Bank of America Corporation

Sujatha Balaji

Srilaxmi Sreepalli

Ramachandran Periyasamy

Sneha Mehta

Ankit Agarwal

Sarath Kumar Navarajan

Rajapandian C

Rajapandian Chellimuthu

Swapnil Sharma

Sandhya Eranki

Embodiments of the invention are directed to systems, computer program products, and methods for assigning geospatial data to tokenized resources via a bridge protocol. The present invention is structured to electronically receive, over a distributed network, a request for a token for a resource. Thereafter, a token generator is initiated and the token is generated, wherein the token comprises resource information and the token is published on a marketplace. Resource information is transmitted to or from the token via a bridge, the resource information comprising geo-spatial data from a geo-spatial analyzer. Thereafter, a consensus is obtained, and the token is recorded on a distributed network.

System and method of assigning geospatial data to tokenized resources via a bridge protocol

Arrangements for providing secure document distribution are provided. In some aspects, a request to distribute a file may be received. The request may include identification of the file being distributed, as well as identification of a recipient. The identified file may be encrypted and stored in a distributed hash table. In some examples, a file reference key associated with the encrypted file may be generated and stored in a distributed ledger. A secure QR code based on the file reference key may be generated and transmitted to a recipient computing device. In some arrangements, an indication of a scan of the secure QR code may be received. Responsive to receiving the indication of the scan, the file reference key may be retrieved and a decrypted file of the encrypted file may be generated and provided to the recipient for viewing and/or downloading.

Distributed computing system for secure document routing

A system for implementing intelligent interactions in a metaverse comprises a metaverse server in communication with an entity server. A metaverse server receives an interaction request for an interaction session from a first user avatar to obtain a digital item in a virtual environment. The metaverse server determines an item value of the digital item is greater than the first asset value, determines a supplement asset required for the first user to obtain the digital item, and sends an asset request with the supplement asset to an entity avatar. The entity server determines that the supplement asset in a first asset pool in a database. The entity server generates digital contracts to receive the supplement asset and send the supplement asset to the metaverse server. The metaverse server completes the interaction session with the first asset and the supplement asset to obtain the digital item for the first user avatar.

System and method for implementing intelligent interactions in a metaverse

A multi-level, ensemble network monitoring system for detection of suspicious network activity from one or more a plurality of user computing devices on an external network communicatively connected via a network server to a private communication network is disclosed. In malware detection, the ensemble network monitoring system comprises artificial intelligence (AI) with bidirectional long short-term memory (BDLSTM) recurrent neural networks (RNNs) and natural language processing (NLP) to predict possible security threats and then initiate remedial measures accordingly. Enabling a proactive approach to detection and prevention of potential malicious activity, the BDLSTM RNN may perform real-time monitoring and proactively forecast network security violations to block network communications associated with high-risk user computing devices from accessing a private communication network.

Malware detection with multi-level, ensemble artificial intelligence using bidirectional long short-term memory recurrent neural networks and natural language processing

Aspects of the disclosure relate to geocoding geocode datasets in KYC blockchain data blocks for spatial analytical risk modeling. In some embodiments, a computing platform may receive a client request to initiate a transaction with an enterprise organization. Using financial documentation and identification documentation associated with the client request, the computing platform may generate geocode coordinates and may identify a series of geographic risk factors. The computing platform may translate the geocode coordinates and the geographic risk factors into analytical overlays. The computing platform may stack the analytical overlays to generate an interactive spatial risk analysis model. The enterprise organization may use the interactive spatial analytical risk model to analyze the client request, and to determine whether to approve or deny the client request.

Geocoding geocode datasets in know your customer blockchain data blocks for spatial analytical risk modeling

A system is provided for a distributed server network with embedded image decoder as a chain code program runtime event. In particular, the system may comprise a distributed computing network comprising one or more decentralized nodes, each of which may store a separate copy of a distributed data register. The system may further comprise one or more specialized nodes which receive, assess, and analyze user input data, where the one or more specialized nodes may include a client identity node comprising an embedded image decoder which may be configured to analyze image portions of the user input data. Once the image data has been analyzed, the client identity node may convert the image data into a text format for storage within the distributed register.

System for distributed server network with embedded image decoder as chain code program runtime

A system provides for data consensus validation in an electronic distributed server network using a screening node. In particular, a distributed database may be hosted on nodes operated by one or more third party entities. The screening node may retrieve reference data, which may be submitted by one or more reference data providers, from the distributed database to generate executable scripts from the screening algorithms within the reference data. The scripts may in turn be validated by the nodes of the distributed database and subsequently embedded into the distributed database for execution by one or more computing systems within the network environment.

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Tamil Nadu, India

Sujatha Balaji