Bank of America Corporation

Durga Prasad Kutthumolu

Sakshi Bakshi

Venkata Karthik Ryali

Anurajam Rajagopalan

Subburathinam Krishnan

Laxma Gavinolla

Pushkar Taneja

Shailendra Singh

Suryanarayana Adivi

Ramprasath S

Sachin S Nagvekar

Saurabh Arora

Krishna Rangarao Mamadapur

Kiran Pulla

Shilpi Choudhari

Prabhakaran Balasubramanian

Sreekanth Raghuveer Maringanti

Anantharajan Srinivasarangan

Ramaswamy M

Kapil Juneja

Saravanan Balasubramanian

Sai Srinivas Vartha

Saravana Kumar Pd

Rajesh Kanduri

Arif Ahmad Khan

Arvind Bansal

Ramakanth Bachu

Priyanka K

Veerendra Gupta

Subhasree Baskaran

Govinda Ramam Gonna Satya Sai

Uttam Dey

Murali Krishna Akula

Sunilkumar Sriperambudur

Jenita Mercy

Sharat Chandran

Thamizh Thendral

Pracheta Ranjan Mohanty

Roy Jyoti Ranjan

Navin Singh

Yegappan Alagappan

Hwee Leng Toh

Saurabh Rajpal

Ankit Kumar

Susheel Chiluka

Mukesh Singh

Venugopal Kailasa

Geetika Sen

Aspects of the disclosure describe methods and systems involving separate, parent (e.g., public) and child (e.g., private) metaverses with varying confidentiality and access privileges for auditor users, financial analyst users, regulatory users, and other virtual reality/metaverse users to interact in a fully immersive, real-time manner (e.g., using an immersive query modulation engine) to fulfill audit and regulatory reporting requirements, including extracting information from heterogeneous data stores, recordkeeping of audit responses for regulatory purposes, and maintaining access privileges of varying user profiles.

Intelligent platform for audit response using a meta verse-driven approach for regulator reporting requirements

Systems, computer program products, and methods are described herein for data traffic control. The present invention may be configured to receive data from a user, encrypt the data, route the encrypted data, via a gateway to a node cluster. The present invention provides for a node cluster comprising an intent crawler and at least one individual node. The intent crawler routes the data, in the form of a query, to an individual node. Once a response is received, both the query and the response are recorded on a distributed ledger and transmitted to the user. The systems, computer program products, and methods may incorporate natural language processing to process voice data.

System and method for data traffic control on a distributed network

A system comprises a memory communicatively coupled to at least one processor. The at least one processor is configured to receive a code-based data exchange request from a user. The code-based data exchange request comprises first user information associated with a user profile. Further, the at least one processor is configured to trigger a request for a retinal scan of the user in response to receiving the code-based data exchange request and receive a result of the retinal scan of the user. The result comprises second user information. The at least one processor is configured to determine that the code-based data exchange request is authentic in response to determining that the first user information and the second user information are associated with the user profile, convert the code-based data exchange request to a light-based data exchange request, and generate a light-guided contract based on the light-based data exchange request.

System and method to perform light-based data exchange operations

Systems, computer program products, and methods are described herein for AI-based adaptive security parameter calculation in license key generation with quantum-resistant protections. The present disclosure is configured to utilize advanced cryptographic techniques, including elliptic curve cryptography and SHA-3 hashing, to produce secure digital signatures for license keys. An AI-driven engine analyzes historical security data to adaptively adjust key generation parameters, ensuring enhanced protection against current and emerging threats. This adaptive approach allows for continuous learning and improvement of security measures, making the system robust against both classical and quantum cryptographic attacks. The disclosed methods integrate the generation, assessment, and validation of keys into a streamlined process that promotes high security while maintaining efficiency.

System and method for AI-based adaptive security parameter calculation in license key generation with quantum-resistant protections

Systems and methods are disclosed to provide a security framework for the authentication of digital content and the prevention of unauthorized modifications, especially targeting the vulnerabilities introduced by deepfake technologies. It innovates by merging reverse engineering with expression manipulation detection to discern genuine from altered digital media. The process involves comparing historical data against synthetic or real-time content, generating a 'video mesh' that enables precise manipulation identification. Enhanced by Smart Contracts for each content piece to record and verify changes, this system advances digital identity and transaction security significantly beyond current methodologies. Furthermore, it employs Generative AI within the Identity Intelligent Clip Reviewer to scrutinize blockchain-secured data for manipulation signs, issuing a Proof of Digital Manipulation (PODM) for verified authenticity. This comprehensive method ensures the integrity and trustworthiness of digital interactions across various platforms, marking a significant step forward in the protection against sophisticated cyber threats and unauthorized data alterations.

Spurious less data authentication by method mesh engineering using digital GenAI with proof of digital manipulation (PODM)

Arrangements for providing near-field communication (NFC) security using smart cyber contract generation (SCC) are provided. A platform may train an anomaly detection engine based on historical user information and an SCC generation engine based further on historical event processing rules. The platform may generate a certificate for a user device based on intercepting a request via NFC. The platform may validate the certificate based on a maintained profile. The platform may generate a suspicion indication for the request using the anomaly detection engine. The platform may generate an SCC, using the SCC generation engine, based on identifying the request is suspicious. The platform may apply rules included in the SCC to information included in the request. Based on determining that less than all of the rules in the SCC are satisfied, the platform may initiate a security action. The platform may update the engines based on updated event processing permissions.

Providing near-field communication security using smart cyber contract generation for a zero-trust network architecture

A method includes generating a metaverse session, a first avatar of a first user, and a virtual advisor avatar. The first user is allowed access to the metaverse session using the first avatar. A voice query of the first user is received and analyzed to determine a preferred language/dialect of the first user, and an issue and a domain of the voice query. In response to determining that a language/knowledge server includes a response corresponding to the issue and the domain, the response is retrieved from the language/knowledge server. In response to determining that a language/dialect of the response matches the preferred language/dialect of the first user, a first voice response is generated from the retrieved response. The first voice response is in the preferred language/dialect of the first user. The first voice response is communicated to the first user using the virtual advisor avatar.

System and method for cross-domain and cross-linguistic knowledge-reinforced user servicing

Aspects of the disclosure relate to a distributed evaluation platform. The distributed evaluation platform may train a machine learning model based on historical nonfungible tokens. The distributed evaluation platform may receive client information from a client device. The distributed evaluation platform may generate NFTs corresponding to the client information. The distributed evaluation platform may generate soft tokens corresponding to each NFT. The distributed evaluation platform may apply test cases to the soft tokens. The distributed evaluation platform may generate remedial tokens based on the soft tokens and remediation actions. The distributed evaluation platform may apply the test cases to the remedial tokens. The distributed evaluation platform may overwrite the NFTs using the remedial tokens. The distributed evaluation platform may send an event processing request to an event processing system. The distributed evaluation platform may refine the machine learning model based on the NFTs.

Distributed evaluation platform for nonfungible tokens using virtual token cloning

Arrangements for an intelligent monitoring platform using a cybersecurity mesh and graph neural networks (GNNs) are provided. A platform may train multiple machine learning models (e.g., a GNN model, a cybersecurity engine, and a monitoring model). The platform may generate, using a GNN model, a suspicion score for a received event processing request. Based on determining the suspicion score satisfies a threshold, the platform may generate a threat score using a cybersecurity engine. The platform may generate an anomaly record for the event processing request based on the threat score and using a monitoring model. The platform may determine a preferred node of a cybersecurity mesh for routing the event processing request based on the anomaly record. The platform may determine a threat prevention response based on the preferred node. The platform may initiate one or more security actions based on the threat prevention response.

Intelligent monitoring platform using graph neural networks with a cybersecurity mesh and associated cybersecurity applications

Innovative distributed tracing system(s) and process(es) integrate automated code instrumentation, AI-driven quantum computing, particularly Photonic Quantum Computing, and real-time analysis algorithms. This system autonomously identifies and monitors network components such as gateways, service meshes, message queues, databases, and proxy servers, seamlessly capturing trace data across various communication protocols. It features dynamic scaling capabilities to handle fluctuating network loads and employs automatic tagging for precise identification of each network element and transaction. Utilizing advanced machine learning algorithms, the system efficiently analyzes trace data, identifying patterns, dependencies, and anomalies. It is equipped to intervene in operations by halting transactions under specific conditions. The incorporation of Photonic Quantum Computing allows for unparalleled anomaly detection and data analysis speed and accuracy. This system enhances trace data analysis, improves anomaly detection, and optimizes overall system performance, offering a robust, secure, and efficient approach for managing complex distributed systems.

Distributed data tracing

Aspects of the disclosure relate to using machine learning models to performing real-time cache updates. A computing system may receive a request to update an unreferenced object of a user interface of an application. A block may be generated in a blockchain stored in a second cache tier. The block may comprise a non-fungible token (NFT) based on the unreferenced object and may indicate that the unreferenced object is not authorized to indicate a system of record update. Based on the request to update the unreferenced object meeting one or more criteria, a block comprising an NFT that is referenced by the unreferenced object may be generated in a first cache tier. A block indicating that the NFT is referenced by the unreferenced object may be generated in a first cache tier and the unreferenced object may be updated in the user interface of the application.

Intelligent method for real time cache updates leveraging distributed ledger technology with non-fungible token (NFT) tied system of record (SOR) update indicators

Methods and systems for synergistic use of a large language model ('LLM') and Graph-of-Thoughts (“GoT”) for unified data access across GraphQL application protocol interfaces (“APIs”) via a single API. Methods and systems may include requesting to identify and retrieve data concerning GraphQL APIs from a GraphQL API schema hub. Methods and systems may include identifying key relationships between data elements in the GraphQL APIs using relationship semantic analysis and transporting a text prompt via a cache to an LLM-GOT synergistic processor. Methods and systems may include modeling information generated by the LLM-GoT synergistic processor as an arbitrary graph, generating a unified GraphQL API based on synergistic outcomes, and storing the unified GraphQL API in the GraphQL API schema hub.

LLM-Graph-of-Thoughts leveraging unified data access across diverse GraphQL APIs

A system receives job requests comprising associated job names and associated job parameters. The system performs a comparison of a job name and parameters for a first, second, and third job request with information of previously performed jobs and determines a first, second, and third amount of memory to perform the job requests. The system evaluates the first, second, and third amounts of memory with predetermined memory sizes to determine if the memory amounts exceed the predetermined memory sizes. The system negotiates with schedulers from one or more service provider networks to allocate memory from temporary memories for each amount of memory that exceeds the predetermined memory sizes. The system creates a prioritized queue comprising the first, second, and third received job requests for scheduler processing based upon the amounts of memory. The system can use a trained algorithmic model to predict the first, second, and third amounts of memories.

System for predicting memory resources and scheduling jobs in service-oriented architectures

Aspects of the disclosure relate to a dual-system reconciliation process of trades. A first real-time trade processing and centralized reconciliation engine may continuously process trades in real-time and may perform centralized reconciliation of the trades. An anomaly detection and reconciliation mesh analysis engine may tokenize trade metadata received from the first real-time trade processing and centralized reconciliation engine, generate tokenized trade digital DNA, generate hashed tokenized trade digital DNA, evaluate and validate the hashed data, and perform decentralized reconciliation mesh analysis of the hashed data using a reconciliation mesh. The anomaly detection and reconciliation mesh analysis engine may send one or more monitory policies from the reconciliation mesh to a user device and may receive a first monitory policy selection from the user device. The anomaly detection and reconciliation mesh analysis engine may update the decentralized reconciliation mesh based on the first monitory policy selection.

System and method for transaction reconciliation and anomaly detection using tokenized decentralized mesh

Systems, methods, and apparatus are provided for developing and applying a metaverse enabled digital cognitive twin. Customer communications may be secured at a data layer using multi-cloud object storage. A first multi-modal AI system may generate segmented customer activity data from the customer communications and output the segmented customer activity data to a set of decentralized streaming caches. At an extended reality platform, a second multi-modal AI system may generate immersive content from a real time customer input and the segmented customer activity data for viewing in an XR environment. The system may train an XR avatar based at least in part on the customer communications. The XR avatar may interact with customers and agents and may present a video together with customized supplementary information. The immersive video and the XR avatar may be generated by a plug-in application configured to adapt a variety of XR platforms.

Metaverse enabled digital cognitive twin

Growing community of inventors

Hyderabad Telangana, India

Durga Prasad Kutthumolu