Bank of America Corporation

Michael Ogrinz

Manu Jacob Kurian

William P Jacobson

Elena Kvochko

Victoria Lynn Dravneek

Joseph Neil Johansen

Jinna Zevulun Kim

Heather Roseann Dolan

Amanda Jane Adams

Heather Linn

Joseph Benjamin Castinado

Brandon Sloane

Matthew Hsieh

Jayachandra Varma

Christine D Black

Stephen A Corrado

Evan Sachs

Elizabeth Votaw

George Albero

Katherine Dintenfass

Cameron Darnell Wadley

Jisoo Lee

John Christopher Checco

Graham Marshall Wyllie

Gerard P Gay

Mark Alan Odiorne

Regina Peyfuss

Allison Dolores Baker

Jeremiah Wiley Fellows

Jennifer Elizabeth Munro

Siddhesh Vinayak Wadikar

David Ryan Ammons

Varadharajan Candhadai Ramaswamy

Alicia C Jones-McFadden

Nathan Dent

Matthew E Carroll

Monika Kapur

Maria Carolina Barraza Enciso

Charles Edward Dudley

Phillip Wade Mork

Darryl C Goebel

David Hsiang

Maharaj Mukherjee

Stephen Thomas Shannon

John H Kling

Elijah Clark

Daniel Joseph Serna

Richard Scot

Jeffery B Schroeder

David Joseph Walsh

Julie M Ingalls

Richard A McEntee

Jogeswar Sarma Malapaka

William Blake Belchee

Madhavi Mendu

Toni J Moore

K Kanaka Subramaniam

Susan E Teague Rector

Michael Raymond Epler

Jasmine Quintana

Candhadai Ramaswamy Varadharajan

Michael B Jones, Jr

Richard Gar Bentley

A system is provided for machine-learning based identification and filtering of electronic network communication. In particular, the system may continuously monitor and pull electronic communications data from one or more networked computing systems in an enterprise environment. Based on the electronic communications data, the system may use machine learning algorithms to generate a database of associations between one or more users and one or more topics of interest. The system may then output one or more recommendations to one or more users for transmitting communications associated with the one or more topics of interest. In this way, the system may improve the efficiency of communications received and transmitted within a network.

System for machine-learning based identification and filtering of electronic network communication

Systems, computer program products, and methods are described herein for dynamic node analysis for network security response. The present invention is configured to detect, using a node analysis engine, a change in a network security protocol associated with a first node within a distributed network; extract information associated with the change in the network security protocol associated with the first node; identify one or more adjacent nodes with a first degree of separation from the first node in response to detecting the change; determine a first set of changes to the network security protocols for the one or more adjacent nodes based on at least the information associated with the change in the network security protocol of the first node; and automatically implement the first set of changes to the network security protocols of the one or more adjacent nodes with the first degree of separation from the first node.

System for dynamic node analysis for network security response

Systems, methods, and computer program products are provided for monitoring network security in a mesh network. An example method includes receiving trust of service information relating to a user. The trust of service information includes one or more security details associated with at least one of a user device or a user network associated with the user. The method also includes determining a security level of a session involving the user based on the trust of service information relating to the user. The method further includes determining a security protocol for the session based on the determined security level. The security protocol determines at least one of a user access level or an additional security measure. The method still further includes causing an execution of the session based on the security protocol determined.

System and method for maintaining network security in a mesh network by analyzing IP stack layer information in communications

Systems, computer program products, and methods are described herein for self-clustering computing protocols. The present invention is configured to detect, using a node analysis engine, a change in a network security protocol associated with a first node or device within a distributed network, and transmit instructions for the first node or device to broadcast the change to nearby nodes or devices such that they can act in concert to protect against identifies security issues.

System and method for self-clustering edge computing protection

Embodiments of the present invention provide a system for monitoring a cybersecurity mesh network comprising a distributed sensor grid and a plurality of devices for detection of one or more security incidents. In response to determining that one of the one or more security incidents has occurred, and in response to receiving the request from an identified device that requires the first level of authentication, transmitting to the identified device a request for authentication credentials that meet a second level of authentication, wherein the second level of authentication is more strict than the first level of authentication.

Distributed sensor grid for intelligent proximity-based clustering and authentication

Aspects of the disclosure relate to a dynamic virtual reality (VR) coaching computing platform. The dynamic VR coaching computing platform may configure a VR coaching model based on model training data. The dynamic VR coaching computing platform may use the VR coaching model and a user profile to select a plurality of VR modules. The dynamic VR coaching computing platform may configure a first VR module of the plurality of VR modules based on one or more user selections. The dynamic VR coaching computing platform may receive real-time feedback during execution of the first VR module. The dynamic VR coaching computing platform may select a second plurality of VR modules based on the first real-time feedback. The dynamic VR coaching computing platform may configure a second VR module of the second plurality of VR modules based on user selections.

Dynamically providing virtual reality (VR) coaching using real-time feedback loops

A system for performing authorization of a user in an augmented reality environment comprises an augmented reality user device, an automatic teller machine, and an authentication server. The automatic teller machine has a keypad with unmarked buttons. The augmented reality user device includes a display configured to overlay virtual objects onto a field of view of a user. The augmented reality user device receives a virtual keypad overlay, which assigns values to the unmarked buttons of the keypad. Using the overlay, the augmented reality user device displays the assigned values on the buttons of the keypad. The automatic teller machine detects an input sequence entered on the keypad and sends the input sequence to the authentication server. The authentication server determines an authentication code by combining the input sequence with the virtual keypad overlay, and compares the determined authentication code with an authentication code stored in a database.

Augmented reality dynamic authentication

Aspects of the disclosure relate to cognitive automation-based engine processing to propagate data across multiple systems via a private network to overcome technical system, resource consumption, and architecture limitations. Data to be propagated can be manually input or extracted from a digital file. The data can be parsed by analyzing for correct syntax, normalized into first through sixth normal forms, segmented into packets for efficient data transmission, validated to ensure that the data satisfies defined formats and input criteria, and distributed into a plurality of data stores coupled to the private network, thereby propagating data without repetitive manual entry. The data may also be enriched by, for example, correcting for any errors or linking with other potentially related data. Based on data enrichment, recommendations of additional target(s) for propagation of data can be identified. Reports may also be generated. The cognitive automation may be performed in real-time to expedite processing.

Engine to propagate data across systems

Systems and methods for implementing sentiment analysis of computer code are provided. Developers who write source code may include comments or other natural language artifacts in the source code. These artifacts may be illustrative of current or legacy cybersecurity threats. Systems and methods may mine comments, and/or other code artifacts, for the dual purposes of cybersecurity threat detection and mitigation. Advanced code analytics may be leveraged for a deeper understanding of the sentiments expressed by the artifacts. Such sentiment may include negative sentiments expressed in error code selection and/or descriptions. All information retrieved is preferably human identity agnostic in line with personal data regulation compliance.

Sentiment analysis for securing computer code

Aspects of the disclosure relate to a cognitive automation based compliance management system. A computing platform may receive, via a network, an alert notification indicative of a change to a legal framework applicable to an enterprise organization. Subsequently, the computing platform may, in response to the alert notification, detect a task that may be impacted by the change. Then, the computing platform may, upon detecting the task, identify at least one task parameter associated with the task. Then, the computing platform may compare the at least one task parameter with the change to determine whether the task is impacted by the change. Subsequently, the computing platform may, upon a determination that the task is impacted by the change, recommend, via the network, one or more actions associated with the task.

Cognitive automation based compliance management system

Embodiments of the present invention provide systems and methods for automated and intelligent analysis of information. The system receives interaction data, interaction metadata, and external information in order to identify parties of interactions, subjects of interactions, and infer relationships between parties and subjects based on the content, context, frequency, and amount of available interaction data. Weighted score scores are generated and used to rank the inferred relationships and determined relevance between parties and subjects. This data may be stored in a graphical database and later used to response to user data queries to facilitate collaboration.

System for automated and intelligent analysis of data keys associated with an information source

A media verification device receives baseline media, which includes videos confirmed to include a target subject. The device determines, based on the baseline media for the target subject, a set of baseline features associated with the target subject. A baseline profile is determined for the target subject based on the set of baseline features. When test media which includes a video purported to include the test subject is received, test features are determined for the test media. A test profile is determined for the test media based on the set of test features. The test profile is compared to the baseline profile for the test subject. Based on this comparison, a confidence score is determined. If the confidence score is not greater than a threshold value, the test media is determined to include a synthetic video of the target subject, and an alert is provided.

Media verification system

A system for customizing media presentation based on user's sentiments is disclosed. The system presents a media item to the user on a platform comprising a website. The system captures a first set of microexpressions of the user reacting to the media item. The system extracts a set of baseline features from the first set of microexpressions. The system determines whether the media item elicits positive or sentiment from the user. If the system determines that the media item elicits positive sentiment from the user, the system classifies the media item into a first class of media items that elicit positive sentiment from the user. The system adjusts contents of the platform to include media items from the first class of media items.

System and method for leveraging a time-series of microexpressions of users in customizing media presentation based on users# sentiments

Typically, a business desires to track and monitor all applications run on its servers. Nonetheless, one or more unauthorized applications may be running on the business's servers, exposing the business to potential regulatory liability and security breaches. Apparatus and methods are provided for isolating and disabling one or more unauthorized applications running on a server. The apparatus may comprise a system including a content-filtering web proxy server configured to filter outgoing requests and data associated with the requests. The system may also include a remediation framework configured to monitor request data in a proxy log stored by the proxy server. The remediation framework may be triggered to perform remedial action when the remediation framework determines that a request and associated data, as stored in the proxy log, meets predetermined conditions. The remediation framework, when triggered, may execute steps to truncate functionality of the unauthorized applications.

Optimization of redundant usage patterns based on historical data and security constraints

Growing community of inventors

Easton, CT, United States of America

Michael Ogrinz