Abstract: An apparatus, computer-readable medium, and computer-implemented method for extracting a subset, including receiving a request comprising one or more criteria indicating one or more criteria tables in a plurality of tables of the database, storing an entity graph corresponding to a schema of the database and the one or more criteria, determining one or more top-most criteria entities in the entity graph, and generating the subset from the plurality of tables by traversing the entity graph starting at the one or more top-most criteria entities without traversing any directed edge more than once.

Abstract: A control device configuration system may receive, store, process, and/or display control device configuration information. The control device configuration system may filter the control device configuration information based on user selections of configuration options for configuration parameters. The control device configuration system may identify compatible and incompatible configuration options for various configuration parameters. The control device configuration system may allow selections of the incompatible configuration options. The control device configuration system may adjust how it filters the control device configuration information based on the selections of the incompatible configuration options. The control device configuration system may implement a configuration model that includes configuration parameter groups for efficient evaluation of user selections.

Abstract: An error message is received from a first computing node indicating a malfunction associated with the first computing node. Based on a first error code received in the error message, a first software program is determined that is to be installed at the first computing node to resolve the malfunction. A geographically nearest second computing node to the first computing node is determined that includes the first software program. The second computing node is instructed to transmit the first software program to the first computing node. The second computing node transmits the first software program to the first computing node. The first computing node receives and installs the first software program at the first computing node.

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.

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.

Abstract: A system that includes a memory and a processor that determines whether to authorize an action. The processor receives a plurality of authorization messages that are requests for authorizing actions. The processor then extracts data from the plurality of authorization messages and analyzes the data with a trained neural network to group the plurality of authorization messages. The resulting plurality of message groupings are then analyzed by a long-short-term-memory algorithm (LSTM) to determine a plurality of patterns that indicate that a particular authorization message may be authorized. The processor then receives one or more new authorization messages from an external device and compares these to the plurality of patterns. If the one or more new authorization messages correspond to any of the patterns, then the external device is notified by the processor that it should deny the action associated with the new authorization messages.

Abstract: A method includes receiving a request. The request is encrypted to generate an encrypted request. The encrypted request includes a version information for a first software package deployed in a standalone computing system, and a region information and a hardware information for the standalone computing system. The encrypted request is sent to a respective regional data center of a cloud computing system based on the region information of the first software package. A second software package is identified among software packages stored in the respective regional data center. The second software package corresponds to the hardware information of the first software package. The version information of the first software package is compared to a version information of the second software package. In response to identifying that the second software package is more recent than the first software package, the second software package is deployed to the standalone computing system.

Abstract: Some embodiments provide a novel method for dynamically deploying gateways for a first network connecting machines. The first network includes segments, routers, and a first gateway that connects to an external network. The method identifies a set of two or more segments that consumes more than a threshold amount of bandwidth of the first gateway. The identified set includes at least first and second segments. The method identifies one or more segment groups by aggregating two or more segments in the identified set. A first segment group includes the first and second segments and a third segment that is not in the identified set of two or more segments. The method configures a second gateway to process flows associated with each identified group including the first group. The method configures a set of routers to forward flows from machines of each segment of each identified group to the second gateway.

Abstract: A control device configuration system may receive, store, process, and/or display control device configuration information. The control device configuration system may filter the control device configuration information based on user selections of configuration options for configuration parameters. The control device configuration system may identify compatible and incompatible configuration options for various configuration parameters. The control device configuration system may allow selections of the incompatible configuration options. The control device configuration system may adjust how it filters the control device configuration information based on the selections of the incompatible configuration options. The control device configuration system may implement a configuration model that includes configuration parameter groups for efficient evaluation of user selections.

Abstract: An apparatus comprises a memory communicatively coupled to a processor. The memory is configured to store network interchange parameters and user profiles. The processor is configured to receive a data exchange request triggered by a user device. Further, the processor is configured to request, to a decentralized network, a token indicating that a user profile associated with the user device is entitled to access an entitlement, determine whether a data exchange network is available to exchange data in accordance with the network interchange parameters, identify a second data exchange network that is available in accordance with second network interchange parameters in response to determine that the data exchange network is unavailable, and request a data exchange output from the second data exchange network via the token. The processor is configured to receive the data exchange output from the second data exchange network.

Abstract: Systems, computer program products, and methods are described herein for flexible data routing in a cloud-based network consortium. The present disclosure is configured to initiate an XR display for display on a user device; in response to a first control signal, generate a nonfungible token (NFT) and transmit a data packet over a secured network; initiate, via the XR display, a secure application programming interface based on the NFT, geographic data, and a unique XR identification value; based on one or more data parameters, identify a preferred data path; and in response to a second control signal, perform an encrypted data exchange via the preferred data path.

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.

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.

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.

Abstract: A system for reestablishing network connectivity for particular network equipment in a failed network zone comprises a processor associated with a server. The processor receives a flag that identifies the failed network zone including particular network equipment that have lost network connectivity in a network. The processor generates a first non-fungible token using the configuration information associated with each of the particular network equipment. The processor determines routing information based at least in part upon the configuration information and a network topology. The processor generates a second non-fungible token based at least in part upon the routing information. The processor aggregates the first non-fungible token and the second non-fungible token to generate a primary non-fungible token. The processor reestablishes network connectivity for at least a portion of the particular network equipment based at least in part upon information associated with the primary non-fungible token.

Abstract: A system for reestablishing network connectivity for particular network equipment in a failed network zone comprises a processor associated with a server. The processor receives a flag that identifies the failed network zone including particular network equipment that have lost network connectivity in a network. The processor generates a first non-fungible token using the configuration information associated with each of the particular network equipment. The processor determines routing information based at least in part upon the configuration information and a network topology. The processor generates a second non-fungible token based at least in part upon the routing information. The processor aggregates the first non-fungible token and the second non-fungible token to generate a primary non-fungible token. The processor reestablishes network connectivity for at least a portion of the particular network equipment based at least in part upon information associated with the primary non-fungible token.

Abstract: Methods and systems are provided for a transformer model for journey simulation and prediction. In embodiments described herein, training data is obtained from stored journeys. The training data for each journey indicates customer interactions with each event in the sequence of events of the journey. A machine learning model is trained using the training data to simulate customer interaction with an input journey. The trained machine learning model then generates a simulation of customer interaction with an input journey and the results of the simulation are displayed.

Abstract: An example method to determine an object spin rate may include training a neural network with a set of initial data. The set of initial data may be generated based on a plurality of initial radar signals of a plurality of initial objects in motion. The method may include receiving a radar signal of a particular object in motion. The method may include converting the radar signal into an input vector. The input vector may include time and frequency information of the particular object in motion. The method may include providing the input vector as input to a trained neural network. The method may include determining a spin rate of the particular object in motion based on an analysis performed by the trained neural. The analysis may include analyzing the input vector including time and frequency information of the object in motion in view of the set of initial data.

Abstract: Some embodiments provide a novel method for dynamically deploying gateways for a first network connecting machines. The first network includes segments, routers, and a first gateway that connects to an external network. The method identifies a set of two or more segments that consumes more than a threshold amount of bandwidth of the first gateway. The identified set includes at least first and second segments. The method identifies one or more segment groups by aggregating two or more segments in the identified set. A first segment group includes the first and second segments and a third segment that is not in the identified set of two or more segments. The method configures a second gateway to process flows associated with each identified group including the first group. The method configures a set of routers to forward flows from machines of each segment of each identified group to the second gateway.

Abstract: Some embodiments provide a novel method for preemptively deploying gateways in a first network to one or more external networks. The first network of some embodiments includes a first gateway connecting to the one or more external networks. The method collects a set of statistics for the first gateway associated with bandwidth usage of the first gateway. The method determines that a second gateway needs to be deployed in the first network (1) by using the collected set of statistics to perform predictive modeling computations to predict a future load on the first gateway, and (2) by determining that the predicted future load exceeds a particular threshold. The method distributes a set of one or more forwarding rules to forward data message flows from a subset of machines in the first network to a particular external network through the second gateway.