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1.发明申请公开(公告)号：US20250080359A1
公开(公告)日：2025-03-06
申请号：US18241306
申请日：2023-09-01
Applicant: BANK OF AMERICA CORPORATION
Inventor： Saurabh Garg , Maneesh Sethia
Abstract: Systems, computer program products, and methods are described herein for cryptographic data transfer and authentication in a distributed network. The present invention is configured to receive credentials on an interface of an endpoint device, receive a request from the endpoint device to access a portal, authenticate the credentials via an authentication engine, receive specifications, wherein the specifications are input into the interface of the endpoint device, select, via a configuration engine comprising pre-existing configurations in a configuration database of a first storage device, a selected pre-existing configuration, determine a verification of the selected pre-existing configuration, and access the portal.
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2.发明申请公开(公告)号：US20250055877A1
公开(公告)日：2025-02-13
申请号：US18230897
申请日：2023-08-07
Applicant: Bank of America Corporation
Inventor： Maneesh Sethia , Manimaran Sundaravel
IPC: H04L9/40
Abstract: A computing platform may train, using historical threat detection information, a threat detection model, which may configure the threat detection model to detect container threats for a plurality of containers deployed at a plurality of nodes on a cloud network. The computing platform may obtain, from a node monitoring system, operating conditions of the plurality of nodes. The computing platform may input, into the threat detection model, the operating conditions of the plurality of nodes, which may cause the threat detection model to identify a threat to at least one container deployed at the plurality of nodes. The computing platform may execute, based on identification of the threat, a security action to protect the at least one container. The computing platform may update, based on the operating conditions of the plurality of nodes and the threat, the threat detection model.
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公开(公告)号：US20240419789A1
公开(公告)日：2024-12-19
申请号：US18210312
申请日：2023-06-15
Applicant: BANK OF AMERICA CORPORATION
Inventor： Saurabh Garg , Abhijit Behera , Paul Martin Mattison , Maneesh Sethia
IPC: G06F21/55
Abstract: Artificial intelligence, in the form of machine-learning models, are implemented to dynamically detect when an online or mobile app application is being filled-out/submitted by an autonomous software program/bot (e.g., an invalid application submission), as opposed to a human (i.e., a valid application submission). Telemetry data is captured from the mobile application or web/online application that is indicative as to whether the application forms are being filled-out by a human or an autonomous software program. The telemetry data is applied to machine learning models to determine if the telemetry data results in a recognized pattern that indicates autonomous software program data entry or, conversely, human data entry. In the event that an application submission is determined to be filled-out by an autonomous software program/bot, subsequent submission and/or further processing of the application is denied.
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公开(公告)号：US12147967B2
公开(公告)日：2024-11-19
申请号：US17875166
申请日：2022-07-27
Applicant: Bank of America Corporation
Inventor： Maneesh Sethia
Abstract: A wearable computing device, such as a smart glass device, may be used to facilitate touchless and/or frictionless transactions at computing devices in the vicinity of the wearable computing device based on a dynamic non-fungible token (NFT). The smart glass device captures biometric information of a user, such as an iris image, and generates the NFT based on the biometric information, a geographic location and a time. The NFT is authenticated via a blockchain by an authentication system at a remote network. Upon validation, the smart glass device presents user interface screens to initiate the transaction. A computing device receives a request message to complete the transaction based on the NFT.
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公开(公告)号：US12051307B1
公开(公告)日：2024-07-30
申请号：US18203682
申请日：2023-05-31
Applicant: Bank of America Corporation
Inventor： Saurabh Garg , Maneesh Sethia , Shailendra Singh
CPC classification number: G07F19/206 , H04L9/3239
Abstract: Aspects of the disclosure relate to reimaging an ATM using an extended reality interface and machine learning models that are configured to reimage the ATM. A computing system may send a request for authorization to access an ATM. Based on the request being granted the ATM may be accessed via an extended reality interface. Reimaging the ATM may be based on inputting ATM data associated with a state of the ATM into machine learning models that are configured to generate instructions to reimage the ATM and then execute threads based on processes that were determined based on the instructions. The threads may be executed in a RAM of the ATM in accordance with machine learning model determined priorities of the threads.
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Patent Agency Ranking
6.发明申请公开(公告)号：US20250112758A1
公开(公告)日：2025-04-03
申请号：US18376138
申请日：2023-10-03
Applicant: Bank of America Corporation
Inventor： Saurabh Garg , Bhagat Allugubelly , Maneesh Sethia
Abstract: A computing platform may train, using smart contract and file type information, a homomorphic encryption model, which may configure the homomorphic encryption model to identify, for a given input file, a corresponding smart contract defining a corresponding set of parameters, included in the given input file, for display. The computing platform may receive an unencrypted file, and may identify, by inputting the unencrypted file into the homomorphic encryption model, a smart contract defining one or more parameters for display. The computing platform may encrypt, using homomorphic encryption, the unencrypted file to produce an encrypted file, and may store the encrypted file. The computing platform may receive, via an application programming interface (API) at a user device, a request to access the encrypted file. The computing platform may send, based on the smart contract and for display at the user device via the API, the parameters for display.
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公开(公告)号：US20250077635A1
公开(公告)日：2025-03-06
申请号：US18240491
申请日：2023-08-31
Applicant: Bank of America Corporation
Inventor： Shahadat Hossain Mazumder , Abhijit Behera , Maneesh Sethia
Abstract: A computing platform may generate, using a generative AI model, voice based authentication prompts corresponding to a user. Upon receiving a registration request from the user, the computing platform may identify the voice based authentication prompts for the user. The computing platform may send, to a first computing device of the user, the voice based authentication prompts and may receive/store voice based authentication information corresponding to the voice based audio inputs. Based on receiving an access request, the computing platform may send the plurality of voice based authentication prompts, and may receive, from a second computing device, additional voice based audio inputs. The computing platform may score, based on the voice based authentication information, the additional voice based audio inputs. The computing platform may compare the score to a threshold. Based on identifying that the score fails to meet the threshold, the computing platform may initiate security actions.
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公开(公告)号：US12058005B1
公开(公告)日：2024-08-06
申请号：US18243901
申请日：2023-09-08
Applicant: Bank of America Corporation
Inventor： Shailendra Singh , Maneesh Sethia , Saurabh Garg
Abstract: Aspects of the disclosure relate to using machine learning models to automatically generate spine-leaf network topologies. A computing system may receive one or more prompts to generate a spine-leaf network topology based on a non-spine-leaf network topology of a non-spine-leaf network. Based on inputting the prompts into a natural language processing model, network criteria for generating the spine-leaf network topology may be generated. Non-spine-leaf network topology data comprising network metadata, network dependency parameters, and network constraint parameters, may be retrieved. Based on inputting the network criteria and the non-spine-leaf network data into a generative adversarial network implemented on a quantum computing device, candidate spine-leaf topologies comprising a qualified candidate spine-leaf network topology that meets the network criteria may be generated. A block of a blockchain may be generated and may comprise the qualified candidate spine-leaf network topology that meets the network criteria.
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9.发明公开公开(公告)号：US20240062184A1
公开(公告)日：2024-02-22
申请号：US17892456
申请日：2022-08-22
Applicant: BANK OF AMERICA CORPORATION
Inventor： Maneesh Sethia
CPC classification number: G06Q20/3278 , G06Q20/065 , G06Q20/4014
Abstract: A system is provided for executing wireless resource transfers on a portable computing device using a secure digital token. In particular, in response to receiving a resource transfer request from a user, the system may dynamically generate a customized digital token in real-time based on information such as authentication credentials of the user, geolocation data, timestamps, and the like. The digital token may be validated and stored on a distributed register that may be accessible by an entity associated with the user. Upon validating the digital token, the entity's server may transmit the data needed to execute the resource transfer. In this way, the system may provide a secure and efficient way to execute resource transfers.
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10.发明申请公开(公告)号：US20240413997A1
公开(公告)日：2024-12-12
申请号：US18207332
申请日：2023-06-08
Applicant: BANK OF AMERICA CORPORATION
Inventor： Shailendra Singh , Maneesh Sethia , Girish Kumar Kakanur , Abhijit Behera
Abstract: Systems, computer program products, and methods are described herein for secure apparatuses to share and deploy machine build programs utilizing unique hash tokens. The invention includes the steps of transforming a resource machine build-program into a first non-fungible token (NFT1) via a resource machine build orchestration module, embedding NFT1 into a flash drive using a flash drive preparation module, generating a second non-fungible token (NFT2) during an interaction of a resource machine with the USB flash drive via a dynamic NFT generator module, wherein NFT2 includes data representing an ownership certificate for the resource machine build owned by a vendor, generating a resultant integrated non-fungible token (NFT3) via a dynamic smart contract module, wherein NFT3 is generated by combining NFT1 and NFT2, and activating and deploying the resource machine build-program on the resource machine via a build activation module, wherein the activation is triggered by the generation of NFT3.
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