Call interception method and device, computer equipment and storage medium

Abstract

The invention relates to the technical field of telephone communication, in particular to a call interception method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring multi-modal data sent by a terminal for an interference number; performing feature extraction and fusion on the multi-modal data to obtain an interception instruction corresponding to the terminal; and determining an interception strategy for the interference number according to the interception instruction and historical call information of the interference number, and storing the interception strategy to a core network, so that the core network performs call interception for the interference number according to the interception strategy. According to the invention, an intelligent harassment interception scheme at a network side is realized, call interception aiming at the interference number is carried out under the condition of not depending on the terminal capability, and the interception convenience, interception accuracy and interception flexibility aiming at the interference number are improved.

Description

Technical Field

[0001] This application relates to the field of telephone communication technology, and in particular to a call interception method, apparatus, computer equipment, and storage medium. Background Technology

[0002] In the field of communications, terminals such as landline phones, mobile phones, and VoIP phones all face the problem of high-frequency harassing calls.

[0003] Existing technologies for intercepting interference numbers mainly employ two methods: local terminal interception and cloud database matching. However, existing interception methods cannot cover "low-capability terminals" such as old landlines and feature phones without caller ID functionality. Therefore, there is an urgent need for a method to intercept interference calls that does not rely on terminal capabilities. Summary of the Invention

[0004] Therefore, it is necessary to provide a call interception method, apparatus, computer device, and storage medium that can intercept calls without relying on terminal capabilities, in order to address the aforementioned technical problems.

[0005] Firstly, this application provides a call interception method. The method includes:

[0006] Acquire multimodal data sent by the terminal targeting the interfering number;

[0007] Feature extraction and fusion are performed on the multimodal data to obtain the interception command corresponding to the terminal;

[0008] Based on the interception command and the historical call information of the interference number, an interception strategy for the interference number is determined, and the interception strategy is stored in the core network so that the core network can intercept calls to the interference number according to the interception strategy.

[0009] In one embodiment, determining the interception strategy for the interfering number based on the interception instruction and the historical call information of the interfering number includes:

[0010] Based on the historical call information of the interfering number, determine the call frequency and call period of the interfering number;

[0011] Extract the instruction parameters from the interception instruction;

[0012] Based on the instruction parameters, the call frequency, and the call time period, a blocking strategy for the interference number is determined.

[0013] In one embodiment, determining the interception strategy for the interference number based on the instruction parameters, the call frequency, and the call period includes:

[0014] Based on the instruction parameters, the call frequency, and the call period, a risk assessment is performed on the interfering number to obtain the risk assessment level corresponding to the interfering number;

[0015] Based on the risk assessment level, a blocking strategy is determined for the interference number.

[0016] In one embodiment, the step of performing feature extraction and fusion on the multimodal data to obtain the interception command corresponding to the terminal includes:

[0017] Semantic features are extracted from the multimodal data to obtain semantic feature data;

[0018] The semantic feature data is fused to obtain the interception command corresponding to the terminal.

[0019] In one embodiment, the multimodal data includes at least one of: USSD unstructured supplemental data service code data, voice command data, and application settings data.

[0020] In one embodiment, determining the interception strategy for the interfering number based on the interception instruction and the historical call information of the interfering number includes:

[0021] The terminal is authenticated; wherein the authentication method includes at least one of SMS verification code verification, dynamic PIN personal identification number verification, and two-factor authentication.

[0022] Secondly, this application also provides a call interception device. The device includes:

[0023] The acquisition module is used to acquire multimodal data sent by the terminal targeting the interfering number;

[0024] The fusion module is used to extract and fuse features from the multimodal data to obtain the interception command corresponding to the terminal.

[0025] The determining module is configured to determine an interception strategy for the interfering number based on the interception instruction and the historical call information of the interfering number, and store the interception strategy in the core network so that the core network can intercept calls for the interfering number according to the interception strategy.

[0026] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to perform the following steps:

[0027] Acquire multimodal data sent by the terminal targeting the interfering number;

[0028] Feature extraction and fusion are performed on the multimodal data to obtain the interception command corresponding to the terminal;

[0029] Based on the interception command and the historical call information of the interference number, an interception strategy for the interference number is determined, and the interception strategy is stored in the core network so that the core network can intercept calls to the interference number according to the interception strategy.

[0030] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, performs the following steps:

[0031] Acquire multimodal data sent by the terminal targeting the interfering number;

[0032] Feature extraction and fusion are performed on the multimodal data to obtain the interception command corresponding to the terminal;

[0033] Based on the interception command and the historical call information of the interference number, an interception strategy for the interference number is determined, and the interception strategy is stored in the core network so that the core network can intercept calls to the interference number according to the interception strategy.

[0034] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, performs the following steps:

[0035] Acquire multimodal data sent by the terminal targeting the interfering number;

[0036] Feature extraction and fusion are performed on the multimodal data to obtain the interception command corresponding to the terminal;

[0037] Based on the interception command and the historical call information of the interference number, an interception strategy for the interference number is determined, and the interception strategy is stored in the core network so that the core network can intercept calls to the interference number according to the interception strategy.

[0038] The aforementioned call interception method, apparatus, computer equipment, and storage medium acquire multimodal data sent by the terminal targeting interference numbers, extract and fuse features from the multimodal data to obtain the corresponding interception command from the terminal, and then determine an interception strategy for the interference numbers based on the interception command and historical call information of the interference numbers, enabling the core network to intercept calls targeting the interference numbers according to the interception strategy. As can be seen from the above, this application, by acquiring multimodal data targeting interference numbers, achieves the acquisition of terminal interception requirements for interference numbers through various data interaction methods. Furthermore, by determining an interception strategy for interference numbers, the core network can intercept calls targeting the interference numbers according to the interception strategy, realizing an intelligent harassment interception scheme on the network side. This ensures call interception of interference numbers without relying on terminal capabilities, improving the convenience, accuracy, and flexibility of interception. Attached Figure Description

[0039] Figure 1 This application provides an application environment diagram for a call interception method according to an embodiment of the present application.

[0040] Figure 2 A flowchart illustrating a first call interception method is provided for embodiments of this application;

[0041] Figure 3 A flowchart illustrating a second call interception method is provided for embodiments of this application;

[0042] Figure 4 A flowchart illustrating a third call interception method is provided for embodiments of this application;

[0043] Figure 5 A flowchart illustrating a fourth call interception method is provided for embodiments of this application;

[0044] Figure 6 A flowchart illustrating a fifth call interception method is provided for embodiments of this application;

[0045] Figure 7 This application provides a schematic diagram of a call interception system according to an embodiment of the present application;

[0046] Figure 8 This application provides a structural block diagram of a call interception device according to an embodiment;

[0047] Figure 9 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0048] 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.

[0049] The call interception method provided in this application embodiment can be applied to, for example, Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104 or placed in the cloud or on other network servers. By acquiring multimodal data sent by the terminal targeting interfering numbers and performing feature extraction and fusion on the multimodal data, the corresponding interception command for the terminal is obtained. Then, based on the interception command and the historical call information of the interfering number, an interception strategy for the interfering number is determined, enabling the core network to intercept calls targeting the interfering number according to the interception strategy. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart vehicle devices, etc. Portable wearable devices can include smartwatches, smart bracelets, head-mounted devices, etc. Server 104 can be implemented using a standalone server or a server cluster composed of multiple servers.

[0050] In one embodiment, such as Figure 2 As shown, a call interception method is provided, which is applied to... Figure 1 Taking server 104 as an example, the following steps are included:

[0051] S201, Obtain multimodal data sent by the terminal targeting the interfering number.

[0052] It should be noted that multimodal data includes at least one of the following: USSD unstructured supplementary data business code data, voice command data, and application settings data.

[0053] In one embodiment of this application, a user can mark a jamming number by entering *#9394# on the terminal, thereby sending USSD data for the jamming number to the server that performs the call interception method, and thus realizing the operation of obtaining multimodal data sent by the terminal for the jamming number.

[0054] In another embodiment of this application, a user can input a voice command to the terminal (e.g., to block unknown calls every night), so that the terminal can generate voice command data based on the user's input voice command and send the voice command data to the server that executes the call blocking method, thereby realizing the operation of obtaining multimodal data sent by the terminal against the interference number.

[0055] In another embodiment of this application, a user can set interception data for interference numbers in the application corresponding to the terminal, so that the terminal can integrate the interception data set by the user in the application into application setting data and send the application setting data to the server that executes the call interception method, thereby realizing the operation of obtaining multimodal data sent by the terminal for interference numbers.

[0056] S202, feature extraction and fusion of multimodal data to obtain the corresponding interception command for the terminal.

[0057] It should be noted that when it is necessary to perform feature extraction and fusion on multimodal data to obtain the interception command corresponding to the terminal, the following may be included: extracting semantic features from multimodal data to obtain semantic feature data; and fusing features from the semantic feature data to obtain the interception command corresponding to the terminal.

[0058] S203: Based on the interception instruction and the historical call information of the interference number, determine the interception strategy for the interference number and store the interception strategy in the core network so that the core network can intercept calls for the interference number according to the interception strategy.

[0059] The blocking strategies may include, but are not limited to: strictly rejecting calls, providing voice or SMS prompts, and temporarily allowing access during specific time periods.

[0060] It should be noted that, in order to ensure the security of user communication, user information, interception commands and interception policies can be encrypted, and the encrypted data can be stored in the core network and the terminal. Both the core network and the terminal are equipped with storage devices, which can be local storage devices or cloud storage devices. No restrictions are placed on the type of storage device here.

[0061] To ensure that the core network can successfully intercept calls from interfering numbers according to the interception policy, the interception policy can be converted into a signaling format that the core network can recognize.

[0062] The aforementioned call interception method acquires multimodal data sent by the terminal targeting interference numbers, extracts and fuses features from the multimodal data to obtain the corresponding interception command from the terminal, and then determines an interception strategy for the interference numbers based on the interception command and historical call information of the interference numbers, enabling the core network to intercept calls targeting the interference numbers according to the interception strategy. As can be seen from the above, this application, by acquiring multimodal data targeting interference numbers, achieves the acquisition of terminal interception requirements for interference numbers through various data interaction methods. Furthermore, by determining an interception strategy for interference numbers, the core network can intercept calls targeting the interference numbers according to the interception strategy, realizing an intelligent harassment interception scheme on the network side. This ensures call interception of interference numbers without relying on terminal capabilities, improving the convenience, accuracy, and flexibility of interception.

[0063] In one embodiment, such as Figure 3 As shown, when it is necessary to determine the interception strategy for a jamming number based on the interception instruction and the historical call information of the jamming number, the following may be included:

[0064] S301, Based on the historical call information of the interfering number, determine the call frequency and call period of the interfering number.

[0065] The historical call information may include historical call records of the terminal receiving calls from interfering numbers, specifically including the historical call time and duration of the interfering number.

[0066] In one embodiment of this application, the call frequency and call period of the interfering number are determined by obtaining the historical call information of the interfering number, and by counting the call time of the interfering number and the call frequency of the interfering number within a preset period.

[0067] S302, extract the instruction parameters from the interception instruction.

[0068] It should be noted that the instruction parameters refer to the interception details sent by the terminal through multimodal data targeting the interfering number. For example, the instruction parameters may include the interception time period, the number of interceptions, etc.

[0069] S303 determines the blocking strategy for interference numbers based on instruction parameters, call frequency, and call time period.

[0070] It should be noted that when it is necessary to determine the blocking strategy for the interference number based on the instruction parameters, call frequency, and call time period, the following may be included: conduct a risk assessment of the interference number based on the instruction parameters, call frequency, and call time period to obtain the risk assessment level corresponding to the interference number; and determine the blocking strategy for the interference number based on the risk assessment level.

[0071] The risk assessment level can be set or adjusted according to the actual situation. The specific content of the risk assessment level is not limited here. As an example, the risk assessment level may include, but is not limited to, high risk level, medium risk level and low risk level.

[0072] In one embodiment of this application, when it is necessary to conduct a risk assessment on a jamming number, a risk assessment model can be pre-trained. Then, the instruction parameters, call frequency, and call time period are input into the risk assessment model, and the output result of the risk assessment model is obtained. The output result is the risk assessment level corresponding to the jamming number.

[0073] The training process of the risk assessment model includes: acquiring sample data in advance, which includes sample instruction parameters, sample call comments and sample call time periods; labeling the sample data with sample levels through manual annotation and other means; and then inputting the labeled sample data into the initial model to train the initial model and obtain the trained risk assessment model.

[0074] In another embodiment of this application, when it is necessary to determine the interception strategy for the interfering number based on the risk assessment level, the mapping relationship between candidate levels and candidate strategies can be obtained in advance. The mapping relationship records different candidate strategies corresponding to different candidate levels. Therefore, after obtaining the risk assessment level corresponding to the interfering number, a reference level that is the same as the risk assessment level is selected from the candidate levels, and the candidate strategy corresponding to the reference level in the mapping relationship is used as the interception strategy for the interfering number.

[0075] The aforementioned call interception method determines the interception strategy for the interfering number by analyzing the call frequency and time period of the interfering number, as well as the command parameters in the interception instruction. This ensures that the core network can subsequently intercept calls to the interfering number according to the interception strategy, guaranteeing call interception against the interfering number without relying on terminal capabilities. This improves the convenience, accuracy, and flexibility of intercepting interfering numbers.

[0076] In one embodiment, such as Figure 4 As shown, when it is necessary to perform feature extraction and fusion on multimodal data to obtain the corresponding interception command for the terminal, the following can be included:

[0077] S401, extract semantic features from multimodal data to obtain semantic feature data.

[0078] The multimodal data includes at least one of the following: USSD unstructured supplementary data business code data, voice command data, and application settings data.

[0079] In one embodiment of this application, a semantic analysis model can be pre-trained. By inputting multimodal data into the semantic analysis model and obtaining the output result of the semantic analysis model, the output result is the semantic feature data.

[0080] The training process of the semantic analysis model includes: acquiring multimodal sample data, annotating the multimodal sample data with semantic features through manual annotation, and then training the initial analysis model with the multimodal sample data annotated with semantic features to obtain the trained semantic analysis model.

[0081] S402 performs feature fusion on the semantic feature data to obtain the corresponding interception command for the terminal.

[0082] It should be noted that when it is necessary to generate interception instructions corresponding to the terminal, the standard format for the instructions can be obtained in advance. Then, based on the standard format, the semantic feature data can be fused to obtain the interception instructions corresponding to the terminal.

[0083] The aforementioned call interception method performs feature fusion on semantic feature data obtained by extracting semantic features from multimodal data to obtain the corresponding interception instructions for the terminal. This provides a data foundation for generating subsequent interception strategies for interference numbers and ensures the smooth progress of subsequent processes.

[0084] In one embodiment, such as Figure 5 As shown, when it is necessary to determine the interception strategy for a jamming number based on the interception instruction and the historical call information of the jamming number, the following may be included:

[0085] S501 performs authentication on the terminal.

[0086] The identity verification methods include at least one of SMS verification code verification, dynamic PIN personal identification number verification, and two-factor authentication.

[0087] S502, after successful terminal authentication, determines the interception strategy for the interfering number based on the interception instruction and the historical call information of the interfering number.

[0088] In one embodiment of this application, the terminal can be identified by sending an SMS verification code "654321". If the terminal enters "654321" into the input box of the corresponding application, the terminal identity verification is confirmed to be successful. Otherwise, if the terminal fails to enter the correct verification code multiple times, the terminal identity verification is confirmed to be unsuccessful.

[0089] The aforementioned call interception method, by authenticating the terminal, ensures the security and effectiveness of users' call interception operations through the terminal, prevents others from making fraudulent operations through other terminals, and guarantees the effective execution of call interception.

[0090] In one embodiment, such as Figure 6 As shown, when call blocking against harassing numbers is required, the following can be included:

[0091] S601, acquire the multimodal data sent by the terminal targeting the interfering number.

[0092] S602, extract semantic features from multimodal data to obtain semantic feature data.

[0093] S603 performs feature fusion on semantic feature data to obtain the corresponding interception command for the terminal.

[0094] S604. Based on the historical call information of the interfering number, determine the call frequency and call period of the interfering number.

[0095] S605 extracts instruction parameters from the interception command.

[0096] S606 performs authentication on the terminal.

[0097] S607, after successful terminal authentication, performs a risk assessment on the interfering number based on instruction parameters, call frequency, and call time period to obtain the corresponding risk assessment level of the interfering number.

[0098] S608 determines the blocking strategy for interference numbers based on the risk assessment level.

[0099] S609 stores the interception policy in the core network so that the core network can intercept calls targeting interference numbers according to the interception policy.

[0100] In one embodiment of this application, such as Figure 7As shown, a call interception method can also be implemented through a call interception system, which includes: ① a multimodal interactive access module, ② an intelligent semantic parsing engine module, ③ an authentication module, ④ a data encryption module, ⑤ an intelligent policy generation module, ⑥ a policy management module, ⑦ a network adaptation module, and ⑧ a network signaling interception module. Specifically, the user inputs multimodal data for the harassing number into the ① multimodal interactive access module, and the ② intelligent semantic parsing engine module extracts features from the multimodal data. The ③ authentication module verifies the legitimacy of the terminal identity through SMS verification codes, dynamic PIN codes, two-factor authentication, etc., and the ④ data encryption module encrypts the relevant data. After successful verification, the marking and blocking configuration for harassing calls is triggered. The ⑤ intelligent policy generation module determines the blocking policy for the harassing number (strict rejection / voice prompt / temporary access). At the same time, the generated policy is pushed to the ⑥ policy management module. The ⑥ policy management module centrally stores the policy in the core network and synchronizes it to all terminals under the user's name (landline, mobile phone, IP extension) in real time through a cross-terminal linkage protection mechanism. ⑦ The network adaptation module connects to the core network equipment and converts the policy into the signaling format of the corresponding network. Finally, ⑧ the network signaling interception module performs signaling-level interception at the core network element, directly blocking high-risk calls and triggering voice verification for medium-risk calls.

[0101] As an example, when call blocking is required, the following can be included: The user speaks to their mobile phone: "Block 138-XXXX-1234, label it as real estate sales." The multimodal interactive access module recognizes the voice input; the intelligent semantic parsing engine extracts the keywords: "block," "138-XXXX-1234," and "real estate sales," generating a standardized blocking instruction: {action:block,number:138XXXX1234,label:real estate sales}; the authentication module authenticates the terminal by sending an SMS verification code "654321," which the user enters to complete the authentication; the intelligent policy generation module combines the call frequency and call time period (high-frequency marking) of the interfering number to determine the blocking policy for the interfering number: strict rejection; the policy management module synchronizes the policy to all user terminals (mobile phones, landlines) and executes signaling-level blocking in the core network through the "network signaling blocking module"; when the interfering number calls again, the mobile phone hangs up without ringing, and the landline displays "line busy"; the terminal receives an SMS notification: "Number 138-XXXX-1234 (real estate sales) has been successfully blocked."

[0102] The aforementioned call interception method acquires multimodal data sent by the terminal targeting interference numbers, extracts and fuses features from the multimodal data to obtain the corresponding interception command from the terminal, and then determines an interception strategy for the interference numbers based on the interception command and historical call information of the interference numbers, enabling the core network to intercept calls targeting the interference numbers according to the interception strategy. As can be seen from the above, this application, by acquiring multimodal data targeting interference numbers, achieves the acquisition of terminal interception requirements for interference numbers through various data interaction methods. Furthermore, by determining an interception strategy for interference numbers, the core network can intercept calls targeting the interference numbers according to the interception strategy, realizing an intelligent harassment interception scheme on the network side. This ensures call interception of interference numbers without relying on terminal capabilities, improving the convenience, accuracy, and flexibility of interception.

[0103] It should be understood that although the steps in the flowcharts of the above embodiments 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 above embodiments 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.

[0104] Based on the same inventive concept, this application also provides a call interception device for implementing the call interception method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more call interception device embodiments provided below can be found in the limitations of the call interception method described above, and will not be repeated here.

[0105] In one embodiment, such as Figure 8 As shown, a call interception device is provided, comprising: an acquisition module 10, a fusion module 20, and a determination module 30, wherein:

[0106] The acquisition module 10 is used to acquire multimodal data sent by the terminal targeting the interfering number.

[0107] The fusion module 20 is used to extract and fuse features from multimodal data to obtain the interception command corresponding to the terminal.

[0108] The determination module 30 is used to determine the interception strategy for the interference number based on the interception instruction and the historical call information of the interference number, and store the interception strategy in the core network so that the core network can intercept calls for the interference number according to the interception strategy.

[0109] In one embodiment, the call frequency and call period of the interfering number are determined based on the historical call information of the interfering number;

[0110] Extract instruction parameters from intercepted instructions;

[0111] Based on the command parameters, call frequency, and call time period, determine the blocking strategy for the interference numbers.

[0112] In one embodiment, the risk assessment of the interfering number is performed based on the instruction parameters, call frequency, and call time period to obtain the risk assessment level corresponding to the interfering number;

[0113] Based on the risk assessment level, determine the blocking strategy for the harassing numbers.

[0114] Semantic features are extracted from multimodal data to obtain semantic feature data;

[0115] The semantic feature data is fused to obtain the corresponding interception command for the terminal.

[0116] Multimodal data includes at least one of the following: USSD unstructured supplemental data business code data, voice command data, and application settings data.

[0117] Based on the interception instructions and the historical call information of the jamming number, determine the interception strategy for the jamming number, including:

[0118] The terminal is authenticated; the authentication method includes at least one of SMS verification code verification, dynamic PIN personal identification number verification, and two-factor authentication.

[0119] After successful terminal authentication, a blocking strategy for the interfering number is determined based on the blocking instructions and the historical call information of the interfering number.

[0120] The aforementioned call interception device acquires multimodal data sent by the terminal targeting interference numbers, performs feature extraction and fusion on the multimodal data to obtain the corresponding interception command from the terminal, and then determines the interception strategy for the interference numbers based on the interception command and the historical call information of the interference numbers, enabling the core network to intercept calls targeting the interference numbers according to the interception strategy. As can be seen from the above, this application, by acquiring multimodal data targeting interference numbers, achieves the acquisition of terminal interception requirements for interference numbers through various data interaction methods. Furthermore, by determining the interception strategy for interference numbers, the core network can intercept calls targeting the interference numbers according to the interception strategy, realizing a network-side intelligent harassment interception scheme. This ensures call interception of interference numbers without relying on terminal capabilities, improving the convenience, accuracy, and flexibility of interception.

[0121] Each module in the aforementioned call interception 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 corresponding operations of each module.

[0122] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 9 As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When executed by the processor, the computer program implements a call interception method. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0123] Those skilled in the art will understand that Figure 9 The structure shown 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 combine certain components, or have different component arrangements.

[0124] 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 perform the following steps:

[0125] Acquire multimodal data sent by the terminal targeting the interfering number;

[0126] Feature extraction and fusion are performed on multimodal data to obtain the interception command corresponding to the terminal;

[0127] Based on the interception instructions and historical call information of the interference number, an interception strategy for the interference number is determined and stored in the core network so that the core network can intercept calls to the interference number according to the interception strategy.

[0128] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0129] Based on the historical call information of the interfering number, determine the call frequency and call time period of the interfering number;

[0130] Extract instruction parameters from intercepted instructions;

[0131] Based on the command parameters, call frequency, and call time period, determine the blocking strategy for the interference numbers.

[0132] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0133] Based on the command parameters, call frequency, and call time period, a risk assessment is performed on the interfering number to obtain the corresponding risk assessment level.

[0134] Based on the risk assessment level, determine the blocking strategy for the harassing numbers.

[0135] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0136] Semantic features are extracted from multimodal data to obtain semantic feature data;

[0137] The semantic feature data is fused to obtain the corresponding interception command for the terminal.

[0138] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0139] Multimodal data includes at least one of the following: USSD unstructured supplemental data business code data, voice command data, and application settings data.

[0140] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0141] The terminal is authenticated; the authentication method includes at least one of SMS verification code verification, dynamic PIN personal identification number verification, and two-factor authentication.

[0142] After successful terminal authentication, a blocking strategy for the interfering number is determined based on the blocking instructions and the historical call information of the interfering number.

[0143] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0144] Acquire multimodal data sent by the terminal targeting the interfering number;

[0145] Feature extraction and fusion are performed on multimodal data to obtain the interception command corresponding to the terminal;

[0146] Based on the interception instructions and historical call information of the interference number, an interception strategy for the interference number is determined and stored in the core network so that the core network can intercept calls to the interference number according to the interception strategy.

[0147] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0148] Based on the historical call information of the interfering number, determine the call frequency and call time period of the interfering number;

[0149] Extract instruction parameters from intercepted instructions;

[0150] Based on the command parameters, call frequency, and call time period, determine the blocking strategy for the interference numbers.

[0151] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0152] Based on the command parameters, call frequency, and call time period, a risk assessment is performed on the interfering number to obtain the corresponding risk assessment level.

[0153] Based on the risk assessment level, determine the blocking strategy for the harassing numbers.

[0154] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0155] Semantic features are extracted from multimodal data to obtain semantic feature data;

[0156] The semantic feature data is fused to obtain the corresponding interception command for the terminal.

[0157] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0158] Multimodal data includes at least one of the following: USSD unstructured supplemental data business code data, voice command data, and application settings data.

[0159] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0160] The terminal is authenticated; the authentication method includes at least one of SMS verification code verification, dynamic PIN personal identification number verification, and two-factor authentication.

[0161] After successful terminal authentication, a blocking strategy for the interfering number is determined based on the blocking instructions and the historical call information of the interfering number.

[0162] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0163] Acquire multimodal data sent by the terminal targeting the interfering number;

[0164] Feature extraction and fusion are performed on multimodal data to obtain the interception command corresponding to the terminal;

[0165] Based on the interception instructions and historical call information of the interference number, an interception strategy for the interference number is determined and stored in the core network so that the core network can intercept calls to the interference number according to the interception strategy.

[0166] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0167] Based on the historical call information of the interfering number, determine the call frequency and call time period of the interfering number;

[0168] Extract instruction parameters from intercepted instructions;

[0169] Based on the command parameters, call frequency, and call time period, determine the blocking strategy for the interference numbers.

[0170] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0171] Based on the command parameters, call frequency, and call time period, a risk assessment is performed on the interfering number to obtain the corresponding risk assessment level.

[0172] Based on the risk assessment level, determine the blocking strategy for the harassing numbers.

[0173] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0174] Semantic features are extracted from multimodal data to obtain semantic feature data;

[0175] The semantic feature data is fused to obtain the corresponding interception command for the terminal.

[0176] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0177] Multimodal data includes at least one of the following: USSD unstructured supplemental data business code data, voice command data, and application settings data.

[0178] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0179] The terminal is authenticated; the authentication method includes at least one of SMS verification code verification, dynamic PIN personal identification number verification, and two-factor authentication.

[0180] After successful terminal authentication, a blocking strategy for the interfering number is determined based on the blocking instructions and the historical call information of the interfering number.

[0181] 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 shall comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0182] 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. When executed, the computer program 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 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, etc., and are not limited to these.

[0183] 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 specification.

[0184] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this 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 call interception method, characterized in that, The method includes: Acquire multimodal data sent by the terminal targeting the interfering number; Feature extraction and fusion are performed on the multimodal data to obtain the interception command corresponding to the terminal; Based on the interception command and the historical call information of the interference number, an interception strategy for the interference number is determined, and the interception strategy is stored in the core network so that the core network can intercept calls to the interference number according to the interception strategy.

2. The method according to claim 1, characterized in that, The step of determining an interception strategy for the interference number based on the interception instruction and the historical call information of the interference number includes: Based on the historical call information of the interfering number, determine the call frequency and call period of the interfering number; Extract the instruction parameters from the interception instruction; Based on the instruction parameters, the call frequency, and the call time period, a blocking strategy for the interference number is determined.

3. The method according to claim 2, characterized in that, The step of determining the interception strategy for the interference number based on the instruction parameters, the call frequency, and the call time period includes: Based on the instruction parameters, the call frequency, and the call period, a risk assessment is performed on the interfering number to obtain the risk assessment level corresponding to the interfering number; Based on the risk assessment level, a blocking strategy is determined for the interference number.

4. The method according to claim 1, characterized in that, The step of extracting and fusing features from the multimodal data to obtain the interception command corresponding to the terminal includes: Semantic features are extracted from the multimodal data to obtain semantic feature data; The semantic feature data is fused to obtain the interception command corresponding to the terminal.

5. The method according to claim 4, characterized in that, The multimodal data includes at least one of the following: USSD unstructured supplemental data service code data, voice command data, and application settings data.

6. The method according to claim 1, characterized in that, The step of determining an interception strategy for the interference number based on the interception instruction and the historical call information of the interference number includes: The terminal is authenticated; wherein the authentication method includes at least one of SMS verification code verification, dynamic PIN personal identification number verification, and two-factor authentication. After the terminal authentication is successful, an interception strategy for the interference number is determined based on the interception instruction and the historical call information of the interference number.

7. A call interception device, characterized in that, The device includes: The acquisition module is used to acquire multimodal data sent by the terminal targeting the interfering number; The fusion module is used to extract and fuse features from the multimodal data to obtain the interception command corresponding to the terminal. The determining module is configured to determine an interception strategy for the interfering number based on the interception instruction and the historical call information of the interfering number, and store the interception strategy in the core network so that the core network can intercept calls for the interfering number according to the interception strategy.

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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