WO2019113765A1 - Procédé d'authentification de paiement basé sur un visage et sur un électrocardiogramme et terminal - Google Patents

Procédé d'authentification de paiement basé sur un visage et sur un électrocardiogramme et terminal Download PDF

Info

Publication number
WO2019113765A1
WO2019113765A1 PCT/CN2017/115557 CN2017115557W WO2019113765A1 WO 2019113765 A1 WO2019113765 A1 WO 2019113765A1 CN 2017115557 W CN2017115557 W CN 2017115557W WO 2019113765 A1 WO2019113765 A1 WO 2019113765A1
Authority
WO
WIPO (PCT)
Prior art keywords
information
face
electrocardiogram
authentication
state
Prior art date
Application number
PCT/CN2017/115557
Other languages
English (en)
Chinese (zh)
Inventor
张炽成
唐超旬
Original Assignee
福建联迪商用设备有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 福建联迪商用设备有限公司 filed Critical 福建联迪商用设备有限公司
Priority to CN201780002070.2A priority Critical patent/CN108401458A/zh
Priority to PCT/CN2017/115557 priority patent/WO2019113765A1/fr
Publication of WO2019113765A1 publication Critical patent/WO2019113765A1/fr

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/38—Payment protocols; Details thereof
    • G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
    • G06Q20/401—Transaction verification
    • G06Q20/4014—Identity check for transactions
    • G06Q20/40145—Biometric identity checks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/32—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials
    • H04L9/3226—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials using a predetermined code, e.g. password, passphrase or PIN
    • H04L9/3231—Biological data, e.g. fingerprint, voice or retina

Definitions

  • 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.
  • 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.
  • 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.
  • 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;
  • 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.
  • the present invention provides a payment authentication method based on a face and an electrocardiogram, comprising the following steps:
  • 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.
  • the method further includes:
  • S02 collecting ECG information while collecting face information;
  • the face information includes face video information and face image information;
  • 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.
  • the S02 and the S03 further include:
  • the accuracy of data processing can be improved by the above method.
  • the new specified action information is randomly displayed, and the face information is collected again, and the ECG information is collected.
  • 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.
  • S1 is specifically:
  • S2 is specifically:
  • 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.
  • determining whether there is high frequency information greater than a preset threshold in the face image information is specifically:
  • 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.
  • the location information in which the transaction is stored during the transaction process makes the transaction location traceable.
  • 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:
  • 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;
  • the method further includes:
  • S02 collecting ECG information while collecting face information;
  • the face information includes face video information and face image information;
  • step S04 If they are consistent, step S1 is performed, otherwise the payment authentication fails.
  • the face information and the electrocardiogram information are separately subjected to noise reduction and filtering processing.
  • 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:
  • the face specifying action information is randomly generated, and the specified action information is displayed.
  • 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.
  • the above-mentioned face and electrocardiogram-based payment authentication terminal further includes:
  • 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 S1 is specifically:
  • the S2 is specifically:
  • 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:
  • the above-mentioned face and electrocardiogram-based payment authentication terminal further includes:
  • 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:
  • step 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;
  • step S0 is re-executed
  • 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;
  • Embodiment 2 of the present invention is:
  • the invention provides a payment authentication method based on a face and an electrocardiogram, comprising the following steps:
  • 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.
  • the default transaction terminal and the server are first authenticated. If the authentication fails, the payment authentication fails and the transaction is terminated.
  • 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;
  • 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:
  • 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.
  • 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:
  • step 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;
  • step S0 is re-executed
  • 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;
  • Embodiment 4 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:
  • 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.
  • the default transaction terminal and the server are first authenticated. If the authentication fails, the payment authentication fails and the transaction is terminated.
  • 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;
  • 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:
  • 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;
  • MCU micro control module
  • ECG acquisition module electrocardiogram acquisition module
  • liquid crystal screen wherein the MCU is electrically connected to the camera, the ECG acquisition module and the liquid crystal screen respectively;
  • the POS software 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.
  • 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.
  • 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.
  • 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.
  • the MCU needs to decrypt the information to obtain the ECG plaintext information.
  • the MCU preprocesses the face information, including noise reduction and normalization processing.
  • 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.
  • 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.
  • the MCU encrypts the face information feature value and transmits it to the transaction background.
  • 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.
  • 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.
  • step 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
  • 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.
  • the MCU encrypts the ECG feature value and transmits it to the transaction background.
  • 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.
  • the POS machine will prompt the trader to the transaction result.
  • 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;
  • 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.

Abstract

L'invention concerne un procédé d'authentification de paiement basé sur un visage et sur un électrocardiogramme et un terminal. Le procédé comprend les étapes suivantes consistant : à déterminer, selon des informations d'électrocardiogramme, si un utilisateur est dans un état de sommeil ; à déterminer, selon des informations faciales, si des informations d'image faciale des informations faciales contiennent des informations haute fréquence supérieures à un seuil prédéfini ; et si les deux résultats de détermination sont négatifs, à réaliser une opération de mise en correspondance associée selon les informations d'image faciale, les informations d'électrocardiogramme, et des informations d'image faciale et des informations d'électrocardiogramme pré-stockées de l'utilisateur, et à déterminer, selon un résultat de correspondance, si l'authentification de paiement est réussie. La présente invention peut déterminer efficacement, selon des informations d'électrocardiogramme et des informations d'image faciale, si un utilisateur est dans un état contraint ou un état de sommeil, ce qui permet d'assurer des transactions plus sécurisées et plus fiables. Le procédé combine des techniques de reconnaissance de visage et d'électrocardiogramme, ce qui permet de réduire considérablement les risques de paiements non autorisés, et d'améliorer la sécurité et la fiabilité des transactions.
PCT/CN2017/115557 2017-12-12 2017-12-12 Procédé d'authentification de paiement basé sur un visage et sur un électrocardiogramme et terminal WO2019113765A1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN201780002070.2A CN108401458A (zh) 2017-12-12 2017-12-12 一种基于人脸和心电图的支付认证方法及终端
PCT/CN2017/115557 WO2019113765A1 (fr) 2017-12-12 2017-12-12 Procédé d'authentification de paiement basé sur un visage et sur un électrocardiogramme et terminal

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2017/115557 WO2019113765A1 (fr) 2017-12-12 2017-12-12 Procédé d'authentification de paiement basé sur un visage et sur un électrocardiogramme et terminal

Publications (1)

Publication Number Publication Date
WO2019113765A1 true WO2019113765A1 (fr) 2019-06-20

Family

ID=63095097

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2017/115557 WO2019113765A1 (fr) 2017-12-12 2017-12-12 Procédé d'authentification de paiement basé sur un visage et sur un électrocardiogramme et terminal

Country Status (2)

Country Link
CN (1) CN108401458A (fr)
WO (1) WO2019113765A1 (fr)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110782247B (zh) * 2019-10-23 2023-07-21 广东盛迪嘉电子商务股份有限公司 一种基于人脸识别的智能手表支付方法

Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20030037264A1 (en) * 2001-08-15 2003-02-20 Tadashi Ezaki Authentication processing system, authentiation processing method, authentication device, and computer program
CN102231213A (zh) * 2011-06-29 2011-11-02 哈尔滨工业大学深圳研究生院 Ecg门禁卡身份识别方法及系统
CN104850827A (zh) * 2015-04-23 2015-08-19 小米科技有限责任公司 指纹识别方法及装置
CN105279641A (zh) * 2014-06-12 2016-01-27 中兴通讯股份有限公司 互联网支付的注册认证、实现方法及装置
CN105320947A (zh) * 2015-11-04 2016-02-10 博宏信息技术有限公司 一种基于光照成分的人脸活体检测方法
CN105550878A (zh) * 2015-06-23 2016-05-04 宇龙计算机通信科技(深圳)有限公司 一种授权请求的处理方法及装置
CN105611531A (zh) * 2015-10-30 2016-05-25 东莞酷派软件技术有限公司 终端的控制方法、终端的控制装置和终端
CN105718874A (zh) * 2016-01-18 2016-06-29 北京天诚盛业科技有限公司 活体检测及认证的方法和装置
CN105809442A (zh) * 2014-12-30 2016-07-27 北京奇虎科技有限公司 一种高安全性的支付系统及方法
CN106127014A (zh) * 2016-08-31 2016-11-16 珠海市魅族科技有限公司 一种生物信息识别方法及终端
CN106156730A (zh) * 2016-06-30 2016-11-23 腾讯科技（深圳）有限公司 一种人脸图像的合成方法和装置

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101679271B1 (ko) * 2015-06-09 2016-11-24 엘지전자 주식회사 이동단말기 및 그 제어방법
CN105761378B (zh) * 2016-01-29 2018-06-05 广州御银科技股份有限公司 一种自动识别异常交易并减少损失的装置及方法
KR101803397B1 (ko) * 2017-05-08 2017-12-01 주식회사 올아이티탑 얼굴과 지문 또는/및 지정맥을 스캐닝하여 사용자 인증을 처리하는 다중 안전 잠금 기능의 금융 거래 중계 시스템 및 그의 처리 방법

Patent Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20030037264A1 (en) * 2001-08-15 2003-02-20 Tadashi Ezaki Authentication processing system, authentiation processing method, authentication device, and computer program
CN102231213A (zh) * 2011-06-29 2011-11-02 哈尔滨工业大学深圳研究生院 Ecg门禁卡身份识别方法及系统
CN105279641A (zh) * 2014-06-12 2016-01-27 中兴通讯股份有限公司 互联网支付的注册认证、实现方法及装置
CN105809442A (zh) * 2014-12-30 2016-07-27 北京奇虎科技有限公司 一种高安全性的支付系统及方法
CN104850827A (zh) * 2015-04-23 2015-08-19 小米科技有限责任公司 指纹识别方法及装置
CN105550878A (zh) * 2015-06-23 2016-05-04 宇龙计算机通信科技(深圳)有限公司 一种授权请求的处理方法及装置
CN105611531A (zh) * 2015-10-30 2016-05-25 东莞酷派软件技术有限公司 终端的控制方法、终端的控制装置和终端
CN105320947A (zh) * 2015-11-04 2016-02-10 博宏信息技术有限公司 一种基于光照成分的人脸活体检测方法
CN105718874A (zh) * 2016-01-18 2016-06-29 北京天诚盛业科技有限公司 活体检测及认证的方法和装置
CN106156730A (zh) * 2016-06-30 2016-11-23 腾讯科技（深圳）有限公司 一种人脸图像的合成方法和装置
CN106127014A (zh) * 2016-08-31 2016-11-16 珠海市魅族科技有限公司 一种生物信息识别方法及终端

Also Published As

Publication number Publication date
CN108401458A (zh) 2018-08-14

Similar Documents

Publication Publication Date Title
WO2019113776A1 (fr) Procédé d'authentification de paiement à base de reconnaissance faciale et d'empreinte vocale ainsi que terminal
AU2020201558B2 (en) System and method for authorizing access to access-controlled environments
US11120111B2 (en) Authentication based on correlation of multiple pulse signals
Crouse et al. Continuous authentication of mobile user: Fusion of face image and inertial measurement unit data
US11580203B2 (en) Method and apparatus for authenticating a user of a computing device
CN108804884B (zh) 身份认证的方法、装置及计算机存储介质
US9892576B2 (en) Biometrics identification module and personal wearable electronics network based authentication and transaction processing
WO2016150154A1 (fr) Procédé, appareil, dispositif et système utilisés pour l'authentification mobile
US20220122051A1 (en) Method and system for securing transactions in a point of sale
US10360555B2 (en) Near field authentication through communication of enclosed content sound waves
WO2018094584A1 (fr) Système de paiement et d'authentification d'identité basé sur la reconnaissance de caractéristiques biométriques
WO2017088693A1 (fr) Procédé de vérification d'identité basée sur une reconnaissance de caractéristiques
US11494474B2 (en) Brain activity-based authentication
JP2011023854A (ja) 情報処理装置、情報処理方法およびプログラム
EP2148295A1 (fr) Système de gestion de configuration des veines, dispositif et procédé d'enregistrement de configuration des veines, dispositif et procédé d'authentification de configuration des veines, programme et structure de données des veines
US20190065874A1 (en) System and method of authentication using image of a user
CN103793640A (zh) 一种将生物识别技术应用在USB Key上的方法和系统
CN109426963B (zh) 认证生物统计请求的生物统计系统
WO2015188434A1 (fr) Authentification d'enregistrement de paiement par internet, procédé et dispositif de mise en œuvre
US11829460B2 (en) Systems and methods for biometric authentication via face covering
WO2019113765A1 (fr) Procédé d'authentification de paiement basé sur un visage et sur un électrocardiogramme et terminal
US20100239129A1 (en) Vein pattern management system, vein pattern registration apparatus, vein pattern authentication apparatus, vein pattern registration method, vein pattern authentication method, program, and vein data configuration
JP2015524968A (ja) 非接触チップカードのユーザを認証する方法
JP5723930B2 (ja) 情報処理装置および情報処理システム
CN115906028A (zh) 用户身份验证方法、装置和自助服务终端

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 17935021

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 17935021

Country of ref document: EP

Kind code of ref document: A1