WO2019113765A1

WO2019113765A1 - Face and electrocardiogram-based payment authentication method and terminal

Info

Publication number: WO2019113765A1
Application number: PCT/CN2017/115557
Authority: WO
Inventors: 张炽成; 唐超旬
Original assignee: 福建联迪商用设备有限公司
Priority date: 2017-12-12
Filing date: 2017-12-12
Publication date: 2019-06-20
Also published as: CN108401458A

Abstract

Provided are a face and electrocardiogram-based payment authentication method and a terminal. The method comprises the following steps: determining, according to electrocardiogram information, whether a user is in a sleeping state; determining, according to facial information, whether facial image information of the facial information contains high-frequency information greater than a preset threshold; and if both determination results are negative, performing a related matching operation according to the facial image information, the electrocardiogram information, and pre-stored facial image information and electrocardiogram information of the user, and determining, according to a match result, whether payment authentication is successful. The present invention can effectively determine, according to electrocardiogram information and facial image information, whether a user is in a compelled state or a sleeping state, thereby ensuring more secure and reliable transactions. The method combines face and electrocardiogram recognition techniques, thereby greatly reducing risks of unauthorized payments, and enhancing transaction security and reliability.

Description

Payment authentication method and terminal based on face and electrocardiogram

Technical field

The present invention relates to the field of electronic payment technologies, and in particular, to a payment authentication method and a terminal based on a face and an electrocardiogram.

Background technique

With the continuous development of Internet technology, online shopping through smart mobile terminals has become an indispensable part of people's lives, which is also very convenient for people's lives. Since online shopping involves sensitive information of users, it requires a more secure payment authentication method when shopping online and making payment. The current payment authentication method mainly performs payment authentication through fingerprint or face recognition, which has the following disadvantages: biometrics Easy to be stolen: Fingerprint information is easier to take when the trader touches the item, and the non-living information, the facial image information is originally public, and it is easy to steal through video or photographing; the stolen biometrics are easy to use. In the attack, the stolen fingerprint and facial information can be used to attack the payment device by making fingerprint and image synthesis techniques respectively, thereby achieving the purpose of stealing.

technical problem

The technical problem to be solved by the present invention is that the present invention provides a payment authentication method and a terminal based on a face and an electrocardiogram, and improves the security of payment authentication.

Technical solution

In order to solve the above technical problem, the present invention provides a payment authentication method based on a face and an electrocardiogram, comprising the following steps:

S1: determining, according to the electrocardiogram information, whether the user is in a sleep state; and determining, according to the face information, whether high-frequency information greater than a preset threshold exists in the face image information included in the face information;

S2: If no, the related matching operation is performed according to the face image information, the electrocardiogram information, the reserved user face image information, and the user's electrocardiogram information, and the payment authentication is determined according to the matching result.

The present invention also provides a face and electrocardiogram-based payment authentication terminal comprising a memory, a processor, and a computer program stored on the memory and operable on the processor, the processor implementing the program to implement the following steps :

Beneficial effect

The beneficial effects of the invention are:

The invention provides a face and electrocardiogram-based payment authentication method and a terminal, which can determine whether a user is in a sleep state through the electrocardiogram information, and prevent the user from being stolen in the sleep state; the image synthesized by the computer A large number of spatial hopping occurs at the edge of the face, the edge of the eye, the edge of the mouth, etc., and there is a large amount of high-frequency information corresponding to the frequency domain, so it is determined whether the presence of the face image information is greater than a preset threshold. The high-frequency information can prevent the problem of payment authentication attack by the image information synthesized by the computer; and at the same time, the payment authentication is performed according to the electrocardiogram information and the face image information, and the security of the payment is improved by the double authentication method, and the above The ECG information is a living feature, and the attacker is not easy to camouflage the ECG to attack the payment authentication, making the payment more secure.

DRAWINGS

1 is a schematic diagram showing main steps of a face and electrocardiogram-based payment authentication method according to an embodiment of the present invention;

2 is a schematic structural diagram of a face authentication and an electrocardiogram-based payment authentication terminal according to an embodiment of the present invention;

Label description:

1, memory; 2, processor.

Embodiments of the invention

Referring to FIG. 1, the present invention provides a payment authentication method based on a face and an electrocardiogram, comprising the following steps:

It can be seen from the above description that through the electrocardiogram information, it can be determined whether the user is in a sleep state, preventing the user from being stolen by the user in the sleep state; due to the image synthesized by the computer, at the edge of the face, the edge of the eye, and the edge of the mouth A large number of spatial hopping occurs in the place where the splicing is performed, and a large amount of high frequency information exists in the frequency domain. Therefore, by determining whether there is high frequency information larger than a preset threshold in the face image information, image information synthesized by the computer can be prevented. The problem of payment authentication attack; and at the same time, according to the electrocardiogram information and the face image information, the payment authentication is performed, and the security of the payment is improved by the double authentication method, and the above-mentioned electrocardiogram information is a living feature, which can prevent theft and make payment. safer.

Further, before the S1, the method further includes:

S01: Display face specified action information required for payment verification;

S02: collecting ECG information while collecting face information; the face information includes face video information and face image information;

S03: determining whether the face motion in the face video information is consistent with the specified action;

S04: If they are consistent, step S1 is performed, otherwise the payment authentication fails.

It can be seen from the above description that the collected face information is the face video information and the face image information collected by the camera device when the user performs the corresponding face action according to the specified action information displayed, and the payment verification is improved by the above method. safety.

Further, the S02 and the S03 further include:

The face information and the electrocardiogram information are separately subjected to noise reduction and filtering processing.

As can be seen from the above description, the accuracy of data processing can be improved by the above method.

Further, the face specifying action information required for displaying the payment verification in the S01 is specifically:

The face specifying action information is randomly generated, and the specified action information is displayed.

As can be seen from the above description, by the above method, it is possible to prevent the fraudulent use of the face information at the time of last support verification to perform payment verification, thereby improving the security of payment.

Further, if the face information or the ECG information fails to be collected within the preset time, the new specified action information is randomly displayed, and the face information is collected again, and the ECG information is collected.

As apparent from the above description, by the above method, it is possible to prevent the payment authentication information from being stolen, and the security of the payment is further improved.

Further, before the S1, the method further includes:

Acquiring a plurality of first face image information in a state of being stressed, and calculating a first feature parameter of each first face image information;

Fitting all the first feature parameters to obtain a first mathematical model between the stressed state and the first feature parameter;

Obtaining multiple normal ECG information in a normal awake state, multiple sleep ECG information in a sleep state, and multiple stress ECG information in a state of being stressed;

Calculating a second characteristic parameter of each normal electrocardiogram information, a third characteristic parameter of each sleep electrocardiogram information, and a fourth characteristic parameter of each stress electrocardiogram information;

All second feature parameters corresponding to the normal awake state, all third feature parameters corresponding to the sleep state, and all fourth feature parameters corresponding to the stress state are respectively fitted to obtain corresponding mathematical models in different states.

It can be seen from the above description that the first mathematical model of the face information under the stress state and the different models corresponding to the ECG information in different states can be established by the above method, so that the user can accurately determine the state of the user and improve the payment. Security.

Further, the S1 is specifically:

Obtaining an electrocardiogram feature parameter and a face feature parameter according to the obtained electrocardiogram information and the face image information in the face information;

Determining whether the user is in a state of being coerced according to the face feature parameter and the first mathematical model, and determining whether the user is in a coerced state or a sleep state according to the electrocardiographic feature parameter and the corresponding mathematical model in different states, and determining the face Whether there is high frequency information larger than a preset threshold in the image information.

As can be seen from the above description, according to the above method, it is possible to accurately determine whether or not the use is in a state of being stressed or in a sleep state, so as to prevent the user from being misappropriated by the criminals in the state of being coerced or sleeping, causing a huge loss to the user.

Further, the S2 is specifically:

If yes, encrypting the face feature parameter and the electrocardiogram feature parameter, and sending the parameter to the server, so that the server performs significant analysis on the feature parameter corresponding to the face feature parameter and the reserved user face image information, and The characteristic parameters corresponding to the reserved user electrocardiogram information of the electrocardiogram characteristic parameter are significantly analyzed, and the significant analysis result is obtained; and according to the significance analysis result, whether the payment authentication is passed is determined.

It can be seen from the above description that the face feature parameters and the electrocardiogram feature parameters are encrypted and transmitted during the transmission process, which can prevent the user data from being stolen and cause a certain economic loss to the user; and at the same time, the saliency analysis can accurately determine the person. Whether the feature parameters corresponding to the face feature parameter and the reserved user face image information match, and can accurately determine whether the feature parameters corresponding to the ECG feature parameter and the reserved user ECG information match; the above double verification method improves the payment authentication Security.

Further, "determining whether there is high frequency information greater than a preset threshold in the face image information" is specifically:

Calculating image frequency domain information corresponding to the face image information, and determining whether there is high frequency information greater than a preset threshold in the image frequency domain information.

As can be seen from the above description, by the above method, it is possible to accurately calculate whether the face image information includes high frequency information, to prevent the image synthesized by the computer from being used for payment verification, and to improve the security of payment.

Further, before the S1, the method further includes:

Performing an authentication judgment on the preset transaction terminal and the server, and if the authentication fails, the payment authentication fails, and the transaction is ended;

If the authentication is successful, acquiring current location information of the transaction terminal;

Encrypting the current location information to obtain location encryption information;

Sending the location encryption information to the server, so that the server saves the location encryption information in preset security log information.

As can be seen from the above description, the location information in which the transaction is stored during the transaction process makes the transaction location traceable.

Referring to FIG. 2, the present invention further provides a face and electrocardiogram-based payment authentication terminal, comprising a memory 1, a processor 2, and a computer program stored on the memory 1 and operable on the processor 2, the processing When the program 2 executes the program, the following steps are implemented:

Further, the above-mentioned face and electrocardiogram-based payment authentication terminal, when the processor executes the program, before the step S1 is implemented, the method further includes:

Further, the above-mentioned face and electrocardiogram-based payment authentication terminal further includes: between S02 and S03:

Further, the face authentication and the ECG-based payment authentication terminal, wherein the face specified action information required for displaying the payment verification in the S01 is specifically:

Further, the above-mentioned face and electrocardiogram-based payment authentication terminal, when the processor executes the program, the steps further include: if the face information or the ECG information collection fails within a preset time, The new specified motion information is randomly displayed, and the ECG information is collected while the face information is re-acquired.

Further, the above-mentioned face and electrocardiogram-based payment authentication terminal further includes:

Further, the above-mentioned face and electrocardiogram-based payment authentication terminal, the S1 is specifically:

Further, the above-mentioned face and electrocardiogram-based payment authentication terminal, the S2 is specifically:

Further, the payment authentication terminal based on the face and the electrocardiogram, "determining whether there is high frequency information greater than a preset threshold in the face image information" is specifically:

Referring to FIG. 1, a first embodiment of the present invention is:

The invention provides a payment authentication method based on a face and an electrocardiogram, comprising the following steps:

S0: randomly generate facial specified action information, display the specified action information; collect face information while collecting ECG information; the face information includes face video information and face image information; After performing noise reduction and filtering processing on the ECG information, it is determined whether the face action in the face video information is consistent with the specified action; if they are consistent, step S1 is performed, otherwise the payment authentication fails;

Wherein, if the face information or the ECG information collection fails within the preset time, step S0 is re-executed;

Embodiment 2 of the present invention is:

Acquiring a plurality of first face image information in a state of being stressed, calculating a first feature parameter of each first face image information; fitting all the first feature parameters to obtaining a stressed state and a first feature parameter The first mathematical model between;

Wherein "fitting all the first characteristic parameters to obtain a first mathematical model between the stressed state and the first characteristic parameter" is specifically:

Reading the first feature parameter corresponding to each sample (first face image information), and fitting all the first feature parameters by deep learning convolutional neural network, that is, defining a neural network, collecting original data, Sorting training, correcting, and outputting results, obtaining a first mathematical model between the stressed state and the first characteristic parameter;

Obtaining multiple normal ECG information in normal awake state, multiple sleeping ECG information in sleep state, and multiple stress ECG information in stress state; calculating second characteristic parameters of each normal ECG information, each sleep a third characteristic parameter of the electrocardiogram information and a fourth characteristic parameter of each stress electrocardiogram information; all second characteristic parameters corresponding to the normal awake state, all third characteristic parameters corresponding to the sleep state, and all fourth corresponding to the stressed state The characteristic parameters are respectively fitted to obtain corresponding mathematical models in different states;

Among them, through the fitting, the corresponding mathematical models in different states are obtained. The method adopted also defines the neural network, collects the original data, and classifies all the corresponding characteristic parameters in different states by the method of deep learning convolutional neural network. By training, correcting, and outputting the results, the corresponding mathematical models in different states can be obtained.

In the payment, the default transaction terminal and the server are first authenticated. If the authentication fails, the payment authentication fails and the transaction is terminated.

If the authentication succeeds, acquiring current location information of the transaction terminal; encrypting the current location information to obtain location encryption information; and transmitting the location encryption information to a server, so that the server saves the location encryption information in a preset Security log information;

After the authentication succeeds, the face specified action information is randomly generated, and the specified action information is displayed; while the face information is collected, the ECG information is collected; the face information includes the face video information and the face image information; After the face information and the ECG information are respectively subjected to noise reduction and filtering processing, it is determined whether the face action in the face video information is consistent with the specified action; if not, the payment authentication fails; otherwise, the following steps are performed:

Determining whether the user is in a state of being coerced according to the face feature parameter and the first mathematical model, and determining whether the user is in a coerced state or a sleep state according to the electrocardiographic feature parameter and the corresponding mathematical model in different states, and determining the face Whether there is high frequency information greater than a preset threshold in the image information;

If yes, the face feature parameter and the electrocardiogram feature parameter are encrypted and sent to the server, so that the server performs the feature parameter corresponding to the face feature parameter and the reserved user face image information by the F test method. The analysis and the characteristic parameters corresponding to the ECG characteristic parameters and the reserved user ECG information are analyzed by the F-test to obtain the significance analysis results. The significant analysis results include the facial feature parameter significance analysis results and the ECG characteristics. If the sexual analysis results are insufficient, it is judged that the payment authentication is not passed, and only two significant analysis results are significant, and the payment authentication is passed.

Referring to FIG. 2, the third embodiment of the present invention is:

The present invention provides a face and electrocardiogram based payment authentication terminal comprising a memory, a processor and a computer program stored on the memory and operable on the processor, the processor implementing the program to implement the following steps:

Embodiment 4 of the present invention is:

If yes, the face feature parameter and the electrocardiogram feature parameter are encrypted and sent to the server, so that the server performs the feature parameter corresponding to the face feature parameter and the reserved user face image information by the F test method. The analysis and the characteristic parameters corresponding to the ECG characteristic parameters and the reserved user ECG information are analyzed by the F-test to obtain the significance analysis results. The significant analysis results include the facial feature parameter significance analysis results and the ECG characteristics. If the sexual analysis results are insufficient, then it is judged whether the payment authentication is passed, and only two significant analysis results are significant, and the payment authentication is passed.

Embodiment 5 of the present invention is:

The invention provides a POS machine, comprising an MCU (micro control module), a camera, an ECG acquisition module (electrocardiogram acquisition module) and a liquid crystal screen, wherein the MCU is electrically connected to the camera, the ECG acquisition module and the liquid crystal screen respectively;

1) Before leaving the factory, the POS software undergoes extensive machine learning training, including tens of thousands of face information under normal emotions and coerced face information, as well as tens of thousands of normal awake state ECGs, sleep ECGs, and under stress conditions. ECG. The recognition software fits into a calculation formula by using a deep learning convolutional neural network method for all training samples by reading specific parameters (the main steps are: defining neural networks, collecting raw data, classifying) Training, correction, and output results, and the relationship between these parameters and emotions, sleep, etc., so that the software for face recognition and ECG recognition has the ability to identify whether the source of information is under stress and sleep.

2) POS and transaction background authentication: If the authentication fails, it means that the POS has no transaction authority and ends the transaction; if the authentication is successful, it means that the POS has the transaction authority, and the encryption of the POS and the transaction background is enabled. The wireless module encrypts and uploads the current base station location at this time, and saves it as the content of the security log in the transaction background.

3) The POS prompts the trader to collect the ECG information by using the ECG acquisition device built in the POS machine or encrypted communication with the POS machine through the LCD screen, and the MCU randomly generates the face specified action (including blinking, opening mouth, turning head, etc.) The LCD screen prompts the user to collect the face information of the specified action through the camera.

4) The camera collects the face information of the trader, and at the same time, the electrocardiogram collecting device delivers the collected single-lead ECG information to the MCU of the POS machine. For an external ECG acquisition device, the MCU needs to decrypt the information to obtain the ECG plaintext information.

5) The MCU preprocesses the face information, including noise reduction and normalization processing.

6) The MCU checks the legality of the face information, including checking whether the face action is consistent with the prompt, checking whether there is high frequency information exceeding the threshold, calculating the main feature parameter, and returning the result obtained in the training in step 1 to check whether it is being If the state of coercion does not pass, it is judged as illegal information, rejected, and the transaction is terminated.

7) The MCU calculates the feature values of the face information, including the geometric features of the eyes, nose, mouth, and the like of the face.

8) The MCU encrypts the face information feature value and transmits it to the transaction background.

9) The face information of the uploaded face information and the face information of the cardholder reserved by the bank are analyzed by the F test method, and the transaction is judged according to the analysis result: if the significance is insufficient, the face recognition is indicated. Failure, telling the POS to end the transaction; if the significance is obvious, it indicates that the face recognition is successful, and the POS is allowed to allow the transaction.

10) The MCU pre-processes the ECG information, including intercepting the ECG waveform and denoising of a single cardiac cycle. For external acquisition devices, decryption operations are required before preprocessing.

11) Calculate the main characteristic parameters of the electrocardiogram, and bring back the results obtained in the training in step 1 to calculate whether the current trader is in a stressful or sleep state of nervous fear. If it is, it is considered illegal information, refused, and ended the transaction. ; otherwise continue to trade

12) The MCU calculates the amplitude, area and mean of the P wave, QRS complex and T wave of the electrocardiogram as the characteristic values of the electrocardiogram.

13) The MCU encrypts the ECG feature value and transmits it to the transaction background.

14) The ECG feature value uploaded by the transaction background and the cardholder's ECG information reserved by the bank are analyzed by the F-test. If the significance is insufficient, the ECG recognition fails, and the POS is notified to end the transaction; if the significance is obvious, It means that the ECG recognition is successful, the background transaction is performed, and the transaction result is notified to the POS.

15) The POS machine will prompt the trader to the transaction result.

In summary, the present invention provides a face and electrocardiogram-based payment authentication method and terminal, which can determine whether a user is in a sleep state through the electrocardiogram information, and prevent the user from being stolen in the sleep state; Through computer-synthesized images, a large number of spatial hopping occurs at the edges of the face, the edges of the eyes, the edges of the mouth, etc., and there is a large amount of high-frequency information corresponding to the frequency domain, so it is determined whether the image information of the face is The presence of high-frequency information greater than a preset threshold can prevent the problem of the authentication authentication attack by the image information synthesized by the computer; and the present invention can effectively determine whether the user is in a coerced state by using the electrocardiogram information and the face image information to make payment It is safer and more reliable; the combination of face and ECG recognition can greatly reduce the risk of misappropriation and enhance transaction security and reliability. The cardholder's face information and ECG information are transmitted to the server as encrypted information through encryption. Only the one-way uplink transmission of the characteristic parameters is allowed to avoid the leakage of sensitive information. The above-mentioned ECG information is not easy to be stolen. Even if the ECG information is stolen, the attacker is not easy to camouflage the ECG to attack the POS, which effectively improves the security of the payment authentication and makes the transaction more secure and reliable.

Claims

A payment authentication method based on a face and an electrocardiogram, characterized in that it comprises the following steps:

S1: determining, according to the electrocardiogram information, whether the user is in a sleep state; and determining, according to the face information, whether high-frequency information greater than a preset threshold exists in the face image information included in the face information;

S2: If no, the related matching operation is performed according to the face image information, the electrocardiogram information, the reserved user face image information, and the user's electrocardiogram information, and the payment authentication is determined according to the matching result.
The method for claim authentication based on a face and an electrocardiogram according to claim 1, wherein the S1 further comprises:

S01: Display face specified action information required for payment verification;

S02: collecting ECG information while collecting face information; the face information includes face video information and face image information;

S03: determining whether the face motion in the face video information is consistent with the specified action;

S04: If they are consistent, step S1 is performed, otherwise the payment authentication fails.
The method for claim authentication based on the face and the electrocardiogram according to claim 2, wherein the S02 and the S03 further comprise:

The face information and the electrocardiogram information are separately subjected to noise reduction and filtering processing.
The face and electrocardiogram-based payment authentication method according to claim 2, wherein the face specifying action information required for displaying the payment verification in the S01 is specifically:

The face specifying action information is randomly generated, and the specified action information is displayed.
The face and electrocardiogram-based payment authentication method according to claim 4, wherein if the face information or the electrocardiogram information fails to be collected within the preset time, the new specified action information is randomly displayed and re-acquired At the same time as the face information, the ECG information is collected.
The method for claim authentication based on a face and an electrocardiogram according to claim 1, wherein the S1 further comprises:

Acquiring a plurality of first face image information in a state of being stressed, and calculating a first feature parameter of each first face image information;

Fitting all the first feature parameters to obtain a first mathematical model between the stressed state and the first feature parameter;

Obtaining multiple normal ECG information in a normal awake state, multiple sleep ECG information in a sleep state, and multiple stress ECG information in a state of being stressed;

Calculating a second characteristic parameter of each normal electrocardiogram information, a third characteristic parameter of each sleep electrocardiogram information, and a fourth characteristic parameter of each stress electrocardiogram information;

All second feature parameters corresponding to the normal awake state, all third feature parameters corresponding to the sleep state, and all fourth feature parameters corresponding to the stress state are respectively fitted to obtain corresponding mathematical models in different states.
The method for claim authentication based on a face and an electrocardiogram according to claim 6, wherein the S1 is specifically:

Obtaining an electrocardiogram feature parameter and a face feature parameter according to the obtained electrocardiogram information and the face image information in the face information;

Determining whether the user is in a state of being coerced according to the face feature parameter and the first mathematical model, and determining whether the user is in a coerced state or a sleep state according to the electrocardiographic feature parameter and the corresponding mathematical model in different states, and determining the face Whether there is high frequency information larger than a preset threshold in the image information.
The method for claim authentication based on a face and an electrocardiogram according to claim 7, wherein the S2 is specifically:

If yes, encrypting the face feature parameter and the electrocardiogram feature parameter, and sending the parameter to the server, so that the server performs significant analysis on the feature parameter corresponding to the face feature parameter and the reserved user face image information, and The characteristic parameters corresponding to the reserved user electrocardiogram information of the electrocardiogram characteristic parameter are significantly analyzed, and the significant analysis result is obtained; and according to the significance analysis result, whether the payment authentication is passed is determined.
A method for payment authentication based on a face and an electrocardiogram according to claim 1 or 8, wherein "determining whether there is high frequency information greater than a preset threshold in the face image information" is specifically:

Calculating image frequency domain information corresponding to the face image information, and determining whether there is high frequency information greater than a preset threshold in the image frequency domain information.
The method for claim authentication based on a face and an electrocardiogram according to claim 1, wherein the S1 further comprises:

Performing an authentication judgment on the preset transaction terminal and the server, and if the authentication fails, the payment authentication fails, and the transaction is ended;

If the authentication is successful, acquiring current location information of the transaction terminal;

Encrypting the current location information to obtain location encryption information;

Sending the location encryption information to the server, so that the server saves the location encryption information in preset security log information.
A face and electrocardiogram-based payment authentication terminal includes a memory, a processor, and a computer program stored on the memory and operable on the processor, wherein the processor executes the program to implement the following steps:

S1: determining, according to the electrocardiogram information, whether the user is in a sleep state; and determining, according to the face information, whether high-frequency information greater than a preset threshold exists in the face image information included in the face information;

S2: If no, the related matching operation is performed according to the face image information, the electrocardiogram information, the reserved user face image information, and the user's electrocardiogram information, and the payment authentication is determined according to the matching result.
The face authentication and the electrocardiogram-based payment authentication terminal according to claim 11, wherein before S1, the method further comprises:

S01: Display face specified action information required for payment verification;

S02: collecting ECG information while collecting face information; the face information includes face video information and face image information;

S03: determining whether the face motion in the face video information is consistent with the specified action;

S04: If they are consistent, step S1 is performed, otherwise the payment authentication fails.
The face authentication and the electrocardiogram-based payment authentication terminal according to claim 12, wherein the S02 and the S03 further comprise:

The face information and the electrocardiogram information are separately subjected to noise reduction and filtering processing.
The face authentication and the electrocardiogram-based payment authentication terminal according to claim 12, wherein the face specifying action information required for displaying the payment verification in the S01 is specifically:

The face specifying action information is randomly generated, and the specified action information is displayed.
The face authentication and electrocardiogram-based payment authentication terminal according to claim 14, wherein if the face information or the electrocardiogram information fails to be collected within a preset time, the new specified action information is randomly displayed and re-acquired. At the same time as the face information, the ECG information is collected.
The face authentication and the electrocardiogram-based payment authentication terminal according to claim 11, wherein before S1, the method further comprises:

Acquiring a plurality of first face image information in a state of being stressed, and calculating a first feature parameter of each first face image information;

Fitting all the first feature parameters to obtain a first mathematical model between the stressed state and the first feature parameter;

Obtaining multiple normal ECG information in a normal awake state, multiple sleep ECG information in a sleep state, and multiple stress ECG information in a state of being stressed;

Calculating a second characteristic parameter of each normal electrocardiogram information, a third characteristic parameter of each sleep electrocardiogram information, and a fourth characteristic parameter of each stress electrocardiogram information;

All second feature parameters corresponding to the normal awake state, all third feature parameters corresponding to the sleep state, and all fourth feature parameters corresponding to the stress state are respectively fitted to obtain corresponding mathematical models in different states.
The face authentication and the electrocardiogram-based payment authentication terminal according to claim 16, wherein the S1 is specifically:

Obtaining an electrocardiogram feature parameter and a face feature parameter according to the obtained electrocardiogram information and the face image information in the face information;

Determining whether the user is in a state of being coerced according to the face feature parameter and the first mathematical model, and determining whether the user is in a coerced state or a sleep state according to the electrocardiographic feature parameter and the corresponding mathematical model in different states, and determining the face Whether there is high frequency information larger than a preset threshold in the image information.
The face authentication and the electrocardiogram-based payment authentication terminal according to claim 17, wherein the S2 is specifically:

If yes, encrypting the face feature parameter and the electrocardiogram feature parameter, and sending the parameter to the server, so that the server performs significant analysis on the feature parameter corresponding to the face feature parameter and the reserved user face image information, and The characteristic parameters corresponding to the reserved user electrocardiogram information of the electrocardiogram characteristic parameter are significantly analyzed, and the significant analysis result is obtained; and according to the significance analysis result, whether the payment authentication is passed is determined.
The face authentication and the electrocardiogram-based payment authentication terminal according to claim 11 or 18, wherein "determining whether there is high frequency information greater than a preset threshold in the face image information" is specifically:

Calculating image frequency domain information corresponding to the face image information, and determining whether there is high frequency information greater than a preset threshold in the image frequency domain information.
The face authentication and the electrocardiogram-based payment authentication terminal according to claim 11, wherein before S1, the method further comprises:

Performing an authentication judgment on the preset transaction terminal and the server, and if the authentication fails, the payment authentication fails, and the transaction is ended;

If the authentication is successful, acquiring current location information of the transaction terminal;

Encrypting the current location information to obtain location encryption information;

Sending the location encryption information to the server, so that the server saves the location encryption information in preset security log information.