user service request to the target UPF, so that a public data network (PDN) connection is established between the target UPF and the user equipment corresponding to the access information, wherein the PDN connection is used to transmit user packet data corresponding to the access information, and the target UPF uses AI detection capabilities to detect the packet after receiving the user packet data corresponding to the access information.

[0112] In one optional implementation, based on the aforementioned scheme, the AI ​​detection requirements include any one or more of the following: the requirement to distinguish key messages, the requirement to analyze message relationships, and the requirement to identify message quality; the AI ​​detection capabilities include any one or more of the following: the ability to intelligently identify key messages, the ability to intelligently analyze message relationships, and the ability to intelligently identify message quality.

[0113] In one optional implementation, based on the aforementioned scheme, the first UPF in the network that has not registered its AI detection capability registers its AI detection capability by sending an AI detection capability registration request to the third network element, so that the third network element stores the AI ​​detection capability registration information of the first UPF; the third network element provides capability registration services.

[0114] In one optional implementation, based on the aforementioned scheme, the second UPF, which has already registered its AI detection capability in the network, updates its AI detection capability registration information by sending an AI detection capability update request to the third network element.

[0115] In the aforementioned business data detection process, in response to user service requests requiring AI detection, the system queries for UPFs that support AI detection capabilities. This allows for the selection of a target UPF from among these supporters for intelligent detection of user packet data. This not only enables differentiated business management and control but also enhances the packet detection capabilities of the communication network, making packet data detection more intelligent and thus meeting the more complex communication needs of user services, ultimately improving the user experience. Furthermore, since UPFs are the network elements in the core network primarily responsible for routing and forwarding user plane data packets, equipping them with AI detection capabilities for intelligent packet detection is an implementation based on the existing communication architecture, making deployment relatively convenient.

[0116] An exemplary embodiment of this disclosure also provides an electronic device capable of implementing the above-described business data detection method. The electronic device may include a processor and a memory. The memory stores executable instructions of the processor, such as program code. The processor executes the executable instructions to perform the method of this exemplary embodiment. Furthermore, the electronic device may also include a display for displaying a graphical user interface.

[0117] The following is for reference. Figure 7 The electronic device is illustrated by way of a general-purpose computing device. It should be understood that... Figure 7 The electronic device 700 shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments disclosed herein.

[0118] like Figure 7 As shown, the electronic device 700 may include: a processor 710, a memory 720, a bus 730, an I / O (input / output) interface 740, a network adapter 750, and a display 760.

[0119] The memory 720 may include volatile memory, such as RAM 721 and cache unit 722, and may also include non-volatile memory, such as ROM 723. The memory 720 may also include one or more program modules 724, including but not limited to: an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. For example, program module 724 may include the modules described above.

[0120] The processor 710 may include one or more processing units, such as an AP (Application Processor), a modem processor, a GPU (Graphics Processing Unit), an ISP (Image Signal Processor), a controller, an encoder, a decoder, a DSP (Digital Signal Processor), a baseband processor, and / or an NPU (Neural-Network Processing Unit).

[0121] The processor 710 can be used to execute executable instructions stored in the memory 720, such as performing any one or more method steps in this exemplary embodiment.

[0122] For example, processor 710 may perform the following steps:

[0123] In response to receiving a user business request that requires AI detection, query the user plane function UPF that supports AI detection capabilities, and determine the target UPF that matches the user business request from the UPF that supports AI detection capabilities;

[0124] Send the access information corresponding to the user service request to the target UPF so that the target UPF can use AI detection capabilities to detect the user packet data that matches the access information.

[0125] In an optional implementation, based on the aforementioned scheme, the above-mentioned response to receiving a user service request with AI detection requirements, querying user plane function UPFs that support AI detection capabilities, and determining the target UPF that matches the user service request from the UPFs that support AI detection capabilities, can be achieved through the following steps: in response to receiving a user service request with AI detection requirements, querying the second network element for UPFs that support AI detection capabilities; the second network element providing AI detection capability management services for each UPF in the network; and determining the target UPF that matches the user service request from the UPFs that support AI detection capabilities.

[0126] In an optional implementation, based on the aforementioned scheme, the determination of the target UPF that meets the user's business request from the UPFs that support AI detection capabilities can be achieved through the following steps: determining the target UPF that meets the user's business request from the UPFs that support AI detection capabilities based on the user equipment requirements determined by the user's business request and / or the load corresponding to the UPFs that support AI detection capabilities.

[0127] In an optional implementation, based on the aforementioned scheme, the above-mentioned sending of access information corresponding to the user service request to the target UPF, so that the target UPF can use AI detection capabilities to detect user packet data matching the access information, can be achieved through the following steps: sending access information corresponding to the user service request to the target UPF, so that a public data network (PDN) connection is established between the target UPF and the user equipment corresponding to the access information, wherein the PDN connection is used to transmit user packet data corresponding to the access information, and the target UPF uses AI detection capabilities to detect the packet after receiving the user packet data corresponding to the access information.

[0128] In one optional implementation, based on the aforementioned scheme, the AI ​​detection requirements include any one or more of the following: the requirement to distinguish key messages, the requirement to analyze message relationships, and the requirement to identify message quality; the AI ​​detection capabilities include any one or more of the following: the ability to intelligently identify key messages, the ability to intelligently analyze message relationships, and the ability to intelligently identify message quality.

[0129] In one optional implementation, based on the aforementioned scheme, the first UPF in the network that has not registered its AI detection capability registers its AI detection capability by sending an AI detection capability registration request to the third network element, so that the third network element stores the AI ​​detection capability registration information of the first UPF; the third network element provides capability registration services.

[0130] In one optional implementation, based on the aforementioned scheme, the second UPF, which has already registered its AI detection capability in the network, updates its AI detection capability registration information by sending an AI detection capability update request to the third network element.

[0131] In the aforementioned business data detection process, in response to user service requests requiring AI detection, the system queries for UPFs that support AI detection capabilities. This allows for the selection of a target UPF from among these supporters for intelligent detection of user packet data. This not only enables differentiated business management and control but also enhances the packet detection capabilities of the communication network, making packet data detection more intelligent and thus meeting the more complex communication needs of user services, ultimately improving the user experience. Furthermore, since UPFs are the network elements in the core network primarily responsible for routing and forwarding user plane data packets, equipping them with AI detection capabilities for intelligent packet detection is an implementation based on the existing communication architecture, making deployment relatively convenient.

[0132] Electronic device 700 can communicate with one or more external devices 800 (such as keyboard, mouse, external controller, etc.) through I / O interface 740.

[0133] Electronic device 700 can communicate with one or more networks via network adapter 750. For example, network adapter 750 can provide mobile communication solutions such as 3G / 4G / 5G, or wireless communication solutions such as wireless LAN, Bluetooth, and near-field communication. Network adapter 750 can communicate with other modules of electronic device 700 via bus 730.

[0134] Electronic device 700 can display a graphical user interface, etc., via display 760.

[0135] although Figure 7 As not shown in the diagram, other hardware and / or software modules may also be configured in the electronic device 700, including but not limited to: a display, microcode, device driver, redundant processor, external disk drive array, RAID (Redundant Arrays of Independent Disks) system, tape drive, and data backup storage system.

[0136] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to exemplary embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0137] Those skilled in the art will understand that various aspects of this disclosure can be implemented as systems, methods, or program products. Therefore, various aspects of this disclosure can be embodied in entirely hardware implementations, entirely software implementations (including firmware, microcode, etc.), or implementations combining hardware and software aspects, collectively referred to herein as “circuit,” “module,” or “system.” Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the claims.

[0138] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is defined only by the appended claims.

Claims

1. A business data detection method, characterized in that, Applied to a first network element, which provides a User Plane Function (UPF) selection decision service, the method includes: In response to receiving a user service request that requires AI detection, the system queries for UPFs that support AI detection capabilities and determines a target UPF that matches the user service request from among the UPFs that support AI detection capabilities; the AI ​​detection requirement refers to the message detection requirement that utilizes AI detection capabilities, and the AI ​​detection capability refers to the ability to intelligently analyze message data; the service is an encrypted service. The target UPF sends the access information corresponding to the user service request to the target UPF, so that the target UPF can use the AI ​​detection capability to detect the user packet data that matches the access information.

2. The method according to claim 1, characterized in that, The step of responding to a user's business request that requires AI detection by querying UPFs that support AI detection capabilities and determining a target UPF that matches the user's business request from among the UPFs that support AI detection capabilities includes: In response to receiving a user service request that requires AI detection, the system queries the second network element for UPFs that support AI detection capabilities; the second network element provides AI detection capability management services for each UPF in the network. The target UPF that matches the user's business request is determined from the UPFs that support AI detection capabilities.

3. The method according to claim 1 or 2, characterized in that, The step of determining the target UPF that matches the user's business request from UPFs that support AI detection capabilities includes: Based on the user equipment requirements determined by the user service request and / or the load corresponding to the UPF that supports AI detection capability, a target UPF that meets the user service request is determined from the UPFs that support AI detection capability.

4. The method according to claim 1, characterized in that, Sending the access information corresponding to the user service request to the target UPF, so that the target UPF can use the AI ​​detection capability to detect user packet data that matches the access information, includes: The target UPF sends access information corresponding to the user service request to the target UPF so that a public data network (PDN) connection is established between the target UPF and the user equipment corresponding to the access information. The PDN connection is used to transmit user packet data corresponding to the access information. After receiving the user packet data corresponding to the access information, the target UPF uses the AI ​​detection capability to perform packet detection.

5. The method according to claim 1, characterized in that, The AI ​​detection requirements include any one or more of the following: distinguishing key messages, analyzing message relationships, and identifying message quality. The AI ​​detection capabilities include any one or more of the following: intelligent identification of key messages, intelligent analysis of message relationships, and intelligent identification of message quality.

6. The method according to claim 1, characterized in that, The first UPF in the network that has not registered its AI detection capability registers its AI detection capability by sending an AI detection capability registration request to a third network element, so that the third network element stores the AI ​​detection capability registration information of the first UPF. The third network element provides capability registration services.

7. The method according to claim 6, characterized in that, The second UPF, which has already registered its AI detection capabilities in the network, updates its AI detection capability registration information by sending an AI detection capability update request to the third network element.

8. A business data detection device, characterized in that, Applied to a first network element, which provides User Plane Function (UPF) selection decision service, the device includes: The UPF filtering module is used to respond to a user business request that has an artificial intelligence (AI) detection requirement, query UPFs that support AI detection capabilities, and determine the target UPF that matches the user business request from the UPFs that support AI detection capabilities; the AI ​​detection requirement refers to the message detection requirement that uses AI detection capabilities, and the AI ​​detection capability refers to the ability to intelligently analyze message data; the business is an encrypted business. The access control module is used to send access information corresponding to the user service request to the target UPF, so that the target UPF can use the AI ​​detection capability to detect user packet data that matches the access information.

9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method described in any one of claims 1 to 7.

10. An electronic device, characterized in that, include: processor; as well as Memory for storing the executable instructions of the processor; The processor is configured to execute the method of any one of claims 1 to 7 by executing the executable instructions.

Images