Bank of America Corporation

Prashant Anna Bidkar

Prashant Khare

Ankit Upadhyaya

Suman Boroi Tamuly

Harmeet Singh

Bharat Indrakanti

Subrojyoti Dey

Kanika Manocha

Nimish Ravindra Deshpande

Ranjan Verma

Anjani Mishra

Madhusudhanan Krishnamoorthy

Thenamudhan Arumugasamy

Ashu Chugh

Vibhuti Gupta

Sachin Ahuja

Mani Arora

Amit Chopra

Harender Dass

Yash Misra

Rachna Gambhir

Sarvesh Neelakanta Subramani

Krishnan T R

Shane Prakash Masih

Hitesh Chopra

Systems, computer program products, and methods are described herein for secure document retrieval and sharing using multistage encryption and authorization. The method includes receiving a user location verification request for an account associated with a user. The user location verification request is for one or more documents relating a user residence. The method includes receiving at least one encryption key for document(s) associated with the user. The document(s) associated with the user relate to the user residence of the user. The method also includes causing a transmission of at least one encryption key used to access document(s) associated with the account. The method further includes determining the user residence of the user based on the document(s) obtained via the at least one encryption key. The method still further includes determining an account access level for the account associated with the user based on the user residence.

System and method for secure document retrieval and sharing using multistage encryption and authorization

A system and method for data processing and storage using quantum and deoxyribonucleic acid (DNA) computing. The method includes receiving a request for a search data item. The request includes a first information represented by classical binary bits. The request is converted into a converted request. The converted request includes the first information represented by quantum bits. One or more servers are searched based on the converted request using a quantum search algorithm. Search results are generated. The search results are ranked according to ranking rules. A highest-ranked result includes a second information represented by quantum bits. The highest-ranked result is converted to a converted highest-ranked result. The converted highest-ranked result includes the second information represented by DNA bits. The converted highest-ranked result is encrypted to generate an encrypted and converted highest-ranked result. The encrypted and converted highest-ranked result is stored in one or more DNA strands.

Data processing and storage using quantum and DNA computing

A system and method for voice processing using photonic quantum computing. A method includes receiving voice data represented by classical binary bits. The voice data is converted to a first photon beam including converted voice data represented by photonic quantum bits. The first photon beam is split into split photon beams. The split photon beams are received by a quantum neural network, which includes quantum neural network clusters. The converted voice data is processed by processing the split photon beams. Each of the split photon beams is processed by a respective neural network cluster in parallel. Processing the converted voice data includes extracting voice features. Word embeddings are created based on the voice features. Sentences are determined based on the word embeddings.

Voice processing using photonic quantum computing

Communication, authentication, and/or validation may be required in various types of device interactions. For example, for some types of device functions, user or device authentication may be required to confirm that the function can and should be performed. Authentication information may be communicated and authentication and/or validation may be performed using LoRaWAN signaling. LoRaWAN signaling provides low power and long-range communication capabilities to efficiently and effectively perform authentication processes. In some arrangements, LoRaWAN signals may be generated by both a first device (e.g., a user device) and a second device (e.g., a function-performing device) and subsequently compared to determine whether they correspond. This correspondence may provide the requisite authentication or validation of the first device and/or an associated user.

Communication, authentication, and validation using LoRaWAN protocol

Aspects of the disclosure relate to NFT exchanges. A computing platform may generate a plurality of F-NFTs including F-NFT identifiers that configure the F-NFTs for end-to-end tracking. The computing platform may extract, from a voice communication, information of a request to transfer an F-NFT. The computing platform may generate, based on the information of the request, a text file. The computing platform may input, into a GPT-4 algorithm, the text file to produce a F-NFT contract identifying the F-NFT, the transferor of the F-NFT, and a transferee of the F-NFT. The computing platform may send, to an NFT exchange platform, the F-NFT contract, which may cause the NFT exchange platform to transfer custody of the F-NFT from an account of the transferor at a first institution to an account of the transferee at a second institution.

Voice based feature extraction and optical receptive net for non-fungible token transfer

Device information may be obtained using LoRaWAN communications. A device information request may be generated and transmitted by a user device and include request parameters such as a device type for which information is desired, a type of information requested, a geographic range for the request, and the like and/or combinations thereof. Device information requests may also be propagated or repeated by intermediary devices to achieve the desired request range. Accordingly, a recipient device of the original request may propagate or repeat, using LoRaWAN, a request signal if it determines that the request range has not been met. If the request range has been met, the recipient device might not repeat the request.

System and method for determining device status using LoRaWAN

Information-security LoRa-wave sensing is used to protect ATMs with LoRa modulator with spread-spectrum modulation techniques and/or transparent laser-guided systems 3D image generation to scan/monitor ATM card slots and ATM keypads for skimmers, fake keypads, etc. Sensor(s) with a DCNN/StNet-based algorithm are trained on 3D dimensions for card slot and keypad. Normal vs. detected constant weight of the keypad as well as weight distribution when keys are depressed are detected. Normal vs. disrupted signals based on the foregoing are observed and used to detect unauthorized objects. NB-IoT LoRa-waves initiate an alarm process. Additional features, functionality, and details are disclosed.

Detection of unauthorized objects on ATM

Transactions may be performed using a mobile device such as a user-wearable device using LoRaWAN protocol to minimize power consumption while maximizing communication range. Transaction information may be stored in the user-wearable device and transmitted to a transaction processing device using LoRaWAN communications. Transaction information may include user-specific information, payment information, merchant information, product information, user preference information and the like. In some instances, the only communication interface (or wireless communication interface) provided in the mobile device is a LoRaWAN communication interface.

Mobile device transaction processing system and method using LoRaWAN communications

The systems and methods described include the ability to store such information in an immutable and distributed, verifiable fashion. Furthermore, the system includes enhanced means for retrieving, interacting with, and visualizing such information via user interface on a variety of user device types. The system is further configured to intelligently determine data forwarding decisions based on one or more configurable data guidelines as determined by one or more entities or third party systems, and provide access to verified data to these entities and systems.

System for data integrity monitoring and securitization

Aspects of the disclosure relate to processing asset transfers. A computing platform may receive an asset transfer request, and may modify a distributed ledger to include a new block corresponding to the asset transfer request. The computing platform may identify, for each of a plurality of consensus methods, a subset of existing blocks that, when used to perform the corresponding consensus method, uses a minimum number of the existing blocks to perform the corresponding consensus method. The computing platform may store, in the distributed ledger, block combinations having the minimum number for each of the plurality of consensus methods, and may execute, using each corresponding identified subset of the existing blocks, each of the plurality of consensus methods. Based on establishing the consensus, the computing platform may direct an event processing platform to process the asset transfer request, which may cause the event processing platform to process the request.

Intelligent distributed ledger consent optimizing apparatus for asset transfer

Transactions between entities may be validated using LoRaWAN communications to more quickly process those transactions. In the example of check depositing, a first entity associated with a check payee may transmit a check clearance request to a second entity associated with a check payor using LoRaWAN communications. The LoRaWAN signaling and communications may be performed between devices within LoRaWAN range. For example, a check depositing device may receive a check deposit where the payor is associated with a different financial institution or entity. Accordingly, the check depositing device may communicate with another device associated with the payor institution or entity using LoRaWAN signals to confirm check clearance.

Validating transactions between entities using LoRaWAN protocol

Aspects of the disclosure relate to processing asset transfers. A computing platform may receive an asset transfer request and extract information from it. The computing platform may modify a distributed ledger to include a new block corresponding to the asset transfer request. The computing platform may identify a consensus method by identifying, for each of a plurality of consensus methods, a subset of blocks from the distributed ledger that, when used to execute the corresponding consensus method, result in a lowest energy consumption value in comparison to remaining subsets of blocks. The computing platform may execute each consensus method using the corresponding identified subset of blocks, which may result in establishing consensus to process the asset transfer request. Based on establishing the consensus, the computing platform may direct an event processing platform to process the asset transfer request, which may cause the event processing platform to process the request accordingly.

Systems, methods and apparatus are provided for an end to end control automation workflow using a distributed network. The data segregation layer may assimilate data from a variety of enterprise sources. A trust engine may validate the data from enterprise sources against enterprise security standards. The system may use a distributed network to validate the data from the various sources and populate a distributed hash table. The distributed network may be a Holochain&#xae; framework. The system may include an automation layer that uses robotic processing automation scripts to validate data against a system of record and flag exceptions. The automation layer may provide data to a user interface layer. The user interface may include an interactive dashboard for presenting a range of detailed reports.

Trusted control automation platform

Apparatus, methods and media for providing a supply chain link performance change indicator. The apparatus may include, and the methods and media may involve a processor module, a receiver module and an output device. The processor module may provide to a user a vector selection control. The receiver module may receive financial data corresponding to the supply chain link. The financial data may include a plurality of vectors. The receiver may receive via the vector selection control a first vector identifier corresponding to a first vector in the plurality of vectors and a second vector identifier corresponding to a second vector in the plurality of vectors. The output device may provide to the user a first supply chain link performance change indicator corresponding to the first vector and a second supply chain link performance change indicator corresponding to the second vector.

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Delhi, India

Prashant Anna Bidkar