Wells Fargo Bank, N.a.

Ramesh Yarlagadda

Ramanathan Ramanathan

Abhijit Rao

Andrew J Garner, Iv

Michael Erik Meinholz

Pierre Arbajian

Peter Bordow

Jeff J Stapleton

Adam M Sanders

Bradford A Shea

Julio Jiron

Richard Orlando Toohey

Volkmar Scharf-Katz

Akhlaq M Khan

Thomas E Bell

Omar B Khan

Pierre Arbadjian

Joon Maeng

William E Goff

Disclosed are example methods, systems, and devices that allow for secure data processing using data packages generated by edge devices. The techniques include generating a biometric signature using information captured by a computing device, and encrypting user data obtained via the computing device using the biometric signature and a device identifier of the computing device. A security token can be generated and utilized by the computing device to generate a data package, which is configured such that any change to the data package would cause a validation process of the data package using the security token to fail. The data package can be encrypted using various digital keys and provided to secondary computing systems.

Secure data processing using data packages generated by edge devices

Disclosed are example methods, systems, and devices that allow for secure digital authorization via generated datasets. The techniques include receiving a first dataset of a first user and a second dataset of a second user and generating a first set of identity elements and a second set of identity elements based on the first dataset and the second dataset, respectively. A linkage definition can be generated based on the first and second datasets, which can be associated with a set of activation elements. The techniques include determining that a set of inputs satisfy one or more of the set of activation elements and, in response, generating a set of security access tokens based on the linkage condition. The security access tokens can be transmitted to a computing device upon analyzing and verifying biometric data received from that computing device.

Secure digital authorization based on identity elements of users and/or linkage definitions identifying shared digital assets

Disclosed are example methods, systems, and devices for sensor data processing for monitoring devices. These techniques include receiving scan data from a computing device that corresponds to a scan by an imaging device and analyzing the scan data to determine that the scan data corresponds to a manufactured article. An indication can be transmitted with a request for audiovisual data corresponding to an operation of the manufactured article, and the audiovisual data can be received from an imaging device or a microphone of the computing device. A sound sample corresponding to the operation of the manufactured article is extracted, and a status metric for the article is generated based on a comparison of the sound sample to a sound signature in an identity profile of the manufactured article. The status of the manufactured article can then be determined.

Sensor data processing for monitoring device performance

Disclosed are example methods, systems, and devices that allow for executing machine-learning models for real-time and secure analysis of digital metrics. The techniques include generating metrics for identity elements stored in digital profiles of users. A subset of profiles can be identified that have metrics that fall below a predetermined thresholds, with which a training dataset can be generated. Machine-learning models can be executed over the training dataset to train an artificial intelligence agent that receives digital profiles as input and outputs translational elements corresponding to identity elements in the digital profiles. After training, additional profiles can be input to the machine-learning models of the artificial intelligence agent to identify a second subset of digital profiles with corresponding metrics. Electronic messages corresponding to the second subset can be generated and transmitted to one or more computing devices identified in the second subset of digital profiles.

Machine-learning for real-time and secure analysis of digital metrics

Disclosed are example methods, systems, and devices that allow for secure generation of authentication datasets from network activity. The techniques include accessing secured data sources to generate a first dataset of secured data, and extracting information from one or more unsecured data sources to generate a second dataset comprising a second dataset. A third set of data elements can be generated from the first and second datasets, and may be utilized to authenticate credentials that can be utilized to access secured data via a network. The techniques can transmit indications that credentials are invalid if the credentials fail to satisfy aspects of the third dataset.

Secure generation of authentication datasets from network activity

A method, apparatus, and computer program product for offline authentication are provided. An example method includes receiving, by a computing device, a request for authentication from a first user device associated with a first user. The request includes first authentication credentials generated based upon user attributes retrieved by the first user device from a digital identity construct database at a first time. The method includes determining an offline condition of the computing device at a first time. The method also includes obtaining, by the computing device, second authentication credentials associated with the first user that are based upon one or more user attributes retrieved by the computing device from the digital identity construct database at a second time later than the first time. The method incudes determining a discrepancy between the first and second authentication credentials and authenticating the first user based upon a forecast operation of the same.

Apparatuses, methods, and computer program products for offline authentication

Secure digital authorization via generated datasets

Systems, methods, and computer program products are provided for disparate quantum computing (QC) detection. An example system includes QC detection data generation circuitry configured to generate a set of QC detection data. The example system further includes cryptographic circuitry configured to distort the set of QC detection data via a first PQC cryptographic technique, generate a pair of asymmetric cryptographic keys comprising a public cryptographic key and a private cryptographic key via a second PQC cryptographic technique, generate encrypted QC detection data from the distorted set of QC detection data based on the pair of asymmetric cryptographic keys, and destroy the private cryptographic key. The example system further includes data monitoring circuitry configured to monitor a set of data environments for electronic information related to the encrypted QC detection data.

Systems and methods for disparate quantum computing threat detection

Various systems and methods are provided for quantum computing based optimization of a personalized portfolio. One exemplary method may comprise identifying one or more filtered personalized portfolio optimization factor data based on one or more optimization factor data for the personalized portfolio, personalized portfolio owner feedback, QC algorithms, and algorithm performance information, selecting one QC algorithm for each filtered portfolio optimization factor data of the one or more filtered portfolio optimization factor data, utilizing the selected QC algorithm to optimize a personalized portfolio determination for each identified filtered personalized portfolio optimization factor data, and rebalancing the personalized portfolio based on the personalized portfolio determination.

Systems and methods for quantum based optimization of a personalized portfolio

Systems, apparatuses, methods, and computer program products are disclosed for post-quantum cryptography (PQC). An example system includes a PQC smartcard. The smartcard may include a PQC cryptographic algorithm selection circuitry configured to select a PQC cryptographic technique from a set of PQC cryptographic techniques for encrypting the data. The smartcard may further include a PQC cryptographic circuitry configured to encrypt data based on a generated set of PQC encryption attributes and the PQC cryptographic technique.

Systems and methods for post-quantum cryptography on a smartcard

Disclosed are example methods, systems, and devices that allow for secure multi-verification of biometric data in a distributed computing environment. The techniques include receiving a request to grant authorization to a second user. The request can include biometric data of the first user and second user. An authorization token can be generated based on the request, which can be transmitted to a second computing device of the second user. A second request can be received from a third computing device that includes the authorization token and third biometric data. The second request can be verified based on the authorization token, the third biometric data, and provenance data, and an indication that the grant of authorization to the second user is verified can be transmitted to the first, second, or third computing devices.

Secure multi-verification of biometric data in a distributed computing environment

Systems, methods, and computer program products are provided for quantum computing (QC) detection. An example QC detection system includes QC detection data generation circuitry that generates QC detection data. The QC detection system also includes cryptographic circuitry that distorts the QC detection data via a first post-quantum cryptographic (PQC) technique and generates a pair of asymmetric cryptographic keys including a public cryptographic key and a private cryptographic key. The cryptographic circuitry further generates encrypted QC detection data based on the pair of asymmetric cryptographic keys and destroys the private cryptographic key. The QC detection system further includes data monitoring circuitry that monitors a set of data environments for electronic information related to the encrypted QC detection data.

Systems and methods for quantum computing threat detection

Systems, apparatuses, methods, and computer program products are disclosed for gathering performance information for post-quantum cryptography (PQC) is provided. An example method includes generating, by a quantum computing (QC) detection data generation circuitry, QC detection data and encrypting, by a PQC cryptographic circuitry and by a first neural network, the QC detection data based on a PQC technique, where the first neural network is trained to encrypt the QC detection data using the PQC technique. The example method further includes decrypting, by a PQC decryption circuitry and by a second neural network, the encrypted QC detection data wherein the second neural network is trained to decrypt data, and storing encryption metadata and decryption metadata as PQC cryptographic performance information associated with the PQC technique.

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Charlotte, NC, United States of America

Ramesh Yarlagadda