Bank of America Corporation

George Albero

Maharaj Mukherjee

Elijah Clark

Edward Lee Traywick

Jinna Zevulun Kim

Scot Lincoln Daniels

Dustin Paul Stocks

Jake Michael Yara

Olga Kocharyan

Rick Wayne Sumrall

Konata Stinson

Emanuel David Guller

Manu Jacob Kurian

Cody Dean Searl

Deborah Mayers

Benjamin D Moores

Naga Vamsi Krishna Akkapeddi

William August Stahlhut

Elizabeth R Liuzzo

Kevin A Delson

Kyle A Mayers

Michael Beveridge

Youshika C Scott

Charlene L Ramsue

Gulsen Saffel

Elizabeth Jordan Knight

Lauren Thanh Nguyen-Lo

Robert Jon Armstrong

Nathalie Elizabeth Conley

Keaton Drake

Michael Robert Young

Michael Ogrinz

Siten Sanghvi

Heather Roseann Dolan

Morgan Stewart Allen

Prashant Thakur

Caleb G Mann

Madhavi Mendu

Elena Kvochko

Marci Landy

Brian H Corr

Daniel Horne

Karen E Davis

Elizabeth Swanzy-Parker

Robert A Lang

Scott Nielsen

Thomas G Frost

David Joseph Walsh

Timothy Scott Murphy

Amit Pandey

Ariel Fontaine Hill

Daniel Martin

Paul Swiencicki

Guisen Saffel

Stephen C Brown

Pratap Dande

Saurabh Arora

Monika Kapur

Christopher Daniel Birch

Daniel Joseph Serna

James J Siekman

Richard Scot

Carrie Elaine Gates

Sanjay Arjun Lohar

Robert Nyeland Huggins

Jeffrey Kyle Johnson

Lisa Snow Pugh

Ron Papka

Jon Codispoti

Kathleen Rae Hablutzel

Michael B Jones, Jr

Hannah Kaplan

Kristoffer Matthew Bertsch

Elizabeth Rhodes Kral

Andrew Sides

Anna Maria Mirarchi

Anna Xu

Samantha Ilse Quales

Nagasubramanya Lakshminarayana

Yuvraj Singh

Jeffrey Felipe

Karen Macqueen

Durga Prasad Kuttumolu

John Scott Alston

Aspects related to an amalgamation platform providing concealed detection of code-passing using steganography are provided. An amalgamation platform may train a scoring engine to generate suspicion scores for code snippets and an amalgamation engine to generate execution scenarios for the code snippets. The platform may embed code in base code of a network using steganography. The platform may use the steganographic code to detect transmission of a code snippet. The platform may generate a suspicion score for the code snippet. The platform may update the scoring engine based on identifying the suspicion score satisfies a threshold. The platform may generate execution scenarios for the code snippet. The platform may determine a match between an execution scenario and a malicious code scenario. The platform may identify the code snippet as malicious and update the amalgamation engine based on the match. The platform may initiate security actions based on the match.

Amalgamation platform providing concealed detection of code-passing using steganography

A method is provided that includes receiving a request to perform an interaction that includes user data and device data. The method includes splitting the user data into one or more logical data components. The method includes comparing the one or more logical data components to one or more predetermined validation thresholds. The method includes determining whether the one or more logical data components satisfy the one or more predetermined validation thresholds. In response to determining that the one or more logical data components satisfy the one or more predetermined validation thresholds, the method includes obfuscating the one or more logical data components to generate one or more unique identifiers, and obfuscating the device data to generate a unique device identifier. The method includes generating an authentication response configured to authorize the external entity server to perform the interaction that includes the unique identifiers and unique device identifier.

System and method for validating an interaction

A system and method for synchronizing data changes. The system is configured to receive a notice from a client device that the client device has updated data and request metadata related to the updated data from the client device that indicates at least a type of data associated with the updated data. The system compares the metadata with first application information and second application information to determine if the first external application or the second external application uses the type of data indicated in the metadata and causes the updated data to be communicated to the first external application but not the second external application when the first external application uses the type of data indicated in the metadata but the second external application does not use the type of data indicated in the metadata.

System and method for automated synchronization of data

Embodiments of the present invention provide a system for generating a real-time audio token for multi-factor audio authentication. The system is configured for determining that a user is accessing an entity resource, via a user device of the user, causing a cryptographic device associated with the user to generate and emit a dynamically varying continuous audio tone, performing authentication of the user based at least in part on the dynamically varying continuous audio tone, determining that the authentication based at least in part on the dynamically varying continuous audio tone is successful, and allowing the user to access the entity resource based on determining that the authentication based at least in part on the dynamically varying continuous audio tone is successful.

Device for generating a real-time audio token for multi-factor audio authentication

Automatically and covertly activating audio/video mechanisms within a mobile communication device when a user is confronted with a duress-inducing event or a situation based on receipt of a duress indicator. The duress indicator is a subtle user input, such as a personal gesture, personal audible code or device input that triggers the covert activation of audio/video recording mechanisms on a mobile communication device. As a result, audio and/or video data of a duress-inducing event can be captured absent other parties to the duress-inducing event being aware that audio/video data is being captured.

Indicator triggered activation of audio/video recording devices within a mobile communication device

Verification of peer-to-peer network transmission occurs implementing AI to determine a match between the purpose/intent of the peer-to-peer network transmission as defined by the sending entity/peer and the purpose/intent of the peer-to-peer network transmission as defined by the recipient entity/peer. The sending peer initiates communication of a peer-to-peer network transmission, which identifies the recipient peer and purpose of the transmission. The peer-to-peer network transmission is captured and held in a transmission pending queue. A push notification is communicated to the recipient entity/peer identified in the transmission, which requests input of their perceived purpose/intent of the transmission. Once the recipient entity/peer identified in the transmission responds with their purpose of the transmission, an AI model trained to determined matches between inputted purposes/intents is executed. Once the AI model determines a purpose/intent match, the transmission is released for the transmission pending queue, so that further communication and/or processing of the transmission occurs.

Peer-to-peer network transmission verification system

Authentication/verification of sub-environments that represent entities within an augmented/virtual reality computing network and virtual objects present in the sub-environment that represent individuals associated with the entity. In response to authentication, a sensory-perceptible indicator (e.g., visual, audible or haptic indicators) is presented to users of the virtual reality computing environment that notify the user that the entity or virtual objects representing the entity have been authenticated. Authentication may be performed via watermarks embedded in images present within the sub-environment, capturing and comparing physical characteristics of an authorized individual representing the entity, cryptographic frequency hopping and/or electromagnetic signatures.

Entity authenticator in augmented or virtual reality computing environments

A system is provided for remediating computing system breaches by reversibly distributing data to a plurality of edge points in a distributed network. In particular, the system may intelligently track network data to predict breach vector pathways and may track various types of network traffic data for computing systems within the network. Based on the network traffic data, the system may generate a network topology, mapping the various types of network connections across the computing systems in the network environment as well as the datasets that were transferred across such connections. In the event of a system breach, the system may divide each dataset into a plurality of partial data packets. The system may transmit each partial data packet to a different user device or computing device in the network. After the breach is remediated, the system may recall the individual data packets and reassemble the datasets for future use.

Establishing dynamic edge points in a distributed network for agnostic data distribution and recovery

Systems, computer program products, and methods are described herein for implicit item embedding within a simulated electronic environment. In various embodiments, the invention includes utilizing a hybrid recommendation engine, the invention suggests product placements based on user data and preferences of a specific user. During the initial warm-up period, either user-based or product-based collaborative filtering is applied to assign the user to a collaborative user group until more information about the user becomes available. The hybrid recommendation engine is enhanced through a collaborative clustering component, which involves assigning the user to the collaborative user group via user-based collaborative filtering based on their similar user characteristics, product interests, or product preferences. The invention dynamically alters digital content streamed to the user's device. An implicit product placement module integrates recommended products within the entertainment content, providing a seamless and personalized experience for the user.

System and method for implicit item embedding within a simulated electronic environment

Aspects of the disclosure relate to predicting the spread of malicious software. The computing platform may identify malicious software at a computing device and may input characteristics of the malicious software into a machine learning model to produce time horizons for the malicious software. The computing platform may identify, using a knowledge graph and based on the time horizons, subsets of computing devices, each corresponding to a particular time horizon. The computing platform may perform, at a time within a first time horizon, a first security action for a first subset of computing devices within the first time horizon and a second security action for a second subset of computing devices located within a second time horizon, where the first time horizon and the second time horizon indicate that the first subset will be affected by the malicious software prior to the second subset.

Hybrid machine learning and knowledge graph approach for estimating and mitigating the spread of malicious software

Systems, computer program products, and methods are described herein for automated translation of digital multimedia. The present disclosure is configured to receive, from a user input device, a search request; determine the response for the search query in a first natural language, wherein the response comprises digital multimedia; reconfigure the response for display on the user input device in the preferred natural language, wherein reconfiguring further comprises: determining an intermediate natural language based on a lexical similarity with the preferred natural language; translating, using a first natural language translation subsystem, the response from the first natural language to the intermediate language; and translating, using a second natural language translation subsystem, the response from the intermediate language to the preferred natural language; and display the reconfigured response on the user input device in the preferred natural language.

Natural language generation system for automated translation of digital multimedia

A system is provided for implementing time-restricted access control to electronic digital resources. In some embodiments, the custom set of executable code used to generate the digital resource may provide granular control over access restrictions for accessing, viewing, and/or transferring the digital resource. Such access restrictions may include time duration restrictions, access frequency restrictions, data quality restrictions, and/or the like. In this way, the system may limit access to the digital resource in a secure manner.

System and method for implementing time-restricted access control to electronic digital resources

A computing platform may receive, from a plurality of IoT information sources, historical information associated with a user. The computing platform may generate, based on the historical information, a user specific policy, defining information distribution rules for the user. The computing platform may receive, from an information collection system, a request for information. The computing platform may identify whether or not the request for information requests personal information of the user. Based on identifying that the request for information requests the personal information of the user, the computing platform may identify whether or not the requested personal information violates the user specific policy. Based on identifying that the requested personal information does not violate the user specific policy, the computing platform may obscure the requested personal information, and send, to the information collection system, the obscured personal information.

Permission based information transfer based on internet of things (IoT) insights

Aspects of the disclosure relate to message validation. A computing platform may receive a message, sent by a first device and directed to a second device, from an electronic messaging server. The computing platform may verify, based on message sender details, an identity of a sender of the message. The computing platform may generate, after verifying the identity of the sender of the message, an authentication token for the message, and may inject the authentication token into the message. The computing platform may route, to the electronic messaging server and after injecting the authentication token into the message, the message. The computing platform may receive a request to validate the message, which may include the authentication token and details of the message. The computing platform may identify, using the authentication token and the details of the message, that the message is authenticated.

Email verification using injected tokens for message authentication

User authentication/login occurs prior to a user accessing a network, application, web site/service or coming in contact with a computing device. Pre-authenticating/logging-in of users in advance of the user visiting or accessing the computing technology. A single device passcode that unlocks the device and a passcode vault storing the user's passcodes. Unlocking the passcode vault provides for the passcodes stored therein to be automatically applied to the corresponding entities requiring authentication to grant users access without requiring any user input/actions. Machine-Learning (ML) models that are trained to learn user login patterns are implemented to identify login pattern(s) and subsequently passcodes are retrieved for the entities making up the login pattern(s) from the passcode vault. Prior to the user accessing the entities that make up the login pattern, the present invention accesses the entities and applies the retrieved passcodes to pre-authenticate the user.

Pre-access automated login to computing devices, applications and web sites/services based on machine-learning determined user access patterns

Growing community of inventors

Charlotte, NC, United States of America

George Albero