Abstract: 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.

Abstract: Systems and methods for securing a cryptocurrency asset transfer via a cross-blockchain bridge. Methods may include detecting a request to transfer the asset between blockchains and extracting a set of features such as smart contract bytecode from event logs associated with the blockchains and a blockchain bridge. Methods may include using a photonic quantum processor to use i) a long short-term neural network and ii) a neural network to generate machine learning models based on the extracted features to output i) a security risk threshold and ii) a security risk percentage, respectively. When the security risk percentage is below the security risk threshold, the method may permit the execution of a smart contract to allow transfer of the cryptocurrency asset over the blockchain bridge. When the security risk percentage is above the security risk threshold, the method may involve blocking an execution of a smart contract on the blockchain bridge.

Abstract: A system is presented for tracking user devices in a facility. Wireless signals and user information are communicated from user devices to a wireless device and a queue management server. The system determines location information for the user devices within a defined space at points in time. The system tracks the movement of the user devices within the defined space over a period based upon the location information. The system determines when user devices are within a threshold distance of corresponding resource devices based upon the determined location information. The system communicates user preference and profile information to the resource devices indicating that the user devices are within a threshold distance of the resource devices. The resource devices display customized information for user devices based upon user preference and profile information.

Abstract: An apparatus may be configured to detect radio-frequency (RF)-based attacks in a predetermined area. The server may include a memory and a processor. The memory may be configured to store a baseline RF signature corresponding to an electric component located in a predetermined area. The baseline RF signature may comprise an expected RF signature tracked from the electric component during a predetermined amount of time. The processor may be configured to monitor electronic operations of the electric component over the predetermined amount of time. The electric component may be located in the predetermined area. The processor may be configured to track an RF signature associated with the electric component. The processor may be configured to determine that the RF signature comprises an anomaly during the predetermined amount of time based at least in part upon the RF signature being different from the baseline RF signature corresponding to the electric component.

Abstract: An apparatus may be configured to detect radio-frequency (RF)-based attackers in a predetermined area. The apparatus may include a memory and a processor. The memory may be configured to store a baseline RF signature corresponding to an electric component located in the predetermined area. The processor may be configured to monitor first electronic operations of the electric component; and track a first RF signature corresponding to the first plurality of electronic operations of the electric component. The processor may be configured to determine that a new device is in the predetermined area; monitor a second plurality of electronic operations of the new device; and track a second RF signature corresponding to the second plurality of electronic operations of the new device. The processor may be configured to determine that the first RF signature comprises an anomaly in response to the first RF signature being different from the baseline RF.

Abstract: Systems, computer program products, and methods are described herein for generating individual records across multiple devices via an ultra-wideband connection. The method includes receiving a transfer request associated with a user. The method also includes determining a first transfer device. In an instance in which a first transfer device amount of the resource is less than the one or more units of the resource indicated by the transfer request, the method also includes determining a second transfer device. The method further includes creating a first transfer device non-fungible token for the first transfer device and a second transfer device non-fungible token for the second transfer device. A cumulative of the resource indicated by the first transfer device non-fungible token and the second transfer device non-fungible token are less than or equal to the one or more units of the resource indicated by the transfer request.

Abstract: Systems and methods are disclosed for validating transactions executed by Internet of Things (IoT) devices leveraging non fungible tokens (NFTs) stored on a blockchain. The system generates a first NFT paired with metadata associated with an IoT device, a second NFT paired with metadata associated with a transaction requested by the IoT device, and a third NFT merging the first and second NFTs together. The NFTs are used in validation processes to ensure an IoT device and/or a transaction requested by an IoT device are valid. The NFTs are bound to smart contracts assigned one or more rules related to validating an IoT device and/or transaction requested by an IoT device. A transaction requested by an IoT device executes based on the validation processes.

Abstract: Systems and methods are disclosed for validating transactions executed by Internet of Things (IoT) devices leveraging non fungible tokens (NFTs) stored on a blockchain. The system generates a first NFT paired with metadata associated with an IoT device, a second NFT paired with metadata associated with a transaction requested by the IoT device, and a third NFT merging the first and second NFTs together. The NFTs are used in validation processes to ensure an IoT device and/or a transaction requested by an IoT device are valid. The NFTs are bound to smart contracts assigned one or more rules related to validating an IoT device and/or transaction requested by an IoT device. A transaction requested by an IoT device executes based on the validation processes.

Abstract: A decentralized swarm intelligence algorithm over a network of paired ATMs to prevent or control surface attacks on ATMs. The ATMs may be seeded with an initial swarm intelligence model to identify suspicious activity. An ATM may relay alerts about suspicious activity at that ATM to other paired ATMs. The ATMs use machine learning to update the model and perform swarm intelligence autonomously at the paired ATMs. A bank may provide the initial swarm intelligence model, receive alerts about and analyze the attacks, and provide updated swarm intelligence models to prevent or limit future attacks. Smart contracts may be used to specify rules for performing swarm intelligence using the paired ATMs. Records regarding swarm intelligence models, attempted suspicious attacks including payment instruments that may have been used, actions taken in response to the attacks, and smart contracts may be recorded on a blockchain distributed ledger.

Abstract: A method for increasing the security of quick response (“QR”) code processing may include creating an inactive QR code. The inactive code may include an algorithmic code and a plurality of dynamic placeholders. The method may retrieve a scan of the inactive QR code using a QR code scanning device and also prevent the scan of the inactive QR code from being processed at the QR code scanning device. The method may receive the scan of the inactive QR code at a central server and interpret the algorithmic code to identify a plurality of non-fungible tokens (“NFTs”) for filling the plurality of dynamic placeholders. The method may fetch the plurality of NFTs and complete the incomplete QR code to form a complete QR code. The completing may include filling the plurality of dynamic placeholders with the plurality of NFTs and interpreting the complete QR code.

Abstract: Arrangements for optimizing quantum bit consumption of quantum programs are provided. In some aspects, a quantum program of a plurality of quantum programs to be executed on target quantum hardware may be received from a digital computing device. The quantum program may be scanned and metadata associated with the quantum program may be parsed using machine learning. In some examples, the quantum program may be optimized by modifying quantum program code for minimum quantum bit consumption using machine learning. A criticality level of the quantum program may be determined based on contextual logic associated with the quantum program. Based on the determined criticality level, a priority sequence may be determined, indicating an order in which the plurality of quantum programs are to be deployed to the target quantum hardware. The quantum program may be transmitted to the target quantum hardware according to the priority sequence.

Abstract: Arrangements for intelligent orchestration of quantum programs using smart contracts linked to quantum program non-fungible tokens (NFTs) are provided. A plurality of quantum programs to be executed on target quantum hardware may be received from a digital computing device. NFTs representing each of the plurality of quantum programs may be created and linked to a corresponding quantum program. The NFTs may be stored on a distributed ledger and controlled by smart contracts storing predefined acceptance rules based on which a quantum processing output is deployed to the digital computing device. A quantum program may be validated for respective target quantum hardware by validating the NFT associated with the quantum program. The respective target quantum hardware may ingest the validated quantum program and perform quantum processing. Responsive the output of quantum processing meeting the predefined acceptance criterion, the output of the quantum processing may be deployed in the digital computing device.

Abstract: A method for establishing an alternative transaction gateway when a default transaction network is down leveraging a network of low-orbit satellites is provided. The method may include creating, using an internet of things (“IoT”) device, a non-fungible token (“NFT”) associated with a transaction executed at the IoT device. The method may include storing the NFT at the IoT device pending proximity to a low-orbit satellite. The method may further include transmitting the NFT to a first low-orbit satellite when the first low-orbit satellite is within a first pre-determined proximity to the IoT device. The method may include, in response to receiving the NFT at the first low-orbit satellite, running a smart contract to identify an optimal pathway for transporting the NFT. The pathway may include the first low-orbit satellite and one or more additional low-orbit satellites from the network operating as carriers for the NFT to a centralized server.

Abstract: Aspects of the disclosure relate to monitoring and deploying security policy rules in in a container-based computing infrastructure. A computing platform may train a quantum knowledge graph based on interactions in a container-based computing infrastructure. The computing platform may generate and deploy, to the container-based computing infrastructure, one or more security rules associated with interactions in the container-based computing infrastructure based on the quantum knowledge graph les. Subsequently, the computing platform may monitor interactions between containers in the container-based computing infrastructure and identify, using the quantum knowledge graph, an anomaly in a first interaction between a first container and a second container.

Abstract: A system is configured to determine multiple sub-requests from one of service requests received from a user device. The system associates each sub-request to at least one knowledge domain. The sub-requests are transmitted to a decentralized network. In turn, the decentralized network generates one or more responses associated with each knowledge domain in each sub-request. At this stage, the system relates multiple responses corresponding to the received service request to a same identifier (i.e., a common identifier) and provide the responses related to the identifier to the user device as a single service request response.

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.

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: The inventive subject matter is directed to pest detection systems that implement infrared emitters with detectors that look for variations in incident light indicative of wingbeats from various pests. Emitters and detectors are placed on one or more printed circuit boards such that infrared light projected from an emitter can be received by one or more detectors. Based on signal generated by a detector, systems of the inventive subject matter can determine whether a pest has flown between an emitter and detector. To save on power, emitter, detectors, or both can be driven by pulse width modulation. Methods of the inventive subject matter are directed to determining pest presence via signal filtering and interpretation.

Abstract: Systems, methods and apparatus are provided for a Dynamic Group Session Data Access Protocol. The system may monitor participant input in a group interactive session. The system may be trained to monitor and understand the group environment and predict intent of the participant discussion and may predict relevant data. The system may be used by a single participant or by multiple participants. The system may determine the access level of the participants. The system may determine the access level of the data. The system may compare the access level of the participants with the access level of the data. The system may dynamically mask the data if the access level of the participants does not match the access level of the data. The system may create customized views of the data for each participant based on the participant's access level and the access level of the data.

Abstract: Systems, apparatus, articles of manufacture, and methods for external display power loss detection and sleep state recovery are disclosed. Example apparatus disclosed herein include first circuitry to set an output of the first circuitry to a first logic value after a determination that a compute device is to enter a sleep state, and set the output to a second logic value after a determination that the compute device is to exit the sleep state. Disclosed example apparatus also include second circuitry to switch control of a hot plug detect (HPD) input of high-definition multimedia interface (HDMI) circuitry between an output of power loss sensing circuitry and an HPD line of an HDMI port of the HDMI circuitry based on the output of the first circuitry.