Bank of America Corporation

Robert Cain Durbin, Jr

Jack Lawson Bishop, Iii

Daniel Joseph Serna

Jake Michael Yara

Marcus Raphael Matos

Michael James Sbandi

Adam Kristian King

Chiamaka Azih

Michael Robert Young

Jo-Ann Taylor

James J Siekman

Anna Kristen Pingel Berry

Stuart David Ford

Benjamin F Tweel

Jennifer T Renckert

Frank J Yanan

Jeffrey Kyle Johnson

Son Huynh

Rebbecca Danielle Nelson

Vicky Kivuti

Angelica Barrera

Sheng Tang Hsiang

Systems, computer program products, and methods are provided for code revision impact analysis. The method includes generating a system map based on data received from a plurality of network devices; receiving a data transmission including a text file; processing the text file via a natural language processing engine, where an output of the natural language processing engine comprises a plurality of expected updates; determining, based on the system map, at least one downstream effect of the plurality of expected updates; and performing a remedial action.

Natural language processing engine for component level data mapping and code revision impact analysis

Systems, computer program products, and methods are provided for automated detection of source code discrepancies. The method includes receiving a data transmission including a text file and a source code file; processing the source code file via a machine learning engine, where an output of the machine learning engine includes a plurality of identified updates; processing the text file via a natural language processing engine, where an output of the natural language processing engine includes a plurality of expected updates; identifying a difference between the plurality of identified updates and the plurality of expected updates; and performing a remedial action.

Natural language processing engine for automated detection of source code discrepancies

Systems, computer program products, and methods are described herein for analyzing micro-anomalies in anonymized electronic data. The present disclosure is configured to import or retrieve a first data set, process the first data set to develop at least one event-outcome projection, define an outcome projection data set, import or receive a monitored user data set, anonymize the monitored user data set, define an avatar data set process the avatar data set, wherein the steps of import or receive a monitored user data set, anonymize the monitored user data set, and define an avatar data set are repeated one or more times.

System and method for analyzing micro-anomalies in anonymized electronic data

Apparatus and methods for establishing a user Internet of Things ('IoT') system is provided. The method may be performed by a central IoT hub run on a user's personal computing device. The method may include detecting user devices in electronic communication with the central IoT hub and onboarding, to the user IoT system, user devices determined to be in conformance with baseline security protocols and performance characteristics. The onboarded user device may be IoT nodes. The method may include monitoring enterprise data to pre-emptively identify and address probable failures of the IoT nodes prior to failure of the IoT nodes. The method may also include addressing known failures for each IoT node on the user IoT system.

Enterprise IOT system for onboarding and maintaining peripheral devices

A blind authenticator performs an authentication procedure with two devices that provides the convenience offered by password storage but avoids storing the passwords themselves. Generally, the blind authenticator stores on the two devices portions of different code generation algorithms. These algorithms on the devices are incomplete&#x2014;they may not execute properly on their own. During an authentication procedure, the blind authenticator communicates to the devices the remaining portions of these code generation algorithms so that the devices can execute their respective code generation algorithms. The devices then send the generated codes to the blind authenticator, which performs a code validation algorithm on the received codes to determine whether the codes are valid. The code validation algorithm is not sent to the devices, so the devices do not know what makes a code valid or invalid.

Blind authenticator

Growing community of inventors

New Hope, PA, United States of America

Robert Cain Durbin, Jr