Facebook, Inc.

Delfigo Corporation

Meta Platforms, Inc.

Raphael A Rodriguez

Julian D Spring

Daniel Volovik

Justin Boyd

Ryan Cahill

Michael Muesch

David Thor

Xiaolu Xiong

J Robert Geiman

Daniel Volovika

The present solution is directed to methods and systems for storing personal identifiable information. In some implementations, the information is collected during the authentication of identification (ID) documents. The personal identifiable information can be useful in processes such as client enrollment, mobile device management, identification processes, and transaction audits. However, the data can be a target for bad actors. The present solution includes a one-way hashing and cryptographic function that converts unique personal identifiable information into a unique digest which can be securely stored on a mobile device and rendered as an original state digital image for proof of ID.

Electronically signing and distributing identification data as a service that provides proof of identity, integrity, validity and origin of data for non-repudiation and ID validation methods

The present disclosure describes methods and systems for handling personally identifiable information. In some implementations, the information is collected during the authentication of identification (ID) documents. The system includes a one-way hashing function that converts unique personal identifiable information into a unique digest. The system can store the digest without having to store the personal identifiable information. Because the hashing function generates the same digest when given the same input, the digests can be used as anonymized identifiers in place of the personal identifiable information.

Storing anonymized identifiers instead of personally identifiable information

The present disclosure describes methods and systems for handling personal identifiable information. In some implementations, the information is collected during the authentication of identification (ID) documents. The system includes a one-way hashing function that converts unique personal identifiable information into a unique digest. The system can store the digest without having to store the personal identifiable information. Because the hashing function generates the same digest when given the same input, the digests can be used as anonymized identifiers in place of the personal identifiable information.

The present disclosure describes a method to determine whether a physical identification document is authentic. An authentication manager receives an image of a physical identification document to be authenticated. The authentication manager extracts a set of characteristics of the document from the image. The authentication manager determines a class of the document based on the set of characteristics. The authentication manager applies a convolution kernel, convolving the image with the kernel to generate a feature map. The authentication manager determines a score based on the feature map, where the score identifies the likelihood that the document is valid. The authentication manager then provides an indication that the physical document is authentic based on the score.

Classification and authentication of identification documents using a convolutional neural network

The present disclosure describes systems and methods to classify and authenticate ID documents based on the information contained on the face of the ID document. This present system can automatically classify, authenticate, and extracting data from documents using artificial intelligence (AI) based machine learning for image recognition. In some implementations, the machine learning techniques include a convolutional neural network. The system can also determine the authenticity of other documents, such as currency, stamps, and invoices.

System and method for classification and authentication of identification documents using a machine learning based convolutional neural network

The present disclosure describes methods and systems for storing virtual personal identifiable information. In some implementations, the information is collected during the authentication of identification (ID) documents. The system includes a one-way hashing function that converts unique personal identifiable information into a unique digest. The system can store the digest without having to store the personal identifiable information. Because the hashing function generates the same digest when given the same input, the digests can be used as anonymized identifiers in place of the personal identifiable information.

Storing identification data as virtual personally identifiable information

A system and method is provided for visual authentication and authorization of a user for mobile devices, the system having: a login display on a mobile selection device displaying a visual pattern, a data collection engine whereby selection features are obtained from a plurality of user selection events to the mobile selection device with reference to the visual pattern, the selection attributes comprise measured selection attributes and derived selection attributes calculated from the measured selection attributes; an authentication engine whereby the selection attributes are compared to projected user selection attributes derived from user selection attribute values obtained during prior successful logins.

Optical cognition and visual authentication and authorization for mobile devices

A method and system for the identification of a user is provided by collecting a series of user enrollment data from a series of user inputs; calculating a user profile from the series of user enrollment data and additional user data, the additional user data being randomly selected user enrollment data from the series of user enrollment data; comparing a post-training user login to the user profile; updating the user profile with data from the post training user login if the post-training login is consistent with the user profile; repeating the comparing and the updating for each successive post training user login.

Multi-factor authentication enrollment optimization method and apparatus

A system and method are provided for identification of a user collecting enrollment data from the user including dwell times for each of an enrollment series of login attempts; creating an iterative unified identification score for the user from the dwell times of login attempts; establishing an iterative average of identification score; establishing a standard deviation of the iterative identification score; deleting the dwell times and other data of the enrollment series of login attempts; prompting and collecting login specific dwell times; calculating a login identification score; comparing the login identification score to the iterative unified identification score, and updating the iterative scores and the iterative standard deviations and storing between login attempts only an iterative average dwell time, an iterative average flight time, the unified identification score and iterative standard deviation of the unified identification score.

Cloud identification processing and verification

A system and method is provided for visual authentication and authorization of a user for mobile touch devices, the system having: a login display on a mobile touch device displaying a visual pattern; a data collection engine whereby touch attributes are obtained from a plurality of user touch events to the mobile touch device with reference to the visual pattern, the touch attributes comprise measured touch attributes and derived touch attributes calculated from the measured touch attributes; an authentication engine whereby the touch attributes are compared to projected user touch attributes derived from user touch attribute values obtained during prior successful logins.

Visual authentication and authorization for mobile devices

A method and system for the identification of a user is provided, the system having: an enrollment processor, whereby initial login attempts by the user are measured, and data identifying the user are collected for a specific device and location; the enrollment processor being configured to collect the identifying data and create a first login score, a iterative average login score, and a iterative standard deviation login score; an enrolled login processor, the enrolled login processor being configured to measure dwell time on keys and flight time between keys in a login sequence and to calculate weighted dwell time and weighted flight time from the dwell time and the flight time; a login score calculator, the calculator taking the weighted flight time and the weighted dwell time and generating an actual login score; a login confidence comparator, the login confidence comparator comprising a processor whereby a comparison score is generated as a function of the actual login score, the iterative average login score, and the iterative standard deviation login score.

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Quincy, MA, United States of America

Raphael A Rodriguez