Bank of America Corporation

Erik Dahl

Pratap Dande

Rahul Yaksh

Elvis Nyamwange

Amer Ali

Brian Neal Jacobson

Sailesh Vezzu

Rahul Shashidhar Phadnis

Steven Reich

Vishwanath Prasad Karra

Tileshia Brenda Alford

Hari Vuppala

Gilbert M Gatchalian

Vijaya L Vemireddy

James J Siekman

Richard Scot

Sanjay Arjun Lohar

Benjamin F Tweel

Dinesh Kumar Agrawal

Steven Nathan Greene

Systems, computer program products, and methods are described herein an automated system for restarting large scale cluster supercomputers. The present disclosure is configured to receive a request to reboot a supercomputer cluster, wherein the request comprises a sequence of reboot instructions; determine, using a data integrity engine, whether a current state of the supercomputer cluster meets reboot requirements, wherein the reboot requirements are associated with a core logic of the data integrity engine; and execute the sequence of reboot instructions in an instance where the current state of the supercomputer cluster meets the reboot requirements.

Automated system for restarting large scale cluster supercomputers

An apparatus may include conduction of a secure transfer at a point of identification using image recognition and blockchain authentication. The apparatus may include a computer processor, a camera, an image capturing machine, a reference database, an XGBoost image recognition machine learning model, and a blockchain. The computer processor may be an edge computing device. The computer processor may be configured to identify a user at a point of identification by capturing an image, running the Features detection engine to identify sets of features, running the XGBoost image recognition machine learning model to identify labels in the sets of features, and matching the sets of features and labels to a record in the reference database. The computer processor may further be configured to seek user approval on the user's portable device before providing the transfer. Once the user has approved the transfer, the transfer may be recorded in the blockchain.

Automated image detection utilizing a convolutional XGBoost image recognition machine learning model on edge computing with blockchain mobile authentication

Aspects of the disclosure relate to detecting attempts to violate the security of an ATM. A computing system may determine whether an ATM is being used to perform a transaction. Based on the ATM not being used to perform a transaction, images of portions of the ATM may be generated. Estimated dimensions of the ATM may be determined. Digital twin data may be retrieved. The digital twin data may comprise a digital twin representation of the ATM and measured dimensions of the ATM. There may be a determination of whether the estimated dimensions of the ATM match the measured dimensions of the ATM. Based on the estimated dimensions of the ATM not matching the measured dimensions of the ATM, the ATM may be deactivated. Furthermore, a message indicating that the ATM was deactivated may be sent to a validation computing system.

Automated teller machine digital twin with an anti NFC/RFID skimming threat device through mist computation

Arrangements for detecting unauthorized activity based on input method analysis and monitoring are provided. In some aspects, identity information associated with a user may be received and be stored. An input may be received from a computing device of the user. An input pattern of the received input may be determined. Using a machine learning model, the input pattern of the received input may be compared to input patterns of humans and input patterns of machines. Based on the comparison, it may be determined whether the user is a human user or a non-human user. Responsive to determining that the user is a non-human user, a request may be transmitted to the user to provide increased authentication credentials. Responsive to determining that the user is a human user, an identity of the user may be verified by comparing the input pattern of the received input to the stored identity information.

Unauthorized activity detection based on input analysis and monitoring

An application mapping engine may determine dependencies in existing executable application by monitoring and analyzing process flow and data flow of the application during runtime execution. The application mapping engine may generate dependency visualization maps that illustrate dependency interaction information.

Application dependency visualization

A system is provided for implementing technology infrastructure upgrades using an automated electronic data aggregation tool. In particular, the system may receive a request from an endpoint device to generate a technology remediation framework for remediating a technology infrastructure issue. In response to the request, the system may use an automated electronic data aggregation tool to receive data associated with the technology infrastructure issue from one or more data sources. The system may then automatically generate the technology remediation framework using the received data and present the framework to one or more users associated with the technology infrastructure issue. In this way, the system provides an efficient way to implement upgrades and remediate issues within a technology infrastructure.

System and method for implementing technology infrastructure upgrades using an automated electronic data aggregation tool

Systems, computer program products, and methods are described herein for a machine learning based system for optimized CPU utilization in data transformation. The present disclosure is configured to receive a new data segment; retrieve characteristics of the new data segment; determine, using a trained machine learning model, an encryption algorithm, and a compression algorithm for implementation on the new data segment based on at least the characteristics of the new data segment; determine, using the trained machine learning model, an order of implementation associated with the implementation of the encryption algorithm and the compression algorithm; and implement the encryption algorithm and the compression algorithm on the new data segment in the determined order of implementation.

Machine learning based system for optimized central processing unit (CPU) utilization in data transformation

Systems, computer program products, and methods are described herein for tracking cross border data transmissions and generating a data passport entry in an electronic network. The present disclosure is configured to receive a file, the file comprising file data; receive an origination location identifier and destination location identifier of the file; parse the file data and apply a natural language processor to the file data to generate a structured meaning of the file data; compare the structured meaning of the file data to a theme database to generate a file theme score; determine, based on the destination location identifier, a destination theme score; generate a hash value for the file; and generate a data passport entry for the file based on the file name, the origination location identifier, the destination location identifier, the file theme score, the destination theme score, the hash value, and a count score.

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Newark, DE, United States of America

Erik Dahl