CN110730459B

CN110730459B - Method and related device for initiating near field communication authentication

Info

Publication number: CN110730459B
Application number: CN201911023105.8A
Authority: CN
Inventors: 刘磊
Original assignee: Alipay Hangzhou Information Technology Co Ltd
Current assignee: Alipay Hangzhou Information Technology Co Ltd
Priority date: 2019-10-25
Filing date: 2019-10-25
Publication date: 2021-05-28
Anticipated expiration: 2039-10-25
Also published as: TWI789586B; TW202118320A; WO2021077828A1; CN110730459A

Abstract

The embodiment of the specification provides a near field communication authentication initiating method and a related device. The method comprises the following steps: and the terminal equipment collects the user behavior characteristic sequence. And the terminal equipment sends the user behavior characteristic sequence to a cloud server. And the cloud server carries out anomaly detection on the user behavior feature sequence based on an anomaly detection model, wherein the anomaly detection model is obtained by training based on the historical user behavior feature sequence of the user in at least one terminal device. And the cloud server sends the abnormity detection result of the abnormity detection model to the terminal equipment. And the terminal equipment determines whether to initiate NFC authentication to Near Field Communication (NFC) authentication equipment or not based on the abnormal detection result.

Description

Method and related device for initiating near field communication authentication

Technical Field

The present invention relates to the field of data processing technologies, and in particular, to a method and a related apparatus for initiating near field communication authentication.

Background

Near Field Communication (NFC) is a short-distance high-frequency wireless Communication technology, and with the popularization of mobile consumer electronics such as smart phones, NFC systems with low energy consumption and high data transmission speed are widely applied in the fields of mobile payment, self-purchase and ticket-buying, entrance guard and the like.

At present, NFC security authentication belongs to a static authentication mode. In this way, the authentication information is fixed and does not pose a high risk once intercepted. In view of this, how to implement dynamic NFC security authentication is a technical problem that needs to be solved urgently at present.

Disclosure of Invention

An object of an embodiment of the present disclosure is to provide a method and a related apparatus for initiating NFC authentication, which can implement dynamic NFC security authentication.

In order to achieve the above object, the embodiments of the present specification are implemented as follows:

in a first aspect, a method for initiating near field communication authentication is provided, including:

the method comprises the steps that terminal equipment collects a user behavior characteristic sequence;

the terminal equipment sends the user behavior characteristic sequence to a cloud server;

the cloud server carries out anomaly detection on the user behavior feature sequence based on an anomaly detection model, wherein the anomaly detection model is obtained by training based on historical user behavior feature sequences of users in at least one terminal device;

the cloud server sends an abnormality detection result of the abnormality detection model to the terminal equipment;

and the terminal equipment determines whether to initiate NFC authentication to Near Field Communication (NFC) authentication equipment or not based on the abnormal detection result.

In a second aspect, a method for initiating near field communication authentication is provided, including:

the terminal equipment sends the user behavior feature sequence to a cloud server, so that the cloud server carries out anomaly detection on the user behavior feature sequence based on an anomaly detection model, and sends an anomaly detection result of the anomaly detection model to the terminal equipment;

In a third aspect, a method for initiating near field communication authentication is provided, including:

the method comprises the steps that a cloud server obtains a user behavior characteristic sequence collected by terminal equipment;

and the cloud server sends the abnormal detection result of the abnormal detection model to the terminal equipment, so that the terminal equipment determines whether to initiate NFC authentication to NFC authentication equipment for near field communication based on the abnormal detection result.

In a fourth aspect, an initiating device for near field communication authentication is provided, including:

the acquisition module acquires a user behavior characteristic sequence based on the terminal equipment;

the first sending module is used for sending the user behavior characteristic sequence to a cloud server based on the terminal equipment;

the anomaly detection module is used for carrying out anomaly detection on the user behavior characteristic sequence based on an anomaly detection model by the cloud server, wherein the anomaly detection model is obtained by training based on the historical user behavior characteristic sequence of the user in at least one terminal device;

the second sending module is used for sending the abnormity detection result of the abnormity detection model to the terminal equipment based on the cloud server;

and the execution module is used for determining whether to initiate NFC authentication to the NFC authentication equipment based on the terminal equipment according to the abnormal detection result.

In a fifth aspect, a terminal device is provided, which includes:

the acquisition module is used for acquiring a user behavior characteristic sequence;

the sending module is used for sending the user behavior characteristic sequence to a cloud server, so that the cloud server carries out abnormity detection on the user behavior characteristic sequence based on an abnormity detection model, and sends an abnormity detection result of the abnormity detection model to the terminal equipment;

and the execution module is used for determining whether to initiate NFC authentication to the NFC authentication equipment based on the abnormal detection result.

In a sixth aspect, a cloud server is provided, including:

the acquisition module is used for acquiring a user behavior characteristic sequence acquired by the terminal equipment;

the cloud server carries out anomaly detection on the user behavior characteristic sequence based on an anomaly detection model, wherein the anomaly detection model is obtained by training based on the historical user behavior characteristic sequence of the user in at least one terminal device;

and the sending module is used for sending the abnormal detection result of the abnormal detection model to the terminal equipment so that the terminal equipment determines whether to initiate NFC authentication to NFC authentication equipment based on the abnormal detection result.

In a seventh aspect, an electronic device is provided that includes: a memory, a processor, and a computer program stored on the memory and executable on the processor, the computer program being executed by the processor to:

acquiring a user behavior characteristic sequence based on terminal equipment;

sending the user behavior feature sequence to a cloud server based on the terminal equipment;

performing anomaly detection on the user behavior feature sequence based on an anomaly detection model based on the cloud server, wherein the anomaly detection model is obtained by training based on historical user behavior feature sequences of users in at least one terminal device;

sending an abnormality detection result of the abnormality detection model to the terminal device based on the cloud server;

and determining whether to initiate NFC authentication to Near Field Communication (NFC) authentication equipment or not based on the terminal equipment according to the abnormal detection result.

In an eighth aspect, a computer readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:

acquiring a user behavior characteristic sequence based on terminal equipment;

Based on the scheme of the embodiment of the specification, the terminal device collects the user behavior characteristic sequence in the using process of the user, uploads the user behavior characteristic sequence to the cloud server, and the cloud server trains the abnormality detection model. When the terminal equipment needs to initiate NFC authentication, the cloud server carries out abnormity detection on the current user behavior characteristic sequence based on the abnormity detection model, and feeds an abnormity detection result back to the terminal equipment, and the terminal equipment determines whether to initiate the NFC authentication or not according to the abnormity detection result. For example, when the abnormality detection result indicates abnormality, initiation of NFC authentication is rejected. Obviously, the scheme of the embodiment of the present specification introduces a dynamic security authentication manner before the NFC authentication is initiated, thereby improving the security of the NFC authentication. In addition, the whole dynamic security authentication process can be carried out without perception of the user, and the use experience of the user on the terminal equipment cannot be influenced.

Drawings

In order to more clearly illustrate the embodiments of the present specification or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only some embodiments described in the embodiments of the present specification, and for those skilled in the art, other drawings can be obtained according to the drawings without any creative efforts.

Fig. 1 is a first flowchart of a method for initiating near field communication authentication provided in an embodiment of the present specification.

Fig. 2 is a second flowchart of a method for initiating near field communication authentication provided in an embodiment of the present specification.

Fig. 3 is a third flowchart of an initiation method of near field communication authentication provided in an embodiment of the present specification.

Fig. 4 is a fourth flowchart of an initiation method of near field communication authentication provided in an embodiment of the present specification.

Fig. 5 is a schematic structural diagram of an initiating device for near field communication authentication provided in an embodiment of the present specification.

Fig. 6 is a schematic structural diagram of a terminal device provided in an embodiment of this specification.

Fig. 7 is a schematic structural diagram of a cloud server provided in an embodiment of the present specification.

Fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure.

Detailed Description

In order to make those skilled in the art better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only a part of the embodiments of the present specification, and not all of the embodiments. All other embodiments obtained by a person skilled in the art based on the embodiments in the present specification without any inventive step should fall within the scope of protection of the present specification.

As mentioned above, the current NFC security authentication belongs to a static authentication method. In this way, the authentication information is fixed and does not pose a high risk once intercepted. To improve security, this document aims to provide a technical solution for implementing dynamic NFC security authentication.

Fig. 1 is a flowchart of an initiation method of near field communication authentication according to an embodiment of the present specification. The method shown in fig. 1 may be performed by a corresponding apparatus, comprising:

and step S102, the terminal equipment collects a user behavior characteristic sequence.

The terminal device may include, but is not limited to: common user personal equipment such as a PC, a mobile phone, a PAD, an intelligent bracelet, intelligent glasses and the like. Obviously, such terminal devices generally have a function of collecting a user behavior feature sequence.

The user behavior characteristic sequence can reflect the habit characteristics of the user using the terminal equipment. By way of exemplary introduction, the user behavior feature sequence may include, but is not limited to:

the user dynamic motion trajectory sequence, for example, the walking frequency, the walking stride and the like of the user at ordinary times, is identified by a gravity sensor, a gyroscope sensor and the like of the terminal device.

The user dynamic touch sequence, for example, the frequency, granularity, etc. of the user touch the screen of the terminal device, is identified by a pressure sensor built in the terminal screen.

The user dynamic application interaction sequence, for example, the usage habit, usage preference, etc. of the user for the application program, is obtained from the system log of the terminal device.

And step S104, the terminal equipment sends the user behavior characteristic sequence to a cloud server.

The terminal device may send the user behavior feature sequence to the cloud server based on any network system (e.g., a 4G mobile network, a 5G mobile network, etc.), which is not specifically limited in this embodiment of the present disclosure.

In addition, the user can also specify a target terminal device which is responsible for interacting with the cloud server. In this step, the terminal device may send the collected user behavior feature sequence to the target terminal device, and the target terminal device further forwards the user behavior feature sequence to the cloud server.

And S106, the cloud server carries out anomaly detection on the user behavior feature sequence based on an anomaly detection model, wherein the anomaly detection model is obtained based on historical user behavior feature sequence training of the user in at least one terminal device.

Specifically, the terminal device sends an auxiliary authentication request to the cloud server in the resource processing process of the user. And the cloud server acquires the user behavior characteristic sequence within a preset time period at the moment of receiving the auxiliary authentication request according to the auxiliary authentication request, and inputs the user behavior characteristic sequence into the abnormality detection model.

It should be understood that the predetermined time period described herein should be similar to the time when the cloud server receives the auxiliary authentication request, that is, the cloud server determines the current user behavior feature sequence from the acquired user behavior feature sequences after receiving the auxiliary authentication request. Of course, the predetermined time period may be a time after the cloud server receives the auxiliary authentication request, or may be a time before the cloud server receives the auxiliary authentication request, and the embodiment of the present specification is not particularly limited.

In addition, the time length of the predetermined time period can be flexibly set. For example, the time length of the predetermined period is set according to the frequency of acquiring the user behavior feature from the terminal device. By way of exemplary introduction, assuming that the cloud server acquires the user behavior feature sequence from the terminal device every 24 hours, the time length corresponding to the predetermined time period may be 24 hours. That is, when receiving an auxiliary authentication request initiated by a target terminal device, the cloud server determines the user behavior characteristics acquired in the last day as the current user behavior characteristics.

The anomaly detection model is obtained by training based on a historical behavior feature sequence of a user in at least one terminal device (the user can be associated with at least one terminal device to be responsible for collecting the user behavior feature sequence), and the current user behavior feature sequence and the historical user behavior feature sequence can be compared to judge whether anomaly occurs or not. It should be noted that the implementation manner of the anomaly detection model is not unique, and as long as the anomaly detection model has a classification function, the anomaly detection model can be applied to the scheme of the embodiment of the present specification.

Step S108, the cloud server sends the abnormal detection result of the abnormal detection model to the terminal equipment.

In this step, the cloud server may directly send the anomaly detection result to the terminal device. Or, the cloud server may send the anomaly detection result to a target terminal device specified by the user, and the target terminal device further forwards the anomaly detection result to the terminal device.

Step S110, the terminal device determines whether to initiate NFC authentication to the NFC authentication device based on the anomaly detection result.

Specifically, if the anomaly detection result indicates that the user is not anomalous, the terminal device initiates NFC authentication to the NFC device, otherwise, the terminal device initiates identity authentication to the user. And if the user passes the identity authentication, the terminal equipment initiates the NFC authentication to the NFC equipment, otherwise, the terminal equipment refuses to initiate the NFC authentication to the NFC equipment. It should be understood that the NFC device described herein is a device that performs NFC authentication on a terminal device, such as an autonomous ticket vending machine, a mobile payment device, or the like.

As can be seen from the security authentication method shown in fig. 1: based on the scheme of the embodiment of the specification, the terminal device collects the user behavior characteristic sequence in the using process of the user, uploads the user behavior characteristic sequence to the cloud server, and the cloud server trains the abnormality detection model. When the terminal equipment needs to initiate NFC authentication, the cloud server carries out abnormity detection on the current user behavior characteristic sequence based on the abnormity detection model, and feeds an abnormity detection result back to the terminal equipment, and the terminal equipment determines whether to initiate the NFC authentication or not according to the abnormity detection result. For example, when the abnormality detection result indicates abnormality, initiation of NFC authentication is rejected. Obviously, the scheme of the embodiment of the present specification introduces a dynamic security authentication manner before the NFC authentication is initiated, thereby improving the security of the NFC authentication. In addition, the whole dynamic security authentication process can be carried out without perception of the user, and the use experience of the user on the terminal equipment cannot be influenced.

The following describes a security authentication method according to an embodiment of the present specification in detail.

The method aims to dynamically acquire the user behavior characteristic sequence through one or more terminal devices associated with a user, analyze the dynamic behavior of the user in real time based on the high-speed transmission capability of a network, and model and depict the user behavior attributes through an artificial intelligence method. If the user behavior is found to be abnormal (the user behavior attribute is not accordant with the user behavior attribute constructed by the history), a preset deep identity authentication process is started. And after the user passes the identity authentication, the terminal equipment further initiates the NFC authentication.

The method of the embodiment of the present specification includes the following main processes:

the terminal equipment periodically collects a user behavior characteristic sequence in the using process of a user according to a preset data synchronization rule and sends the user behavior characteristic sequence to the cloud server.

Optionally, the message sent by the terminal device to the user behavior feature sequence includes, in addition to the user behavior feature sequence, acquisition time corresponding to the user behavior feature sequence, so as to conveniently indicate that the cloud server can determine the current user behavior feature sequence, that is, the user behavior feature sequence belonging to the preset time period, based on the acquisition time corresponding to the user behavior feature sequence.

And after receiving the user behavior characteristic sequence, the cloud server adds the user behavior characteristic sequence serving as training data to the training data set, and trains the anomaly detection model based on the training data in the training data set when a training condition is triggered.

Wherein the training condition trigger may include, but is not limited to, at least one of:

and reaching a preset training period of the anomaly detection model. That is, the cloud server may periodically train the anomaly detection model using the training data in the training data set.

And the incremental training data of the training data set relative to the abnormal detection model trained last time reaches a preset threshold value. That is, the cloud server trains the abnormality detection model using the training data in the training data set when a certain number of new training data are accumulated in the training data set.

Obviously, based on the training conditions, the cloud server can perform iterative update on the abnormal model in real time to dynamically depict the user behavior attributes, which is also the basis for realizing dynamic authentication.

In a specific training process, the cloud server may use the user behavior feature sequence as an input of the anomaly detection model, and use the user identifier of the user as an output of the anomaly detection model, so as to train the anomaly detection model. In practical application after training, the current user behavior characteristic sequence collected by the terminal equipment can be input into the anomaly detection model. If the user identification used in the original training process is not output by the anomaly detection model, the anomaly is represented; otherwise, it indicates that no exception has occurred.

Or, the cloud server may use the user behavior feature sequence and the corresponding user identifier as input of the anomaly detection model, and use the specified anomaly detection result as output of the anomaly detection model, so as to train the anomaly detection model. In practical application after training, the current user behavior feature sequence and the corresponding user identification collected by the terminal equipment can be input into the anomaly detection model. If the abnormal detection model does not output the specified abnormal detection result used in the original training process, the abnormal detection result is represented; otherwise, it indicates that no exception has occurred.

The above is a process of dynamically training the anomaly detection model by the cloud server through the user behavior characteristic sequence uploaded by the terminal device. Meanwhile, if the terminal equipment needs to initiate the NFC authentication, an auxiliary authentication request can be sent to the cloud server.

After receiving the auxiliary authentication request, the cloud server determines a preset time period associated with the auxiliary authentication request time, and inputs a user behavior characteristic sequence which is acquired from the terminal equipment and belongs to the preset time period into the abnormality detection model, so that the abnormality detection model performs abnormality detection on the current user behavior characteristics.

And then, the cloud server feeds back the abnormity detection result of the abnormity detection model to the terminal equipment.

And if the abnormal detection result indicates that the user is not abnormal, the terminal equipment initiates NFC authentication to the NFC equipment, otherwise, the terminal equipment initiates identity authentication to the user so as to further confirm whether the current user is a legal user.

And if the user passes the identity authentication, the terminal equipment initiates NFC authentication to the NFC equipment, otherwise, the terminal equipment refuses to initiate the NFC authentication to the NFC equipment.

In addition, after the user passes the identity authentication, the terminal device can also send the identity authentication result to the cloud server, so that the cloud server takes the user behavior feature sequence as training data for subsequently training the anomaly detection model to update the anomaly detection model.

The following provides an exemplary description of the method according to the embodiments of the present disclosure, with reference to application scenarios.

In the application scenario, the user completes payment by using the NFC payment function of the terminal device. As shown in fig. 2, the corresponding method flow includes:

the terminal equipment periodically collects a user behavior characteristic sequence in the resource processing process of the terminal equipment used by a user according to a preset data synchronization rule, and sends the user behavior characteristic sequence to a cloud server of the payment application. Among other things, resource processing may include the processing of funds transfers, such as collections, transfers, payments, and the like. If the terminal device is a PC, the user behavior feature sequence may include: the strength distribution of keyboard knocking, the mouse clicking behavior, the mouse clicking rule and other characteristics. If the terminal device is a mobile device, the user behavior feature sequence may include: the user can further include characteristics such as the dynamics distribution of mobile device fingertip interaction, click behavior mode law simultaneously: some basic characteristics collected by mobile device sensors (gravity sensors, angular velocity sensors, temperature sensors).

And when the obtained user history uses the payment application, the cloud server takes the user behavior characteristic sequence in the resource processing process as training data to train the abnormality detection model, so that the abnormality detection model describes the habit of the user using the payment application to process the resource.

When the user uses the NFC payment function of the payment application of the terminal device, the payment application controls the terminal device and initiates an auxiliary authentication request to the cloud server.

After receiving the auxiliary authentication request, the cloud server determines a preset time period close to the receiving time of the auxiliary authentication request, and takes the user behavior characteristic sequence belonging to the preset time period as a current user behavior characteristic sequence. And then, the cloud server inputs the current user behavior characteristic sequence into an anomaly detection model so as to detect the anomaly of the user.

And then, after obtaining the abnormal detection result output by the abnormal detection model, the cloud server feeds the abnormal detection result back to the terminal equipment.

And after receiving the abnormal detection result, the terminal equipment determines whether to initiate NFC payment or not based on the abnormal detection result. And if the abnormity detection result indicates that the abnormity does not exist, the payment application starts the NFC payment function to the user, and the user completes the payment operation based on the NFC payment function. And if the abnormity detection result indicates abnormity, the payment application calls functions configured by the terminal equipment, such as fingerprint authentication, voiceprint authentication and the like, and initiates deep copy authentication to the user. And if the user passes the deep share authentication, the payment application starts the NFC payment function to the user, otherwise, the payment application disables the NFC payment function, so that the user cannot complete the payment operation.

The above is a description of the method of the embodiments of the present specification. It will be appreciated that appropriate modifications may be made without departing from the principles outlined herein, and such modifications are intended to be included within the scope of the embodiments herein.

Fig. 3 is a schematic flowchart of a security verification method on a terminal device side in an embodiment of this specification, where the method includes:

step S302, the terminal device collects a user behavior characteristic sequence.

Step S304, the terminal device sends the user behavior feature sequence to the cloud server, so that the cloud server carries out abnormity detection on the user behavior feature sequence based on the abnormity detection model, and sends an abnormity detection result of the abnormity detection model to the terminal device.

Step S306, the terminal device determines whether to initiate NFC authentication to the NFC authentication device based on the anomaly detection result.

Based on the security authentication method shown in fig. 3, the terminal device collects the user behavior feature sequence in the user using process, uploads the user behavior feature sequence to the cloud server, and the cloud server trains the anomaly detection model. When NFC authentication needs to be initiated, the terminal equipment requests the cloud server to perform anomaly detection on the user behavior characteristic sequence of the current situation based on an anomaly detection model, an anomaly detection result is fed back to the terminal equipment, and the terminal equipment determines whether to initiate the NFC authentication based on the anomaly detection result. Obviously, the scheme of the embodiment of the present specification introduces a dynamic security authentication manner before the NFC authentication is initiated, thereby improving the security of the NFC authentication. In addition, the whole dynamic security authentication process can be carried out without perception of the user, and the use experience of the user on the terminal equipment cannot be influenced.

Fig. 4 is a schematic flowchart of a security verification method on a cloud server side in an embodiment of the present specification, where the security verification method includes:

step S402, the cloud server obtains a user behavior characteristic sequence collected by the terminal equipment.

Step S404, the cloud server carries out anomaly detection on the user behavior feature sequence based on an anomaly detection model, wherein the anomaly detection model is obtained based on historical user behavior feature sequence training of a user in at least one terminal device.

Step S406, the cloud server sends the anomaly detection result of the anomaly detection model to the terminal device, so that the terminal device determines whether to initiate NFC authentication to the NFC authentication device based on the anomaly detection result.

Based on the security authentication method shown in fig. 4, the cloud server trains the anomaly detection model by using the user behavior feature sequence acquired by the terminal device in the user using process, so that the anomaly detection model describes the user behavior attribute of the user. When the terminal equipment needs to initiate NFC authentication, the cloud server carries out abnormity detection on the user behavior characteristic sequence of the current situation based on the abnormity detection model, feeds an abnormity detection result back to the terminal equipment, and the terminal equipment determines whether to initiate the NFC authentication or not according to the abnormity detection result. Obviously, the scheme of the embodiment of the present specification introduces a dynamic security authentication manner before the NFC authentication is initiated, thereby improving the security of the NFC authentication. In addition, the whole dynamic security authentication process can be carried out without perception of the user, and the use experience of the user on the terminal equipment cannot be influenced.

Fig. 5 is a security authentication apparatus 500 according to an embodiment of the present specification, including:

an acquisition module 510, which acquires a user behavior feature sequence based on a terminal device;

the first sending module 520 is used for sending the user behavior feature sequence to a cloud server based on the terminal equipment;

an anomaly detection module 530, configured to perform anomaly detection on the user behavior feature sequence based on an anomaly detection model based on the cloud server, where the anomaly detection model is obtained based on historical user behavior feature sequence training of a user in at least one terminal device.

A second sending module 540, configured to send an anomaly detection result of the anomaly detection model to the terminal device based on the cloud server.

And the executing module 550 determines whether to initiate NFC authentication to the NFC authentication device based on the terminal device according to the abnormal detection result.

As can be appreciated by the initiating device of near field communication authentication shown in fig. 5: based on the scheme of the embodiment of the specification, the terminal device collects the user behavior characteristic sequence in the using process of the user, uploads the user behavior characteristic sequence to the cloud server, and the cloud server trains the abnormality detection model. When the terminal equipment needs to initiate NFC authentication, the cloud server carries out abnormity detection on the current user behavior characteristic sequence based on the abnormity detection model, and feeds an abnormity detection result back to the terminal equipment, and the terminal equipment determines whether to initiate the NFC authentication or not according to the abnormity detection result. For example, when the abnormality detection result indicates abnormality, initiation of NFC authentication is rejected. Obviously, the scheme of the embodiment of the present specification introduces a dynamic security authentication manner before the NFC authentication is initiated, thereby improving the security of the NFC authentication. In addition, the whole dynamic security authentication process can be carried out without perception of the user, and the use experience of the user on the terminal equipment cannot be influenced.

Optionally, when executed specifically, the executing module 550 implements the following steps:

if the abnormal detection result indicates that the user is not abnormal, the terminal equipment initiates NFC authentication to Near Field Communication (NFC) equipment, otherwise, the terminal equipment initiates identity authentication to the user; and if the user passes the identity authentication, the terminal equipment initiates NFC authentication to the NFC equipment, otherwise, the terminal equipment refuses to initiate the NFC authentication to the NFC equipment.

Optionally, the executing module 550 is further configured to:

and after the NFC authentication is refused to be initiated to the NFC equipment, disabling the NFC function of the terminal equipment, wherein the activation of the NFC function of the terminal equipment requires the identity authentication of a user.

Optionally, the initiating device of near field communication authentication further includes:

and the auxiliary request module is used for sending an auxiliary authentication request to the cloud server when the NFC authentication is prepared to be initiated to the NFC authentication equipment. The cloud server acquires a user behavior feature sequence within a preset time period at the receiving moment of the auxiliary authentication request, and inputs the user behavior feature sequence within the preset time period to an anomaly detection model so as to perform anomaly detection on the user behavior feature sequence within the preset time period.

Optionally, the time length of the predetermined time period is determined based on a frequency of the cloud server acquiring the user behavior feature sequence.

Optionally, the terminal device is installed with a payment application, and the auxiliary authentication request is initiated by the payment application controlling the terminal device when the user uses the payment application to perform resource processing.

Optionally, the acquiring module 510 specifically acquires a user behavior feature sequence during resource processing performed by the user at the end of execution.

Optionally, the user behavior feature sequence includes at least one of:

the method comprises a user motion track characteristic sequence, a user positioning track characteristic sequence, a user touch characteristic sequence and a user application interaction characteristic sequence.

Obviously, the initiating device of near field communication authentication in the embodiments of the present specification may be used as the executing main body of the initiating method of near field communication authentication shown in fig. 1, and thus can implement the function of the initiating method implemented in fig. 1. Since the principle is the same, the detailed description is omitted here.

Fig. 6 is a schematic structural diagram of a terminal device 600 according to an embodiment of the present specification, including:

and the acquisition module 610 acquires the user behavior characteristic sequence.

The sending module 620 is configured to send the user behavior feature sequence to a cloud server, so that the cloud server performs anomaly detection on the user behavior feature sequence based on an anomaly detection model, and sends an anomaly detection result of the anomaly detection model to the terminal device.

The executing module 630 determines whether to initiate NFC authentication to the NFC authentication device based on the anomaly detection result.

The terminal device in the embodiment of the description collects the user behavior characteristic sequence in the user using process, uploads the user behavior characteristic sequence to the cloud server, and the cloud server trains the anomaly detection model. When NFC authentication needs to be initiated, the terminal equipment requests the cloud server to perform anomaly detection on the user behavior characteristic sequence of the current situation based on an anomaly detection model, an anomaly detection result is fed back to the terminal equipment, and the terminal equipment determines whether to initiate the NFC authentication based on the anomaly detection result. Obviously, the scheme of the embodiment of the present specification introduces a dynamic security authentication manner before the NFC authentication is initiated, thereby improving the security of the NFC authentication. In addition, the whole dynamic security authentication process can be carried out without perception of the user, and the use experience of the user on the terminal equipment cannot be influenced.

Obviously, the terminal device of the embodiment of the present specification may serve as an execution subject of the initiation method of near field communication authentication shown in fig. 3, and thus can implement the function implemented in fig. 3 by the initiation method. Since the principle is the same, the detailed description is omitted here.

Fig. 7 is a schematic structural diagram of a cloud server 700 according to an embodiment of the present specification, including:

the obtaining module 710 obtains a user behavior feature sequence acquired by the terminal device;

the anomaly detection module 720 is used for carrying out anomaly detection on the user behavior feature sequence by the cloud server based on an anomaly detection model, wherein the anomaly detection model is obtained by training based on the historical user behavior feature sequence of the user in at least one terminal device;

the sending module 730 sends the abnormal detection result of the abnormal detection model to the terminal device, so that the terminal device determines whether to initiate NFC authentication to the NFC authentication device based on the abnormal detection result.

The cloud server in the embodiment of the description trains the anomaly detection model by using the user behavior feature sequence acquired by the terminal device in the user using process, so that the anomaly detection model describes the user behavior attribute of the user. When the terminal equipment needs to initiate NFC authentication, the cloud server carries out abnormity detection on the user behavior characteristic sequence of the current situation based on the abnormity detection model, feeds an abnormity detection result back to the terminal equipment, and the terminal equipment determines whether to initiate the NFC authentication or not according to the abnormity detection result. Obviously, the scheme of the embodiment of the present specification introduces a dynamic security authentication manner before the NFC authentication is initiated, thereby improving the security of the NFC authentication. In addition, the whole dynamic security authentication process can be carried out without perception of the user, and the use experience of the user on the terminal equipment cannot be influenced.

Obviously, the cloud server of the embodiment of the present specification may serve as an execution subject of the initiation method of near field communication authentication shown in fig. 4, and thus the functions of the initiation method implemented in fig. 4 can be implemented. Since the principle is the same, the detailed description is omitted here.

Fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present specification. Referring to fig. 8, at a hardware level, the electronic device includes a processor, and optionally further includes an internal bus, a network interface, and a memory. The Memory may include a Memory, such as a Random-Access Memory (RAM), and may further include a non-volatile Memory, such as at least 1 disk Memory. Of course, the electronic device may also include hardware required for other services.

The processor, the network interface, and the memory may be connected to each other via an internal bus, which may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 8, but that does not indicate only one bus or one type of bus.

And the memory is used for storing programs. In particular, the program may include program code comprising computer operating instructions. The memory may include both memory and non-volatile storage and provides instructions and data to the processor.

The processor reads the corresponding computer program from the nonvolatile memory into the memory and then runs the computer program, and the security authentication device is formed on the logic level. The processor is used for executing the program stored in the memory and is specifically used for executing the following operations:

and acquiring a user behavior characteristic sequence based on the terminal equipment.

And sending the user behavior feature sequence to a cloud server based on the terminal equipment.

And carrying out anomaly detection on the user behavior feature sequence based on an anomaly detection model based on the cloud server, wherein the anomaly detection model is obtained by training based on the historical user behavior feature sequence of the user in at least one terminal device.

And sending the abnormity detection result of the abnormity detection model to the terminal equipment based on the cloud server.

The security authentication method disclosed in the embodiment shown in fig. 1 of the present specification may be applied to or implemented by a processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present specification may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the embodiments of the present specification may be embodied directly in a hardware decoding processor, or in a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.

It should be understood that the electronic device according to the embodiment of the present disclosure may implement the functions of the above-described apparatus according to the embodiment shown in fig. 1 and fig. 2, and will not be described herein again.

Of course, besides the software implementation, the electronic device in this specification does not exclude other implementations, such as logic devices or a combination of software and hardware, and the like, that is, the execution subject of the following processing flow is not limited to each logic unit, and may also be hardware or logic devices.

Furthermore, the present specification embodiments also propose a computer-readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a portable electronic device comprising a plurality of application programs, are capable of causing the portable electronic device to perform the method of the embodiment shown in fig. 1, and in particular to perform the following method:

It should be understood that the above-mentioned instructions, when executed by a portable electronic device comprising a plurality of application programs, can enable the initiating device described above to implement the functions of the embodiment shown in fig. 1, and will not be described in detail herein.

As will be appreciated by one skilled in the art, embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, the description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.

The above description is only an example of the present specification, and is not intended to limit the present specification. Various modifications and alterations to this description will become apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present specification should be included in the scope of the claims of the present specification. Moreover, all other embodiments obtained by a person skilled in the art without making any inventive step shall fall within the scope of protection of this document.

Claims

1. A method of initiating near field communication authentication, comprising:

the terminal equipment dynamically acquires a user behavior characteristic sequence;

the terminal equipment sends an auxiliary authentication request to the cloud server when preparing to initiate NFC authentication to NFC authentication equipment;

the cloud server acquires a user behavior feature sequence in a preset time period at the receiving moment of the auxiliary authentication request, inputs the user behavior feature sequence in the preset time period to an anomaly detection model so as to perform anomaly detection on the user behavior feature sequence in the preset time period, wherein the anomaly detection model is obtained based on historical user behavior feature sequence training of a user in at least one terminal device;

2. The method of claim 1, wherein the first and second light sources are selected from the group consisting of,

the terminal device determines whether to initiate NFC authentication to a near field communication NFC authentication device based on the anomaly detection result, including:

and if the user passes the abnormal detection, the terminal equipment initiates NFC authentication to the NFC equipment, otherwise, the terminal equipment refuses to initiate the NFC authentication to the NFC equipment.

3. The method of claim 2, further comprising:

and if the user does not pass the abnormal detection, the terminal equipment disables the NFC function of the terminal equipment, wherein the activation of the NFC function of the terminal equipment requires the user to perform identity authentication.

4. The method of claim 3, further comprising:

and if the user fails the anomaly detection, the cloud server takes the user behavior feature sequence as training data for subsequently training the anomaly detection model.

5. The method of claim 1, wherein the first and second light sources are selected from the group consisting of,

the terminal equipment is provided with a payment application, and the auxiliary authentication request is initiated by the payment application when the user uses the payment application to perform resource processing.

6. The method of claim 5, wherein the first and second light sources are selected from the group consisting of,

the terminal equipment collects a user behavior characteristic sequence, and the method comprises the following steps:

and the terminal equipment acquires a user behavior characteristic sequence in the resource processing process of the user.

7. The method of any one of claims 1-6,

the sequence of user behavior features includes at least one of:

8. A method of initiating near field communication authentication, comprising:

when the terminal equipment prepares to initiate NFC authentication to NFC authentication equipment, an auxiliary authentication request is sent to the cloud server, so that the cloud server carries out abnormity detection on the user behavior characteristic sequence based on an abnormity detection model, and an abnormity detection result of the abnormity detection model is sent to the terminal equipment;

9. A method of initiating near field communication authentication, comprising:

the method comprises the steps that a cloud server dynamically obtains a user behavior characteristic sequence collected by terminal equipment;

the cloud server receives an auxiliary authentication request sent by the terminal equipment when the terminal equipment prepares to initiate NFC authentication to NFC authentication equipment;

10. An initiating device of near field communication authentication, comprising:

the acquisition module is used for dynamically acquiring a user behavior characteristic sequence based on the terminal equipment;

the auxiliary request module is used for sending an auxiliary authentication request to the cloud server based on the terminal equipment when the NFC authentication is prepared to be initiated to the NFC authentication equipment;

the anomaly detection module is used for acquiring a user behavior characteristic sequence within a preset time period at the receiving moment of the auxiliary authentication request based on the cloud server and inputting the user behavior characteristic sequence within the preset time period into an anomaly detection model so as to perform anomaly detection on the user behavior characteristic sequence within the preset time period, wherein the anomaly detection model is obtained by training based on the historical user behavior characteristic sequence of a user in at least one terminal device;

11. A terminal device, comprising:

the acquisition module is used for dynamically acquiring a user behavior characteristic sequence;

the sending module is used for sending the user behavior characteristic sequence to a cloud server;

the system comprises an auxiliary request module and a cloud server, wherein the auxiliary request module sends an auxiliary authentication request to the cloud server when preparing to initiate NFC authentication to NFC authentication equipment, so that the cloud server acquires a user behavior feature sequence within a preset time period at the receiving moment of the auxiliary authentication request, inputs the user behavior feature sequence within the preset time period to an abnormality detection model so as to perform abnormality detection on the user behavior feature sequence within the preset time period, and sends an abnormality detection result of the abnormality detection model to the terminal equipment, wherein the abnormality detection model is obtained by training based on historical user behavior feature sequences of users in at least one terminal equipment;

12. A cloud server, comprising:

the terminal equipment comprises an acquisition module, a processing module and a verification module, wherein the acquisition module is used for acquiring a user behavior characteristic sequence dynamically acquired by the terminal equipment and an auxiliary authentication request sent by the terminal equipment when the terminal equipment is ready to initiate NFC authentication to the NFC authentication equipment;

the abnormality detection module is used for acquiring a user behavior characteristic sequence in a preset time period at the receiving moment of the auxiliary authentication request, inputting the user behavior characteristic sequence in the preset time period into an abnormality detection model so as to perform abnormality detection on the user behavior characteristic sequence in the preset time period, wherein the abnormality detection model is obtained based on historical user behavior characteristic sequence training of a user in at least one terminal device;

and the sending module is used for sending the abnormal detection result of the abnormal detection model to the terminal equipment, so that the terminal equipment determines whether to initiate NFC authentication to NFC authentication equipment based on the abnormal detection result, wherein if the abnormal detection is not passed, the NFC function is forbidden.

13. An electronic device includes: a memory, a processor, and a computer program stored on the memory and executable on the processor, the computer program being executed by the processor to:

dynamically acquiring a user behavior characteristic sequence based on terminal equipment;

when the terminal equipment prepares to initiate NFC authentication to NFC authentication equipment, an auxiliary authentication request is sent to the cloud server based on the terminal equipment;

acquiring a user behavior feature sequence within a preset time period at the receiving moment of the auxiliary authentication request based on the cloud server, and inputting the user behavior feature sequence within the preset time period to an anomaly detection model to perform anomaly detection on the user behavior feature sequence within the preset time period, wherein the anomaly detection model is obtained based on historical user behavior feature sequence training of a user in at least one terminal device;

14. A computer-readable storage medium having a computer program stored thereon, which when executed by a processor, performs the steps of: