Bank of America Corporation

Other

John Christopher Checco

Patrick Nicholas Lawrence

Joseph Benjamin Castinado

Jisoo Lee

Suki Ramasamy

William August Stahlhut

Brad Romano

Lekha Ananthakrishnan

Michael Ogrinz

Ryan Muzzo

Victoria Lynn Dravneek

Hitesh Shah

William P Jacobson

Jesse Strickland Newsom, Iii

David Hsiang

Elena Kvochko

John Ryan Bowling

Aspects of the disclosure relate to data sharding for transmission over a high generation cellular network. A computing platform may detect, via a communication network, transmission of data from a first computing device to a second computing device. Subsequently, the computing platform may intercept, prior to receipt of the transmission by the second computing device, the data. Then, the computing platform may shard the data into a first shard and a second shard. Then, the computing platform may identify, within the communication network, a first communication channel and a second communication channel. Then, the computing platform may send, to the second computing device, the first shard via the first communication channel, and the second shard via the second communication channel. Subsequently, the computing platform may merge, the first shard and the second shard, to reconfigure the data.

Data sharding for transmission over a high generation cellular network

Methods and systems for using block chain technology to verify transaction data are described herein. A computing platform may receive data about events related to transactions, personal or corporate information, supply chains, and other relevant information about a person or corporate entity. The event information may be received, aggregated, and processed to determine metadata about the person or corporate entity. The metadata may indicate, for example, a trustworthiness of the person or corporate entity for various purposes. Such event information and/or metadata may be stored as transactions in a block chain that may be accessible by counterparties to a potential transaction involving the person or corporate entity. The automated event processing computing platform may further use automated techniques to implement smart transactions between the person/entity and counterparty based on the trust metadata.

Automated event processing computing platform for handling and enriching blockchain data

Aspects of the disclosure relate to optimizing authentication and management of wireless devices in zero trust computing environments. In some embodiments, a computing platform may receive, from a user computing device, a connection request. Subsequently, the computing platform may generate, using an artificial-intelligence engine, a profile for the connection request. Based on the profile for the connection request generated using the artificial-intelligence engine, the computing platform may determine that the connection request is valid. In response to determining that the connection request is valid, the computing platform may establish a connection with the user computing device. Based on establishing the connection with the user computing device, the computing platform may assign an identity to the user computing device. After assigning the identity to the user computing device, the computing platform may monitor behavior of the user computing device based on the identity assigned to the user computing device.

Optimizing authentication and management of wireless devices in zero trust computing environments

A method for authenticating to a network comprising a plurality of Internet of Things ('IoT') devices is provided. The method may include using a mobile telephone apparatus, a wrist-worn apparatus and a head-worn apparatus to monitor the level of at least one of a wearer's pulse, body temperature, voice, gait and/or other biorhythmic indicator. One of the aforementioned apparatus may operate as a hub apparatus. The method may further include using the hub apparatus to assign a federated biometric marker based at least in part on the first, second and third biometric markers. The method may also include using artificial intelligence to monitor for one or more outliers with respect to historical monitoring. Each of the one or more outliers may include a magnitude that exceeds a security threshold difference between the current magnitude and the historically monitored magnitude. When the difference in magnitude exceeds a security threshold difference between the current magnitude and the historically monitored magnitude the method may quarantine apparatus associated with the outlier.

Multi-biometric-factor, internet of things (IoT), secured network

A supply chain for a batch of identical units is provided. The supply chain includes database architecture. The batch of units may include a distributed ledger (blockchain) identification (ID), and at least two additional pieces of information. The information includes a serial number of the batch, a location of manufacture of the batch, an ID associated with the source of the batch, and/or the ID(s) of one or more components of each unit in the batch. The supply chain may include a private database supplier key. The supplier key enables publishing of batch transaction information onto a blockchain. The information may include a transfer of control of the batch from the supplier to a receiver-manufacturer. The supply chain may further include a private database receiver-manufacturer key associated with each batch associated with the receiver-manufacturer. The private database manufacturer key enables the receiver-manufacturer to review transactions associated with each batch.

Blockchain-based supply chain certification systems and methods

Methods, systems, and apparatuses for blockchain-based unexpected data detection are described herein. In some arrangements, a node within a decentralized peer-to-peer (e.g., P2P) network may receive a plurality of network function requests corresponding to the decentralized network. The node may analyze the plurality of network function requests to identify whether the requests included unexpected data and/or irregular data, and/or are associated with flagged wallets and/or smart contracts.

Blockchain-based unexpected data detection

Apparatus and methods for a reverse proxy server are provided. The reverse proxy server may provide compatibility and security for nodes on an IoT network. A reverse proxy server may normalize inter-node communications. A reverse proxy server may identify an IoT node and upon identification of the node, determine native communication protocol(s) specific to the node. The reverse proxy server may encapsulate data transmitted via the native communication protocol. The reverse proxy server may impose a principal-agent relationship. For example, the reverse proxy server may be a principal of one or more nodes (agents) on the IoT. The reverse proxy server may enforce security protocols on all agents. An agent (e.g., node) may be required to route all communications to other IoT devices through the principal (e.g., reverse proxy server). An IoT network may include more than one reverse proxy server. Each agent may have one or more principals.

Reverse proxy server for an internet of things ('IoT') network

A method for executing a smart recall of a plurality of manufactured units is provided. The method may include, inter alia, using a database architecture to administer a supply chain for the units, assigning each component of the units a distributed ledger (blockchain) identification (ID), and additional pieces of information such as a serial number of the component, a date of manufacture of the component, a location of manufacture of the component, an ID associated with the source of the component, and/or the ID(s) of one or more subcomponent unit(s) of the component. The assigned information is stored in the database architecture. The method may also include generating a private database supplier key and a manufacturer key. The method further includes: transmitting a notice to downstream manufacturers, transmitting a notice to a regulatory agency to implement safety procedures and/or unit and transmitting a recall notice.

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Stony Point, NY, United States of America

John Christopher Checco