Visa International Service Association

Lacey Best-Rowden

Kim R Wagner

Sunpreet Singh Arora

John F Sheets

Sunit Lohtia

Saloni Vijaykumar Mahajan

Saman Sarraf

Dennis Franklin Olson

Amisha Sisodiya

Jorge Andre Torres Perez Palacios

Amy Dawson

Binoy Parag Parikh

Sowmya Vuddaraju

Andres Jimenez

Sneha Sri Tadepalli

Elianna Starr

Jiayun He

Chunxi Jiang

Provided is a computer-implemented method for authenticating a customer during payment transactions based on biometric identification parameters of the customer that includes receiving image data associated with an image template for identification of a customer, receiving image data associated with an image of a biometric identification parameter of the customer during a payment transaction between the customer and a merchant, establishing a short-range communication connection with a user device associated with the customer during the payment transaction between the customer and the merchant, authenticating an identity of the customer for the payment transaction via the short-range communication connection, determining an account identifier of an account of the customer based on authenticating the identity of the customer for the payment transaction, and processing the payment transaction using the account identifier of the account of the customer. A system and computer program product are also disclosed.

Authentication based on biometric identification parameter of an individual for payment transaction

A first biometric sample of a user is received by an access device from a user device. First biometric information is generated in an obscured format, based on the first biometric sample. A plurality of biometric information is received in an obscured format. The plurality of biometric information corresponds to a plurality of users, and was obtained from biometric samples of the plurality of users. The first biometric information in the obscured format is compared to the plurality of biometric information in the obscured format, and a match result is generated based on the comparing. The match result is provided to a server computer. Based on the match result, information indicating that one of the plurality of users that is associated with one of the plurality of biometric information is the user associated with the first biometric information is received.

Biometric validation process utilizing access device and location determination

Described herein are a system and techniques for enabling biometric authentication without exposing the authorizing entity to sensitive information. In some embodiments, the system receives a biometric template from a user device which is encrypted using a public key associated with the system. The encrypted biometric template is then provided to a second entity along with a biometric identifier. Upon receiving a request to complete a transaction that includes the biometric identifier and a second biometric template, the second entity may encrypt the second biometric template using the same public key associated with the system and perform a comparison between the two encrypted biometric templates. The resulting match result data file is already encrypted and can be provided to the system to determine an extent to which the two biometric templates match.

Server-assisted privacy protecting biometric comparison

Techniques for intelligently deciding the optimal authenticator(s) from amongst those supported by an electronic device are described. The authentication system according to some embodiments may include a dynamic machine learner that incorporates the attributes of: (i) user behavior attributes (e.g., preferred authenticator); (ii) device attributes (e.g., hardware and software specifications, applications, etc.); and (iii) operating environment attributes (e.g., ambient light, noise, etc.), as well as the interplay between the aforementioned attributes over time to make the decision. In some embodiments, the authentication activities and patterns of other users of similar type (e.g., users exhibiting similar behavior across different operating environments) can also be learned and employed to improve the decision making process over time.

Dynamic learning system for intelligent authentication

A method is disclosed. An authentication node may receive a plurality of encrypted match values, wherein the plurality of encrypted match values were formed by a plurality of worker nodes that compare a plurality of encrypted second biometric template parts derived from a second biometric template to a plurality of encrypted first biometric template parts derived from a first biometric template. The authentication node may decrypt the plurality of encrypted match values resulting in a plurality of decrypted match values. The authentication node may then determine if a first biometric template matches the second biometric template using the plurality of decrypted match values. An enrollment node may be capable of enrolling a biometric template and storing encrypted biometric template parts at worker nodes.

Distributed biometric comparison framework

A method and system of using a vehicle mounted camera device to authenticate a user during an interaction is disclosed. The method includes receiving interaction data regarding an interaction between a user operating a communication device and an access device, the user being near other candidate users. The method then includes determining one or more match indicators, the match indicators generated by comparing different sample biometric templates of the user with different enrolled biometric templates. At least one of the different biometric sample templates may be an image-based biometric template and at least one may be a voice print biometric template. Then the method includes identifying the user based on at least the match indicator associated with the voice print biometric template. The method then includes, if the match indicators are positive match indicators, initiating a process on behalf of the user.

Camera device enabled identification and disambiguation system and method

A method is disclosed. The method includes constructing a table by encrypting a plurality of unencrypted match values using a public key to produce a plurality of encrypted match values. Each unencrypted match value being an indication of a degree of match between an input biometric template and an enrollment template. The method includes arranging each row so that each row has a match value and a corresponding encrypted match value. The method also includes storing, in a database, the table comprising the plurality of encrypted match values and the plurality of unencrypted match values. The server computer can be programmed to receive an encrypted biometric template and the table is used to determine a match value using the encrypted biometric template, and the match value is used to determine if a person is enrolling a biometric template associated with the encrypted biometric template more than once.

Method of constructing a table for determining match values

A biometric matching process is disclosed. The biometric matching process may be used to obtain access to a resource managed by an access device using only biometric information. In some embodiments, a biometric template is stored in relation to a user device and/or account information, and is obscured. Upon receiving a request for access to a resource from an access device, the system may identify a number of user devices in proximity to the access device. Biometric templates associated with each of those user devices may be compared to a biometric template received from the access device. Upon identifying a match, the system may provide the access device with account information stored in relation to the matched biometric template. The access device may then complete a transaction using the provided account information and grant access to the requested resource.

Embodiments of the invention are directed to a system and methods for determining a likelihood that an image that includes a user is a spoof or fake. In some embodiments, focus values are determined for various parts of the image during a focus sweep. The focus values may represent a focus point at which a particular part of the image is sharp. In some embodiments, the focus values may be determined only for the sections of the image that correspond to a face within the image. From the focus values, the system may determine a relative depth of various parts of the image. Using the relative depths, the system may generate a rough depth map for the image. The depth map may be analyzed to determine a likelihood that the image is authentic.

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San Mateo, CA, United States of America

Lacey Best-Rowden