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

Rick Wayne Sumrall

Konata Stinson

Emanuel David Guller

Manu Jacob Kurian

Cody Dean Searl

Olga Kocharyan

Deborah Mayers

William August Stahlhut

Elizabeth R Liuzzo

Benjamin D Moores

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 Ogrinz

Siten Sanghvi

Naga Vamsi Krishna Akkapeddi

Heather Roseann Dolan

Madhavi Mendu

Caleb G Mann

Michael Robert Young

Elena Kvochko

Morgan Stewart Allen

Marci Landy

Brian H Corr

Daniel Horne

Karen E Davis

Elizabeth Swanzy-Parker

Robert A Lang

Scott Nielsen

Thomas G Frost

David Joseph Walsh

Daniel Martin

Paul Swiencicki

Guisen Saffel

Stephen C Brown

Pratap Dande

Monika Kapur

Christopher Daniel Birch

James J Siekman

Daniel Joseph Serna

Richard Scot

Carrie Elaine Gates

Sanjay Arjun Lohar

Robert Nyeland Huggins

Prashant Thakur

Jeffrey Kyle Johnson

Ron Papka

Jon Codispoti

Timothy Scott Murphy

Lisa Snow Pugh

Amit Pandey

Ariel Fontaine Hill

Hannah Kaplan

Kristoffer Matthew Bertsch

Elizabeth Rhodes Kral

Anna Maria Mirarchi

Andrew Sides

Anna Xu

Samantha Ilse Quales

John Scott Alston

Michael B Jones, Jr

Alternative distribution/communication of and access to One-Time Passwords/Passcodes (OTPs). Triggering events are detected that result in the OTP being communicated to a communication device different from the device designated by the user for receiving OTPs. The triggering event may be determination that the user's designated device (i) is not currently in possession of the user, (ii) is located in a geo-location designated for No-OTP receipt, and/or (iii) is currently in an inoperable state. The different communication device may be a device other than one in possession/control of the user and may be a device designated by the user or the device may be one selected, based on proximity of location to the user, from a network of trusted devices/individuals.

Alternative distribution and accessing of one-time passwords (OTPs)

A computing platform may train, using historical call information, a prompt generation model to identify, for an initiated call between a first individual and a second individual, one or more security prompts to validate an identity of the first individual. The computing platform may detect and temporarily pause a call. The computing platform may input, into the prompt generation model, information of the call, which may cause the prompt generation model to output the security prompts, which may be customized CAPTCHA tests based on the information. The computing platform may send, while the call is paused and to a user device of the first individual, the security prompts. The computing platform may receive, while the call is paused and from the user device, responses to the one or more security prompts. The computing platform may validate, while the call is paused, the responses, and resume the call.

Automated vishing detection to prevent deepfake and chatbot attacks

Aspects of the disclosure relate to energy optimization. A computing platform may receive a cryptocurrency request indicating a gas price and KPIs of the cryptocurrency request. The computing platform may input the gas price and the KPIs into a mining optimization model, which may cause the mining optimization model to output an energy mix for use in processing the cryptocurrency request. The energy mix may indicate energy sources, capable of providing an amount of energy needed to process the cryptocurrency request and used to support operation of a data center configured to process cryptocurrency requests, and a cost of the amount of energy from the energy mix may be less than a cost of the amount of energy from other available energy sources. The computing platform may send commands directing the data center to process the cryptocurrency request using the energy mix, which may cause it to do so.

Energy optimization platform for cryptocurrency mining

A device for performing a secured operation is disclosed. The device is embedded with a predefined data item and verification information. The verification information is uniquely associated with the user of the device. The verification information is linked to the identity of the user. The verification information is configured to be extracted in conjunction with the secured operation being performed. The secured operation is performed in response to the verification information being verified. A system and method for performing the secured operation are also disclosed.

System, device, and method for performing secured operations

Various aspects of the disclosure relate to monitoring a physical location to determine and/or predict anomalous activities. One or more machine learning algorithms may be used to analyze inputs from one or more sensors, cameras, audio recording equipment, and/or any other types of sensors to detect anomalous measurements/patterns. Notifications may be sent one or more devices in a network based on the detection.

Artificial intelligence (AI)-based security systems for monitoring and securing physical locations

A computing device may configure a plurality of device partitions. The computing device may send, to a one time password (OTP) server and via an interface of a first partition of the plurality of device partitions, a login request. The computing device may receive, at a second partition of the plurality of device partitions, an OTP. The computing device may access, by validating authentication credentials corresponding to the second partition of the plurality of device partitions, the OTP. The computing device may send, to the OTP server, the OTP. The computing device may access, upon receiving confirmation of validation of the OTP, services hosted by the OTP server.

Enhanced security with multiple factor authentication at devices using partitions

A security feature within an apparatus that includes a fingerprint scanner used for purposes of authentication. Specifically, a first indicator is detected that is a user input to a fingerprint scanner and indicates the occurrence of a duress-inducing event. In response to detecting the first indicator, (i) access to the apparatus is controlled, and (ii) access to functionality provided by the apparatus is controlled. As such, if the user is being forced to input their fingerprint by a nefarious entity desiring access to the apparatus, the present invention provides a means by which the user can covertly activate certain features on the apparatus that prevent the nefarious entity from access to the apparatus and/or functionality provided by the apparatus.

Fingerprint authentication-related indicators for controlling device access and/or functionality

Arrangements for continuous authentication and secure access control are provided. In some aspects, a computing platform may receive user data from a plurality of user data sources. The user data may include a plurality of different data types. The computing platform may use the user data to train a machine learning model, which may then be used to generate user specific baseline data. Subsequent user data may be received and analyzed, using the machine learning model, to determine whether an anomaly exists between the subsequent user data and the baseline data. If not, the user may be considered authenticated and second user data may be received and analyzed to continuously authenticate the user. If an anomaly is detected, the anomalous data and other data may be further analyzed to determine whether to authenticate the user or execute a response action.

Multi-computer system for providing continuous authentication and secure access control

Aspects of the disclosure relate to energy optimization. A computing platform may receive an event processing request. The computing platform may identify parameters of the event processing request. The computing platform may input the parameters into a global energy optimization model, to identify an edge computing system at which to process the event processing request. The computing platform may route the event processing request to the edge computing system along with commands to process the event processing request using an energy mix identified by a local energy optimization model, corresponding to the edge computing system, which may cause the edge computing system to: input the parameters of the event processing request into the local energy optimization model to identify the energy mix, and process, using the energy mix, the event processing request.

Energy optimization platform using artificial intelligence and edge computing

Systems, computer program products, and methods are described herein for data protection in a distributed network via reconstruction and analysis of data segments. The present invention is configured to initiate a network flow analysis to assign indicators to specialized access nodes of a network diagram, execute a first cut to remove predetermined nodes, store the corresponding discrete data segments for each of the first plurality of electronic communications at the nodes, construct a first arrangement of a selected group of the corresponding discrete data segments, determine a presence of sensitive information, and construct additional arrangements of the selected group of the corresponding discrete data segments to determine a presence of sensitive information.

System and method for data protection in a distributed network via reconstruction and analysis of data segments

Real-time adjustment of the volume of passcode entry authentication attempts is performed based on systematic determinations of the likelihood that the passcode entrant is the rightful holder/user of the active passcode. Specifically, after an entered passcode has been determined to be incorrect, a determination is made as to the likelihood that the passcode entrant is the rightful holder of the active passcode and, based on such a determination, the number of authentication attempts afforded the passcode entrant is either increased, decreased or exhausted. Systematic determination of the likelihood that the passcode entrant is the rightful holder/user of the active passcode is accomplished by applying predetermined mismatched passcode rules and comparing machine learning (ML)-based user authentication behavior patterns to characteristics of the current authentication attempt.

Real-time adjustment of the volume of passcode entry authentication attempts

An illustrative computing system for a weblink content scanning system scans an electronic message for the presence of one or more weblinks. The computing system accesses, in a sandbox computing environment, content linked to the one or more weblinks. The computing system generates a hash of the accessed content and/or content linked to weblinks accessible via the accessed content. The computing system scans the content accessed via the one or more weblinks for a presence of malicious content and categorizes the scanned content accessed via the one or more weblinks (e.g., safe, malicious, and the like), associates the categorization with each corresponding hash, and saves such information to a data store for future analysis. Based on a result of this analysis, the computing system allows delivery of the original electronic message or generates a modified electronic message for delivery to a recipient device.

Scanning of content in weblink

A system is provided for monitoring real-time data inputs across multiple channels, determining potential impacts to a network or entity policy taxonomy, and taking one or more automated, responsive actions based on determined impacts. In this way, the system described herein is able to optimize system processes and system protections on an enterprise-wide scale in response to current events, policy or regulation changes, or predicted measures taken by private or public entities that may necessitate adaptation of one or more workflow processes or technology taxonomies, either upstream or downstream of the system itself.

Event based network micro-segmentation modeling for user authenticated access to distributed network system segments

Detecting malicious/spoofed Universal Resource Locators (URLs) and/or files in received electronic mail (i.e., email) and, in response to detection, automatically taking responsive measures to prevent interaction/access to the malicious/spoofed URLs and/or files and/or limit, network-wide, the exposure to the malicious/spoofed URLs and/or files. Valid URLs and/or files are assigned a token, such as an alpha-numeric passcode or the like and the assigned token is verified upon receipt of the email by the intended recipient. In the event that the token cannot be verified or a token is not received for a URL or file, the automated responsive actions ensue.

Malicious universal resource locator and file detector and response action engine

A system is provided for containerization-based countermeasures to cybersecurity vulnerabilities. In particular, the system may generate one or more containers (e.g., virtual environments), where each container may be configured to execute one or more tasks. At least a portion of the containers may be decoy containers that may be executing one or more decoy tasks. The system may then use a randomized process to change which containers are decoy and/or which tasks or jobs are executed within each container. Each container may be associated with a cryptographic key such that each container may be hashed by the system and compared against a reference hash associated with the container. If the hash has changed, the system may determine that the container has been modified and subsequently implement one or more intelligent remediation processes.

System for containerization-based countermeasures to cybersecurity vulnerabilities

Growing community of inventors

Charlotte, NC, United States of America

George Albero