Bank of America Corporation

Abb Technology Ltd

Pictory, Corp

Shailendra Singh

Sandeep Kumar Chauhan

Maneesh Kumar Sethia

Saurabh Gupta

Vasuki Anand

Abhijit Behera

Saurabh Garg

Satyajeet Priyadarshi

Rama Rao Gaddam

Ashutosh Tripathi

Amit Mishra

Durga Prasad Kutthumolu

Saurabh Arora

Krithika Viswanathan

Nandini Rathaur

Sneha Padiyar

Amardeep Singh Talwar

Gowri Sundar Suriyanarayanan

Amit Kumar Bidhanya

Swadeep Mekala

Kamlesh Kanayalal Gangaramani

Sandeep Verma

Prashant Khare

Puneetha Polasa

Govinda Rajulu Nelluri

Subburathinam Krishnan

Nimish Ravindra Deshpande

Sheetal Bhatia

Savitri Jaganath Podal

Saurabh Uprit

Swathi Bussa

Vinod Maghnani

Amrut Gopal Nayak

Saravanan Balasubramanian

Bhagat Kumar Allugubelly

Suryanarayana Adivi

Divya Sharma

Ramarao Gaddam

Santosh Kumar Miryala

Pushkar Taneja

Zhanwei Tu

Manimaran Sundaravel

Ajay Kumar Gowni

Moses Salagala

Thomas Boffin James

Savitri Sibaram Desulu

Shreya Manocha

Anu Joy

Amaresh Gunasekar

Arul Victor Benjamin

Suresh K S

Divya Nagarajan

Jai Issrani

Suresh Loganathan

Arup Francis

Govinda Ramam Gonna Satya Sai

Ankit Dholakiya

Salma Umme

Subbiahthever Dukkaiappan

Pavan Kumar Gauji

Tushar Agarwal

Pushpa Neelakantan

Vikram Chalana

Vishal Chalana

Vaddi Sreenivasulu Reddy

Ashish Kumar Dwivedi

Abid Ali Mohammed

Sarabjeet Kaur

Gaurav Sachdeva

Sukanya V

Kavitha Hariharan

Raj Kiran Akkera

Sharvani Ganachary

Charles Joseph Fernandez

Shyam Prasad Rokula

Systems, methods, and apparatus are provided for AI-based generation of a secure network path and corresponding encryption protocols. AI algorithms may detect network nodes for data transfer from an origin point to a destination point. The nodes may be located in different countries. Nodes may be selected based on security levels and regulatory profiles generated for each node. AI algorithms may analyze the transfer data and output encryption algorithms for generating synthetic data from the transfer data. The encryption algorithms may be mapped to the nodes based on security levels and regulatory profiles associated with the nodes. A node may receive the transfer data and apply the mapped encryption algorithm. Successive nodes may iteratively encrypt the transfer data. A data packet header may include an identifier for each encryption algorithm applied to the transfer data.

Artificial intelligence (AI) based secure network protocols with dynamic multilayer encryption

Systems and processes are disclosed to monitor and control toxic configuration in software container deployment. AI-based monitor in each node provides end-to-end fault management system that can detect, diagnose, classify, and suggest remediation actions for non-virtualized cloud-based misconfiguration vulnerabilities. Anomalies are diagnosed using pre-computed fault signatures and automated remediation is integrated with a cloud management stack. Multiple monitoring layers within nodes secure the container-based virtualization environment. Container-based 'CSTC security framework' virtualization technology provides security and identifies potential toxic configuration threats. CSTC security locates container-based systems at severe risk for DDOS attacks to kernel vulnerability/container breakout and ensures appropriate privilege configuration for user processes. Resource access limited based on policies and CSTC security profiles as well as provide AI-based monitoring of container runtime behavior to provide additional security layer that ensures safety and protection in container-based virtualization.

Monitor and control toxic configuration in container deployment

A system for dynamically caching information includes a memory for storing location information and user information and a processor configured to periodically receive geolocation data associated with a first external device and store that geolocation data, along with a time stamp, as location information in the memory. After a predetermined period of time, the processor retrieves from the memory the location information corresponding to the predetermined time period. Machine learning is used to determine the probability of a first action. When the probability is higher than the first predetermined amount, the processor is configured to retrieve information needed to perform a first action and send the retrieved information to a second external device to store the information as cached information. This cached information is then used to perform a first action using the cached information on the second external device.

Dynamic caching based on a user's temporal and geographical location

The present disclosure provides a method. The method includes receiving a request from a user to generate content using generative artificial intelligence based on an original prompt having a first specific parameter and a second specific parameter. The method includes determining an authority level of the user and determining an authority level of the first specific parameter and the second specific parameter. The method includes determining whether the user is authorized to access the first specific parameter and the second specific parameter based on the authority level of the user. The method includes modifying the first specific parameter into a first generalized parameter and modifying the second specific parameter into a second generalized parameter. The method includes creating a modified prompt to generate the content using the generative artificial intelligence, wherein the modified prompt obfuscates the content of the original prompt using the first and second generalized parameter.

System and method for controlling generative artificial intelligence output based on user entitlements

A method includes rendering, on displays of an extended reality (XR) device, an XR environment, and detecting, based on sensor data obtained from sensors of the XR device, a device capability associated with the XR device and one or more environmental conditions associated with the XR environment. The method further includes receiving a request corresponding to one or more user interactions with an XR application. In response to receiving the request, the method includes generating, based the device capability and the environmental conditions, a dynamic digital profile to be associated with the user, in which the dynamic digital profile is dynamically generated to be responsive to one or more input modalities associated with the request, and render, on the displays, the dynamic digital profile. The rendered dynamic digital profile includes a set of elements responsive to the one or more input modalities of the request.

System and method for generating and securing a user-specific application in an extended reality environment

Embodiments of the present invention provide a system for secure validation, registration, and distribution of resources in a distributed electronic network. In particular, the system may be configured to determine that a user is at a third party entity location for acquiring computing device provided by a third party entity associated with the third party entity location, establish a connection between a user device of the user and the computing device, cause the user device to extract computing device information associated with the computing device, via the connection, receive an input associated with acquiring the computing device, transfer funds associated with acquiring the computing device from a resource pool of the user to an entity resource pool associated with the third party entity, via the user device, and establish a smart contract between the user and the third party entity associated with the computing device.

System and method for secure validation, registration, and distribution of resources in a distributed electronic network

A method is provided herein for evaluating a physical building, utilizing an automated image capture apparatus, a spatial computing apparatus, a machine learning model, a blockchain network, and a computer processor, the method including capturing and analyzing images of the building, dividing the building into sections, identifying defective characteristic(s) in and assigning a status to each section, sharing the images and status identifiers with a remote user, the remote user reviewing the images and identifiers, and receiving feedback from the remote user. When a section lacks sufficient images to determine whether a defect is present, the section may be flagged, and a supplemental image(s) may be captured and provided by the remote user. When no additional images are needed, the section may be indicated as completed. Otherwise, the section may retain its flagged status, and the aforementioned steps may be repeated as necessary.

Methods and systems for evaluating buildings

Apparatus and methods for securing a communication link. The apparatus may include a microprocessor. The apparatus may include a memory cell. The apparatus may include a photovoltaic circuit. The apparatus may include a radio frequency transceiver circuit. The apparatus may include an organic light emitting diode display circuit. The microprocessor may be embedded in an information card. The memory cell may be embedded in the information card. The photovoltaic circuit may be embedded in the information card. The radio frequency transceiver may be embedded in the information card. The organic light emitting diode display may be embedded in the information card. The display circuit may include an array of separately excitable diode fields. The display circuit may include a display controller that is in electronic communication with each of the fields.

Mobile phone pairing for dynamic spatial activation of communication device

A registered lower orbit satellite-powered generative artificial intelligence ('AI')-based lost active smart card (“ASC”) tracking and reporting mechanism. The methods and systems may include detecting a threshold distance between a lost ASC and a user device. The lost ASC may initiate a reporting, may include a microwave communication transceiver, and may be associated with an originating entity. The methods and systems may include determining a threshold time that the lost ASC was located at least the threshold distance from the user device. The methods and systems may include tracking the geolocation of the lost ASC by submitting instructions to the lost ASC, instructing the lost ASC to emit a beeping noise, and reporting lost ASC geocoordinates to the originating entity. The lost ASC may emit the beeping noise in response to receipt of the instructions from a satellite network.

Registered lower orbit satellite-powered generative artificial intelligence ('AI')-based lost card tracking and reporting mechanism

A system includes a memory and a processor that validates an interaction between an initiating and a receiving device. An encrypted request is received to perform the interaction and the processor extracts an initiating device identification, a receiving device identification, and one or more numerical values associated with the interaction. Using this extracted information, the processor produces a verification key by applying a hash function and a verification checksum value using a checksum function. The verification key and verification checksum value are then compared with an authentication key and authentication checksum value that were produced in a same manner prior to the interaction being initiated. If it is determined that either the verification key and the authentication key do not have the same value, or verification checksum value and authentication checksum value do not have the same value, then the interaction is reversed.

System and method for validating an interaction using an agreement key

A method for modifying smart card properties of a smart card leveraging a spatial computing device is provided. The spatial computing device may be in electronic communication with an entity server. The method may include identifying the smart card within a field of view of the spatial computing device. The method may include establishing a wireless communication between the smart card and the spatial computing device. The method may further include generating a digital copy of the smart card and displaying the digital copy of the smart card on a display of the spatial computing device. The method may further include displaying a plurality of selectable options for modifying card properties of the smart card and in response to a detection of a selection of one of the selectable options, transmitting a request to the entity server to modify a property of the smart card based on the selected option.

Leveraging spatial computing to modify smart card properties

A method for providing a QR code. The method includes generating a map of an environment surrounding a spatial computing device. The map may be converted into a video. The video may be stored in a database. The video may be divided into multiple frames. A pattern may be arranged for placement of the frames. The frames may be placed inside the QR code in accordance with the pattern. The QR code may be scanned. The pattern may be decoded. The video frames may be retrieved, and the video may be restored. A request associated with the QR code may be executed.

Spatial computing device powered lidar technology enabled dynamic quick response ('QR') code generation mechanism

An apparatus may comprise a memory communicatively coupled to a processor. The memory may be configured to store user profiles and security information. The processor may be configured to receive a device profile from a user device. Further, the processor may be configured to validate the device profile against a user profile; determine an entitlement associated with the user profile; generate an initial token indicating that the device profile is entitled to access the entitlement; transmit the initial token to a decentralized network; and receive an updated token from the decentralized network. The updated token may indicate a firewall configuration based at least in part upon the initial token. The firewall configuration may be configured to enable the user device to access the entitlement. The processor may be configured to transmit the firewall configuration to the user device to implement a firewall at the user device.

System and method for updating a firewall security configuration in a decentralized network

A request is transmitted to a second computing node of a second blockchain network to perform a data interaction between a first computing node of a first blockchain network and the second computing node. Upon receiving an acknowledgement of the request, a first smart contract, an encrypted first network address and a first authentication code is generated. The first smart contract is encrypted using the first authentication code to generate an encrypted first smart contract. The encrypted first smart contract, the encrypted first network address and the first authentication code is transmitted to the second computing node. A digital signature is received indicating an approval of the first smart contract. Thereafter, data objects are transmitted to the second computing node as agreed in the first smart contract.

System and method for exchanging data between blockchain networks

A card device receives a first sensor data from sensors associated with the card device and extracts a set of user features from the first sensor data, where the user features indicate physical attributes of the user. The card device receives a second sensor data from the sensors. The card device extracts a set of viewer features from the second sensor data, where the viewer features indicate physical attributes of the viewer. The card device compares at least one of the user features with a counterpart feature from among the viewer features. The card device determines that the user is not the viewer. The card device determines a distance between the viewer and the card device. The card device determines that the distance between the viewer and the card device is less than a threshold distance. In response, the card device dynamically masks the information displayed on the card device.

Altering card device attributes in response to detecting a proximity intrusion

Growing community of inventors

Maharashtra, India

Shailendra Singh