CN110636531B

CN110636531B - Subscription abnormity user identification method and device

Info

Publication number: CN110636531B
Application number: CN201810539333.XA
Authority: CN
Inventors: 黄珊; 林永兴; 黄洁; 史超云; 李佐辉; 茅宏业
Original assignee: China Mobile Group Zhejiang Co Ltd
Current assignee: China Mobile Group Zhejiang Co Ltd
Priority date: 2018-05-30
Filing date: 2018-05-30
Publication date: 2023-04-25
Anticipated expiration: 2038-05-30
Also published as: CN110636531A

Abstract

The embodiment of the invention provides a method and a device for identifying abnormal subscription users, wherein the method comprises the following steps: screening candidate signing abnormal users according to a preset abnormal scene signaling feature model and long term evolution voice VoLTE service signaling data of each user; and carrying out subscription inquiry on each subscription gateway network element corresponding to the candidate subscription abnormal user, and identifying the subscription abnormal user according to the subscription inquiry result. The scheme provided by the embodiment of the invention can actively identify the subscribed abnormal user, avoid checking after the user perceives the abnormal user and complains, improve the timeliness of finding the problem, and facilitate timely repairing the abnormal user, thereby improving the user service experience.

Description

Subscription abnormity user identification method and device

Technical Field

The embodiment of the invention relates to the technical field of communication, in particular to a method and a device for identifying abnormal subscription users.

Background

With the maturation and deep coverage of LTE (Long Term Evolution ) networks, voLTE (Voice over LTE)/eSRVCC (Enhanced Single Radio Voice Call Continuity, enhanced single radio Voice VoLTE service continuity) services are widely popularized in order to further enhance user Voice service awareness.

The network architecture of the VoLTE service is very complex, and relates to VoLTE AS (Application Server ), i\s\p-CSCF (inter-working\working\ Proxy Call Session Control Function, negotiation\service\proxy-VoLTE service session control function), SBC ((Session Border Controller), session edge control), ENS (Enhanced Name Server ), MGCF (Media Gateway Control Function), media gateway control function), HSS (Home Subscriber Server ), MRFC (Multimedia Resource Function Controller, multimedia resource controller), MRFP (Multimedia Resource Function Processor, multimedia resource processor) and other network elements, and the subscription data of the VoLTE user also relates to multiple aspects. When a user opens a VoLTE service, a BOSS (Business Operation Support System, service operation support system) needs to send a plurality of service opening instructions to three network elements of an HSS, an ENS and a VoLTE AS respectively, and only if the user subscription data of the three network elements are normal and effective, the excellent experience of the user when using the VoLTE service can be ensured.

In the prior art, the guarantee of the accuracy of the subscription data of the VoLTE user by the network side is mainly realized through the sequence of the optimized service opening instruction of the BOSS side, wherein VoLTE TAG (label), IMS (Internet Protocol Multimedia Subsystem ) APN (Access Point Name, access point name) and STNSR (Session Transfer Number Single Radio, single wireless session transfer number) data of the user are issued to the HSS first, then multimedia user information of the user is issued to the VoLTE AS, NAPTR (Naming Authority Pointer, name authority pointer) data of the user is issued to the ENS, and finally VoLTE TCSI (Terminating-CAMEL Subscription Information, terminating intelligent network subscription information) data of the user is supplemented to the HSS.

However, when the user performs operations such as card replacement, service inquiry/synchronization, new service activation, and existing service cancellation, the change of the VoLTE user subscription data may be caused. When the data of the VoLTE user abnormally influences the service experience of the VoLTE user, the problem can be found and solved only through complaints initiated by the user to a network and a supporting department, the network and the supporting side are difficult to actively find the signing problem related to the VoLTE user, and the timeliness of finding the problem is low.

Disclosure of Invention

Aiming at the defects in the prior art, the subscription abnormal user identification method and device provided by the embodiment of the invention can actively find out the users with subscription abnormalities, improve the timeliness of finding out problems, and facilitate timely repairing the abnormalities, thereby improving the user service experience.

In one aspect, an embodiment of the present invention provides a method for identifying a subscriber with abnormal subscription, including:

screening candidate signing abnormal users according to a preset abnormal scene signaling feature model and long term evolution voice VoLTE service signaling data of each user;

and carrying out subscription inquiry on each subscription gateway network element corresponding to the candidate subscription abnormal user, and identifying the subscription abnormal user according to the subscription inquiry result.

In still another aspect, an embodiment of the present invention provides a subscription abnormal user identification device, including:

the candidate abnormal screening unit is used for screening candidate contracted abnormal users according to a preset abnormal scene signaling characteristic model and long term evolution voice VoLTE service signaling data of each user;

and the abnormal user identification unit is used for carrying out subscription inquiry on each subscription related network element corresponding to the candidate subscription abnormal user, and identifying the subscription abnormal user according to the subscription inquiry result.

In yet another aspect, an embodiment of the present invention provides an electronic device, including a processor, a memory, and a bus, wherein:

the processor and the memory complete communication with each other through a bus;

the processor may call a computer program in memory to perform: screening candidate signing abnormal users according to a preset abnormal scene signaling feature model and long term evolution voice VoLTE service signaling data of each user; and carrying out subscription inquiry on each subscription gateway network element corresponding to the candidate subscription abnormal user, and identifying the subscription abnormal user according to the subscription inquiry result.

In yet another aspect, an embodiment of the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs: screening candidate signing abnormal users according to a preset abnormal scene signaling feature model and long term evolution voice VoLTE service signaling data of each user; and carrying out subscription inquiry on each subscription gateway network element corresponding to the candidate subscription abnormal user, and identifying the subscription abnormal user according to the subscription inquiry result.

According to the subscription abnormal user identification method and device provided by the embodiment of the invention, candidate subscription abnormal users are screened out according to the preset abnormal scene signaling feature model and the long term evolution voice VoLTE service signaling data of each user; and carrying out subscription inquiry on each subscription gateway network element corresponding to the candidate subscription abnormal user, and identifying the subscription abnormal user according to the subscription inquiry result. In this way, the voice over LTE service signaling data is used for actively identifying the subscribed abnormal user, so that the user is prevented from perceiving the abnormal user and checking after complaints occur, the timeliness of finding the problem is improved, the abnormal user is convenient to repair in time, and the service experience of the user is improved.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 illustrates an exemplary flow chart of a method of subscription anomaly user identification in accordance with an embodiment of the present invention;

Fig. 2 is a schematic diagram illustrating a configuration of a subscription abnormal user identification apparatus according to an embodiment of the present invention;

fig. 3 shows a physical structure of an electronic device according to an embodiment of the invention.

Detailed Description

The following description of the embodiments of the present invention will be made more apparent and fully hereinafter with reference to the accompanying drawings, in which some, but not all embodiments of the invention are shown. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the invention, are within the scope of the invention.

As used herein, the terms "module," "apparatus," and the like are intended to include a computer-related entity, either hardware, firmware, a combination of hardware and software, or software in execution. For example, a module may be, but is not limited to: a process running on a processor, an object, an executable, a thread of execution, a program, and/or a computer. By way of example, both an application running on a computing device and the computing device can be a module. One or more modules may be located in one process and/or thread of execution, and one module may be located on one computer and/or distributed between two or more computers.

The technical scheme of the invention is described in detail below with reference to the accompanying drawings.

Referring to fig. 1, an exemplary flow chart of a method of subscription anomaly user identification in accordance with an embodiment of the present invention is shown.

As shown in fig. 1, the method for identifying a subscriber with abnormal subscription provided by the embodiment of the invention may include the following steps:

s110: and screening out candidate contracted abnormal users according to a preset abnormal scene signaling feature model and long term evolution voice VoLTE service signaling data of each user.

The method for identifying the abnormal signing user provided by the embodiment of the invention can be applied to the abnormal signing user identification device for identifying the VoLTE abnormal signing user in the network domain. Among other things, voLTE traffic may include, but is not limited to: voLTE registration traffic and VoLTE call traffic.

In practical application, network signaling generated when the user uses the VoLTE service every day can be analyzed in advance, and various scenes of call connection failure caused by abnormal VoLTE subscription of the user can be examined and summarized. In the embodiment of the invention, the subscription data anomaly scene may include: abnormal VoLTE AS subscription data, un-deleted subscription data on ENS after HSS is sold, un-deleted anchor TCSI data when HSS is sold, and inconsistent IMSI (International Mobile Subscriber Identification Number, international mobile subscriber identity) in HSS.

And analyzing the signaling flow of each abnormal scene of the subscription data, and extracting the signaling characteristics of the abnormal scene of the subscription data, thereby obtaining an abnormal scene signaling characteristic model.

In the embodiment of the invention, the signaling data of all VoLTE services in the network (which means the control plane and user plane basic flow records generated for the signaling monitoring platform and signaling application after processing based on the total signaling data) can be pulled from the signaling platform in real time or periodically.

In this way, the generalized abnormal scene signaling feature model can be used as a condition, and the data of the abnormal scene of the subscription data in the signaling data can be filtered out, so that candidate abnormal subscription users with suspected VoLTE subscription anomalies can be screened out.

S120: and carrying out subscription inquiry on each subscription gateway network element corresponding to the candidate subscription abnormal user, and identifying the subscription abnormal user according to the subscription inquiry result.

In the embodiment of the present invention, after screening out the candidate abnormal subscriber with suspected VoLTE abnormal subscription through step S110, subscription information may be further queried from the subscription related network elements such AS HSS, ENS, voLTE AS, etc. for the candidate abnormal subscriber to determine whether the candidate abnormal subscriber is truly abnormal subscription, if yes, the candidate abnormal subscriber is identified AS abnormal subscription.

According to the subscription abnormal user identification method provided by the embodiment of the invention, candidate subscription abnormal users are screened out according to the preset abnormal scene signaling feature model and the long term evolution voice VoLTE service signaling data of each user; and carrying out subscription inquiry on each subscription gateway network element corresponding to the candidate subscription abnormal user, and identifying the subscription abnormal user according to the subscription inquiry result. In this way, the voice over LTE service signaling data is used for actively identifying the subscribed abnormal user, so that the user is prevented from perceiving the abnormal user and checking after complaints occur, the timeliness of finding the problem is improved, the abnormal user is convenient to repair in time, and the service experience of the user is improved.

Further, on the basis of the foregoing embodiment, in the subscription abnormal user identification method provided in still another embodiment of the present invention, the abnormal scene signaling feature model includes:

the first abnormal scene signaling feature model, the second abnormal scene signaling feature model, and the third abnormal scene signaling feature model.

The first abnormal scene signaling feature model comprises first signaling features conforming to the abnormal scene of the AS subscription data of the VoLTE application server.

The second abnormal scene signaling feature model comprises second signaling features which are in line with the scene of undeleted subscription data on the enhanced name server ENS after the home subscriber server HSS is sold or the scene of undeleted subscription information TCSI data of the anchoring terminating intelligent network when the HSS is sold.

The third abnormal scene signaling feature model comprises a third signaling feature which accords with the scene of inconsistent IMSI (International Mobile Subscriber Identification Number, international mobile subscriber identity) in the HSS.

In practical application, for scene one and the abnormal scene of VoLTE AS subscription data, when the user has subscribed VoLTE service data in the HSS, but the VoLTE AS subscription data is abnormal, the third party registration of the user will fail at this time, and the VoLTE call connection will be affected. When a caller calls from VoLTE back to CS (Circuit Switched) domain, the call continues to be initiated, the connection time is long, the VoLTE experience is affected, the callee can be connected, but no VoLTE AS ticket is available, and charging is affected.

In a scenario, when a user calls, the SCSCF where the SCSCF is located sends an invite message to the VoLTE AS according to the IFC subscribed by the HSS of the user, and the VoLTE AS returns a 500internal server error response (warning contains no userdata or query dba fail or query ssdb fail) due to abnormal subscription of the user in the VoLTE AS.

Thus, in an embodiment of the present invention, the first signaling feature includes: the first tear-down network element is a VoLTE AS, the tear-down message is a 500 message, and the warning code in the 500 message comprises any one of the following: no userdata, query dba fail, and query ssdb fail.

In practical application, for a scene of deleting subscription data on ENS after a user logs out of a HSS in a second scene, when the user cancels the VoLTE service, if VoLTE subscription data in the HSS is deleted, but there is residue on ENS data, other users can listen to a blank prompt when calling the user in the VoLTE domain, and user experience is seriously affected.

In scenario two, when other users call the user in the VoLTE domain, because the ENS data of the user is not deleted, the calling SCSCF queries the ENS for the ICSCF address of the user, and generates an invite message to the ICSCF. The ICSCF sends LIR (Location Info Request, location information request) message to the called home HSS to query the SCSCF address of the called registration, and the HSS returns LIA (Location Info Answer, location information answer) message to the ICSCF, carrying 5001 error, since other VoLTE subscription data of the called subscriber has been deleted. After receiving the message, the called ICSCF returns a 404 not found or 604Does Not Exist Anywhere message to the calling side, the call connection fails, and the calling side listens for the prompt tone of the called blank number.

For the scene three, anchoring TCSI data is not deleted when HSS sells the user, when the user cancels VoLTE service, if other VoLTE subscription data are all cleared, but anchoring TCSI data is not deleted, other users can listen to the blank number prompt when calling the user in CS/PSTN domain, and the user experience is seriously affected.

Under the third scenario, when other users call the user in CS/PSTN (Public Switched Telephone Network ), because the user signs up with VoLTE anchored TCSI, the call is sent to VoLTE domain ICSCF via MGCF (Media Gateway Control Function ), ICSCF sends LIR message to called home HSS to inquire the SCSCF address registered by the called, because other VoLTE signed data of the called user has been deleted, HSS returns LIA message to ICSCF, carrying 5001diameter-error-user-unknown error. After receiving the message, the called ICSCF returns 404 the message to the MGCF side, the call connection fails, and the calling party listens to the prompt tone of the called number as the null number.

Thus, in an embodiment of the present invention, the second signaling feature includes: the first drop network element is HSS, the drop message is LIA (Location-Info-Answer), and the cause value is: 5001.

for the scene four and the scene that the IMSI in the HSS is inconsistent, after the user opens the VoLTE service, the user may have the actions of supplementing the card, canceling the VoLTE service, restarting the VoLTE service and the like, and in the process, the IMSI of the user in the SEA-HSS and the IMSI of the user in the IMS-HSS may be inconsistent due to the reasons of supporting side data and the like, so that the VoLTE registration of the user is affected, and the service cannot be used.

Under the fourth scenario, when the user is initially registered, the ICSCF sends a UAR message to the user home HSS to obtain the SCSCF capability set, and after checking that the user data is abnormal, the HSS replies a UAA message, carrying 5001 an error.

Thus, in an embodiment of the present invention, the third signaling feature includes: the first tear-down network element is an HSS, the tear-down message is a UAA (User-authentication-Answer), and the cause value is: 5001.

other steps of the embodiment of the present invention are similar to those of the previous embodiment, and are not repeated.

According to the subscription abnormal user identification method provided by the embodiment of the invention, the typical scene of call connection failure caused by the subscription abnormality of the user VoLTE is checked and summarized, so that an abnormal scene signaling feature model formed by signaling features in the subscription data abnormal scene is obtained; therefore, users suspected of VoLTE abnormal subscription can be accurately and rapidly screened out through the abnormal scene signaling feature model, and the efficiency and accuracy of identifying abnormal subscription users are improved.

Further, on the basis of the foregoing embodiment, in the subscription abnormal user identification method provided in another embodiment of the present invention, the screening the candidate subscription abnormal users according to the preset abnormal scene signaling feature model and the long term evolution voice VoLTE service signaling data of each user includes:

For each VoLTE service, if the signaling data of the VoLTE service has the data matched with the first signaling feature, identifying the calling number or the called number of the VoLTE service as a candidate subscription abnormal user matched with the signaling feature model of the first abnormal scene;

if the signaling data of the VoLTE service has the data matched with the second signaling feature, identifying the called number of the VoLTE service as a candidate subscription abnormal user matched with a signaling feature model of a second abnormal scene;

and if the signaling data of the VoLTE service has the data matched with the third signaling feature, identifying the registered user in the VoLTE service as a candidate subscription abnormal user matched with the signaling feature model of the third abnormal scene.

In the embodiment of the invention, for each VoLTE service, the signaling data of the VoLTE service can be compared with the signaling characteristics in the signaling characteristic models of different abnormal scenes.

If the signaling data of the VoLTE service has the data matched with the first signaling feature, the VoLTE service is indicated to accord with the abnormal scene of the VoLTE AS subscription data, and the calling number or the called number in the VoLTE service can be identified AS the candidate subscription abnormal user matched with the signaling feature model of the first abnormal scene. In practical application, the calling number or the called number in the VoLTE-originated service may be identified AS a candidate abnormal subscription user matching the first signaling feature or the abnormal VoLTE AS subscription data scene.

In practical application, if the signaling data of the VoLTE service has data matched with the first signaling feature, judging whether the first split network element is a calling side VoLTE AS; if yes, identifying the calling number of the VoLTE service as a candidate abnormal subscription user; if not, the called number of the VoLTE service is identified as the candidate abnormal subscription user.

If the signaling data of the VoLTE service has the data matched with the second signaling feature, the signaling data of the VoLTE service is indicated to accord with a scene with undeleted subscription data on the ENS after the HSS is sold or a scene with undeleted anchor TCSI data when the HSS is sold, and the called number of the VoLTE service can be identified as a candidate subscription abnormal user matched with a signaling feature model of a second abnormal scene. In practical application, the called number of the VoLTE service can be identified as a candidate abnormal subscription user matched with the second signaling feature. Or, the called number of the VoLTE-initiated service may be identified AS a candidate subscriber with abnormal subscription matching the abnormal subscription data scenario of VoLTE AS or the scenario with the TCSI data not deleted when the HSS is subscribed.

If the signaling data of the VoLTE service has the data matched with the third signaling feature, the VoLTE service is indicated to accord with the scene of inconsistent IMSI in the HSS, and the registered user in the VoLTE service can be identified as the candidate signing abnormal user matched with the signaling feature model of the third abnormal scene. In practical application, the registered user in the VoLTE service may be identified as a candidate subscription anomaly user matching the third signaling feature or the scenario of inconsistent IMSI in the HSS.

According to the method for identifying the abnormal subscription subscribers, provided by the embodiment of the invention, the VoLTE service with suspected abnormal subscription data is screened out through the comparison of the signaling data of the VoLTE service and the signaling characteristics in the abnormal scene signaling characteristic model corresponding to different abnormal subscription data scenes, so that candidate abnormal subscription subscribers with suspected abnormal subscription data are identified, and meanwhile, the identification rate and the accuracy rate can be improved.

Further, in the method for identifying abnormal subscription users according to the foregoing embodiment of the present invention, the performing subscription inquiry on each subscription gateway network element corresponding to the candidate abnormal subscription user, and identifying abnormal subscription users according to the subscription inquiry result includes:

after determining that the candidate abnormal subscription user is a VoLTE user for the candidate abnormal subscription user matched with the signaling feature model of the first abnormal scene, if the user subscription data in the HSS and the user subscription data in the ENS are normal and no user subscription data in the VoLTE AS is available, identifying the candidate abnormal subscription user AS the abnormal subscription user;

For the candidate abnormal subscription users matched with the signaling feature model of the second abnormal scene, determining that the candidate abnormal subscription users are non-VoLTE users, and after IMS user subscription data is not contained in the HSS, if user subscription data exists in the ENS or TCSI in the HSS is anchoring AS, identifying the candidate abnormal subscription users AS abnormal subscription users;

and for the candidate abnormal subscription users matched with the signaling feature model of the third abnormal scene, determining that the candidate abnormal subscription users are VoLTE users, and after IMS user subscription data exist in the HSS, if the IMSI in the SEA-HSS is inconsistent with the IMSI in the IMS-HSS, identifying the candidate abnormal subscription users as abnormal subscription users.

In the embodiment of the invention, in order to accurately identify the abnormal subscriber, the candidate abnormal subscriber suspected of abnormal subscription data can further query the HSS, the ENS and the HSS for subscription information so as to determine whether the abnormal subscription data is abnormal.

Specifically, for the candidate subscribed abnormal user matching the signaling feature model of the first abnormal scene, whether the VoLTE TAG in the HSS is true may be first determined, if yes, it is indicated that the candidate subscribed abnormal user is a VoLTE user; after the candidate abnormal subscription user is determined to be the VoLTE user, whether the user subscription data in the ENS is normal or not is further judged, if the user subscription data in the HSS and the user subscription data in the ENS are normal, whether the VoLTE AS has the user subscription data is further judged, if the user subscription data does not exist in the VoLTE AS, the problem that the candidate abnormal subscription user has AS subscription abnormality is indicated, and the candidate abnormal subscription user can be identified AS the abnormal subscription user.

For the candidate subscription abnormal user matched with the signaling feature model of the second abnormal scene, whether the VOLTE TAG in the HSS is false or not can be judged first, if so, the candidate subscription abnormal user is a non-VoLTE user; after determining that the candidate abnormal subscription user is a non-VoLTE user and there is no IMS user subscription data in the HSS, it may further be determined whether there is user subscription data in the ENS, and at the same time, whether the TCSI in the HSS anchors the AS.

If the user subscription data exists in the ENS, the problem that the candidate abnormal subscription user has ENS subscription abnormality is indicated, and the candidate abnormal subscription user can be identified as the abnormal subscription user.

If the TCSI in the HSS is the anchor AS, it indicates that the candidate abnormal subscriber has the problem of abnormal HSSTCSI subscription, and the candidate abnormal subscriber can be identified AS the abnormal subscriber.

For the candidate subscription abnormal user matched with the signaling feature model of the third abnormal scene, whether the VoLTE TAG in the HSS is true or not can be judged first, if so, the candidate subscription abnormal user is indicated to be the VoLTE user; after determining that the candidate abnormal subscription user is a VoLTE user and IMS user subscription data exists in the HSS, the MSISDN can be used for inquiring the IMSI in the SEA-HSS of the user and the IMSI in the IMS-HSS respectively, and comparing, if the IMSI in the SEA-HSS is inconsistent with the IMSI in the IMS-HSS, the subsequent candidate abnormal subscription user is the abnormal subscription user.

According to the method for identifying the abnormal subscription users, provided by the embodiment of the invention, the candidate abnormal subscription users with abnormal suspected subscription data are further inquired about subscription information from the HSS, the ENS and the HSS to check the abnormal subscription users with abnormal subscription problems, so that the identification accuracy is ensured.

Further, on the basis of the foregoing embodiment, in the subscription abnormal user identification method provided in still another embodiment of the present invention, the method further includes:

determining the subscription anomaly category of the subscription anomaly user according to the anomaly scene signaling feature model matched with the subscription anomaly user;

the abnormal subscription category of the abnormal subscription user is specifically any one of the following: abnormal AS subscription, abnormal ENS subscription, abnormal HSS TCSI subscription and abnormal IMS user subscription in IMS-HSS.

In the embodiment of the invention, for the subscription anomaly users matched with the first anomaly scene signaling feature model, the subscription anomaly category corresponding to the subscription anomaly users is determined to be AS subscription anomaly.

And for the abnormal signing user matched with the second abnormal scene signaling feature model, if user signing data exists in the ENS, determining that the abnormal signing category corresponding to the abnormal signing user is the ENS abnormal signing.

And for the subscribed abnormal users matched with the second abnormal scene signaling feature model, if TCSI in the HSS is an anchor AS, determining that the subscribed abnormal category corresponding to the subscribed abnormal users is HSS TCSI subscribed abnormal.

And for the subscribed abnormal users matched with the third abnormal scene signaling feature model, determining that the subscribed abnormal category corresponding to the subscribed abnormal users is IMS user subscription abnormal in the IMS-HSS.

According to the abnormal subscription user identification method provided by the embodiment of the invention, the abnormal subscription category of the abnormal subscription user is determined according to the abnormal scene signaling feature model matched with the abnormal subscription user by the user identified as abnormal subscription, so that the abnormal subscription network element, namely the network element with abnormal subscription, is positioned, and the subsequent restoration of the user subscription is facilitated.

according to the abnormal subscription category of the abnormal subscription user, locating the abnormal subscription network element, and repairing the subscription data corresponding to the abnormal subscription user on the abnormal subscription network element.

In the embodiment of the invention, if the abnormal subscription category of the abnormal subscription user is AS abnormal subscription, the abnormal subscription network element can be positioned AS the AS corresponding to the abnormal subscription user.

If the abnormal subscription category of the abnormal subscription user is ENS abnormal subscription, the abnormal subscription network element can be positioned as ENS.

If the abnormal subscription category of the abnormal subscription user is HSS TCSI abnormal subscription, the abnormal subscription network element can be positioned as HSS.

If the abnormal subscription category of the abnormal subscription user is abnormal subscription of the IMS user in the IMS-HSS, the abnormal subscription network element can be positioned as the HSS.

In practical application, a repair instruction script can be automatically generated for the subscription data of the network element with the subscription abnormality and the subscription data of the subscription abnormality user, so AS to repair the data such AS VoLTE AS, ENS, TCSI, IMSI and the like associated with the subscription abnormality user.

According to the subscription abnormal user identification method provided by the embodiment of the invention, the user service experience can be improved through restoration of subscription data.

On the basis of the above embodiments, a further embodiment of the present invention provides a subscription abnormal user identification device.

Referring to fig. 2, a schematic diagram of a subscription abnormal user identification device according to an embodiment of the present invention is shown.

As shown in fig. 2, the subscription abnormal user identification device 200 provided in the embodiment of the present invention may include: a candidate abnormality screening unit 201 and an abnormal user identifying unit 202.

The candidate abnormal screening unit 201 is configured to screen candidate subscribed abnormal users according to a preset abnormal scene signaling feature model and long term evolution voice VoLTE service signaling data of each user.

The abnormal user identification unit 202 is configured to perform subscription inquiry on each subscription gateway network element corresponding to the candidate abnormal subscription user, and identify the abnormal subscription user according to the subscription inquiry result.

Optionally, the abnormal scene signaling feature model includes:

the first abnormal scene signaling feature model, the second abnormal scene signaling feature model and the third abnormal scene signaling feature model;

the first abnormal scene signaling feature model comprises first signaling features conforming to the abnormal scene of the AS subscription data of the VoLTE application server;

the second abnormal scene signaling feature model comprises second signaling features which accord with the scene of undeleted subscription data on the enhanced name server ENS after the home subscriber server HSS is sold or the scene of undeleted subscription information TCSI data of the anchoring terminating intelligent network when the HSS is sold;

And the third abnormal scene signaling feature model comprises third signaling features which accord with the scene that the International Mobile Subscriber Identity (IMSI) of the HSS is inconsistent.

Optionally, the candidate abnormal screening unit 201 is specifically configured to identify, for each VoLTE service, if there is data matching the first signaling feature in signaling data of the VoLTE service, a calling number or a called number of the VoLTE service as a candidate subscribed abnormal user matching the signaling feature model of the first abnormal scene; if the signaling data of the VoLTE service has the data matched with the second signaling feature, identifying the called number of the VoLTE service as a candidate subscription abnormal user matched with a signaling feature model of a second abnormal scene; and if the signaling data of the VoLTE service has the data matched with the third signaling feature, identifying the registered user in the VoLTE service as a candidate subscription abnormal user matched with the signaling feature model of the third abnormal scene.

Optionally, the candidate anomaly screening unit 201 is specifically configured to determine whether the first tear-down network element is a caller-side VoLTE AS if there is data matching the first signaling feature in the signaling data of the VoLTE-start service; if yes, identifying the calling number of the VoLTE service as a candidate abnormal subscription user; if not, the called number of the VoLTE service is identified as the candidate abnormal subscription user.

Optionally, the abnormal user identifying unit 202 is specifically configured to identify, for a candidate abnormal user who matches the signaling feature model of the first abnormal scenario, that the candidate abnormal user is a VoLTE user, and identify the candidate abnormal user AS the abnormal user if the user subscription data in the HSS and the user subscription data in the ENS are normal and the user subscription data in the VoLTE AS is not available; for the candidate abnormal subscription users matched with the signaling feature model of the second abnormal scene, determining that the candidate abnormal subscription users are non-VoLTE users, and after IMS user subscription data is not contained in the HSS, if user subscription data exists in the ENS or TCSI in the HSS is anchoring AS, identifying the candidate abnormal subscription users AS abnormal subscription users; and for the candidate abnormal subscription users matched with the signaling feature model of the third abnormal scene, determining that the candidate abnormal subscription users are VoLTE users, and after IMS user subscription data exist in the HSS, if the IMSI in the SEA-HSS is inconsistent with the IMSI in the IMS-HSS, identifying the candidate abnormal subscription users as abnormal subscription users.

Optionally, the abnormal user identifying unit 202 is further configured to determine a subscription abnormal category of the subscription abnormal user according to the abnormal scene signaling feature model matched with the subscription abnormal user.

Optionally, the abnormal user identification unit 202 is further configured to locate an abnormal subscribed network element according to the abnormal subscription category of the abnormal subscription user, and repair subscription data corresponding to the abnormal subscription user on the abnormal subscribed network element.

According to the subscription abnormal user identification device provided by the embodiment of the invention, candidate subscription abnormal users are screened out according to the preset abnormal scene signaling feature model and the long term evolution voice VoLTE service signaling data of each user; and carrying out subscription inquiry on each subscription gateway network element corresponding to the candidate subscription abnormal user, and identifying the subscription abnormal user according to the subscription inquiry result. In this way, the voice over LTE service signaling data is used for actively identifying the subscribed abnormal user, so that the user is prevented from perceiving the abnormal user and checking after complaints occur, the timeliness of finding the problem is improved, the abnormal user is convenient to repair in time, and the service experience of the user is improved.

The embodiment of the subscription anomaly user identification device provided by the invention can be specifically used for executing the processing flow of the embodiment of the method, and the functions of the embodiment of the method are not repeated herein, and can be referred to in the detailed description of the embodiment of the method.

Referring to fig. 3, a schematic diagram of the physical structure of an electronic device according to an embodiment of the present invention is shown. As shown in fig. 3, the electronic device 300 may include: a processor (processor) 301, a memory (memory) 302, and a bus 303, wherein the processor 301 and the memory 302 communicate with each other through the bus 303.

The processor 301 may call a computer program in the memory 302 to perform the method provided by the method embodiment shown in fig. 1, for example, including:

In another embodiment, the abnormal scene signaling feature model includes:

In another embodiment, the processor 301, when executing the computer program, implements the following method: the screening of candidate subscribed abnormal users according to a preset abnormal scene signaling feature model and long term evolution voice VoLTE service signaling data of each user comprises the following steps:

In another embodiment, the processor 301, when executing the computer program, implements the following method: the subscription inquiry is carried out on each subscription gateway networking element corresponding to the candidate subscription abnormal user, and the identification of the subscription abnormal user is carried out according to the subscription inquiry result, which comprises the following steps:

In another embodiment, the processor 301, when executing the computer program, implements the following method: the method further comprises the steps of:

The electronic device 300 provided by the embodiment of the invention has at least the following technical effects: screening candidate signing abnormal users according to a preset abnormal scene signaling feature model and long term evolution voice VoLTE service signaling data of each user; and carrying out subscription inquiry on each subscription gateway network element corresponding to the candidate subscription abnormal user, and identifying the subscription abnormal user according to the subscription inquiry result. In this way, the voice over LTE service signaling data is used for actively identifying the subscribed abnormal user, so that the user is prevented from perceiving the abnormal user and checking after complaints occur, the timeliness of finding the problem is improved, the abnormal user is convenient to repair in time, and the service experience of the user is improved.

Embodiments of the present invention disclose a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, enable the computer to perform the methods provided by the method embodiments described above, for example comprising:

screening candidate signing abnormal users according to a preset abnormal scene signaling feature model and long term evolution voice VoLTE service signaling data of each user; and carrying out subscription inquiry on each subscription gateway network element corresponding to the candidate subscription abnormal user, and identifying the subscription abnormal user according to the subscription inquiry result.

Embodiments of the present invention provide a non-transitory computer-readable storage medium storing a computer program that causes the computer to execute the methods provided by the above-described method embodiments, for example, including:

Further, the logic instructions in the memory described above may be implemented in the form of software functional units and stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.

From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform the method described in the respective embodiments or some parts of the embodiments.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. The subscription abnormal user identification method is characterized by comprising the following steps of:

carrying out subscription inquiry on each subscription gateway networking element corresponding to the candidate subscription abnormal user, and identifying the subscription abnormal user according to the subscription inquiry result;

the abnormal scene signaling feature model comprises:

2. The method of claim 1, wherein the screening candidate subscribed abnormal users according to the preset abnormal scene signaling feature model and the long term evolution voice VoLTE service signaling data of each user comprises:

3. The method according to claim 2, wherein identifying the calling number or the called number of the VoLTE-originated service as the candidate subscribed abnormal user matching the first abnormal scene signaling feature model if the data matching the first signaling feature exists in the signaling data of the VoLTE-originated service comprises:

If the signaling data of the VoLTE service has the data matched with the first signaling characteristic, judging whether the first split network element is a calling side VoLTE AS or not;

if yes, identifying the calling number of the VoLTE service as a candidate abnormal subscription user; if not, the called number of the VoLTE service is identified as the candidate abnormal subscription user.

4. A method according to claim 2 or 3, wherein the performing subscription inquiry on each subscription gateway network element corresponding to the candidate abnormal subscription user, and performing identification of the abnormal subscription user according to the subscription inquiry result, includes:

5. The method according to claim 4, wherein the method further comprises:

6. The method of claim 5, wherein the method further comprises:

7. A subscription anomaly user identification device, comprising:

The abnormal user identification unit is used for carrying out subscription inquiry on each subscription related network element corresponding to the candidate subscription abnormal user, and carrying out identification of the subscription abnormal user according to the subscription inquiry result;

the abnormal scene signaling feature model comprises:

8. An electronic device comprising a processor, a memory, and a bus, wherein:

The processor invokes a computer program in memory to perform the steps of the method according to any of claims 1-6.

9. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, carries out the steps of the method according to any one of claims 1-6.