Abstract: A system includes a first data center that includes a first computing device communicatively coupled to a first database. The first computing device is configured to determine data stored in the first database to be replicated to a second database communicatively coupled to a second computing device of a remote data center. The first computing device is further configured to determine whether a point-to-point data tunnel has been established across a broadband cellular network between the first computing device and the second computing device and to establish the point-to-point data tunnel across the broadband cellular network between the first computing device and the second computing device when it is determined that the point-to-point data tunnel has not been established. The first computing device is further configured to replicate the data to the second database by transmitting the data to the second computing device across the point-to-point data tunnel.

Abstract: Arrangements for dynamic enterprise center access control are provided. In some examples, a user device may be detected and current location and/or user data associated with the detected device may be requested. Upon receiving the location data, a current geographic location of the user device may be determined and an enterprise center at or near the geographic location may be identified. Received user data may be analyzed to identify a user and retrieve access preferences associated with the user. Based on the access preferences, a command to lock or unlock a door (e.g., permit or disable access) to an area within the enterprise center, the enterprise center in general, or the like, may be generated and transmitted to a computing device for execution. Accordingly, the system may activate desired locking configurations based on user preferences. Upon detecting that the user is no longer at the enterprise center, a command to return to default settings may be generated, transmitted and executed.

Abstract: Architecture and methods may be provided to enable a user to authenticate and complete a cardless transaction at a point-of-sale (“POS”) device. The POS device may include a keypad configured to receive a sequence of keypresses. The POS device may also include a processor configured to record the sequence of keypresses and tag each keypress with a time-stamp. The POS device may include a keypress controller configured to determine from the sequence of keypresses, a number of keypresses, a frequency of each keypress and a time-delay between each keypresss. The sequence of keypresses may be transmitted to a secure transaction network and, using a machine-learning pattern identifier, be configured to identify a pattern to the sequence of keypresses based off of the determined number of keypresses, the frequency and time-delay and then further verify that the pattern matches to a stored pattern to authenticate the cardless transaction.

Abstract: Aspects of the disclosure relate to using smart glass and distributed ledger technology to provide secure authentication for digitally hand signing documents. Smart glasses worn by a customer may be activated via an application on a mobile device. The smart glasses may then scan the document and a biometric feature of the customer. The captured biometric feature and document content may be stored on a distributed ledger system. Based on the information stored on the distributed ledger, a unique binary code may be generated. The binary code may be converted into an image and shared with the mobile application. The image may then be embedded into the document as a digital hand signature. The document and the embedded image may be submitted to nodes of the distributed ledger for authentication of the digital hand signature.

Abstract: A device configured to receive a connection request that includes device authentication credentials and to determine the user device passes authentication in response to identifying a device profile associated with the device authentication credentials. The device is further configured to receive user credentials for a first user and identify a first user identity that corresponds with the user credentials. The device is further configured to establish a first network connection with the user device, to send a token request to the user device, and to receive a token via the first network connection. The device is further configured to identify a second user identity based on the token, to determine the first user identifier matches the second user identifier, and to establish a second network connection for the user device, wherein the network connection enables the user device to access the network.

Abstract: Aspects of the disclosure relate to a dynamic virtual reality (VR) coaching computing platform. The dynamic VR coaching computing platform may configure a VR coaching model based on model training data. The dynamic VR coaching computing platform may use the VR coaching model and a user profile to select a plurality of VR modules. The dynamic VR coaching computing platform may configure a first VR module of the plurality of VR modules based on one or more user selections. The dynamic VR coaching computing platform may receive real-time feedback during execution of the first VR module. The dynamic VR coaching computing platform may select a second plurality of VR modules based on the first real-time feedback. The dynamic VR coaching computing platform may configure a second VR module of the second plurality of VR modules based on user selections.

Abstract: 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.

Abstract: A network security computing system includes a steganographic communications analysis engine monitoring incoming and outgoing messages on a secure computing network. The steganographic communications analysis engine identifies a pattern of file transfers between a first computing device on the secure computing network and an internal or external message recipient. When a pattern is identified, the steganographic communications analysis engine quarantines an associated computing device from the secure network. The steganographic communications analysis engine analyzes files transferred between the computing device and the recipient for indications of steganographic information and causes display, based on an identified indication of steganography, an indication that the computing device had been compromised by command and control malware.

Abstract: Systems, computer program products, and methods are described herein for controlling electronic communications in real time via an artificial intelligence engine based on location data and user data. The present invention may be configured to determine a location of a user device associated with a user based on location data generated by the user device and determine, using an emotional artificial intelligence engine, an emotional state of the user based on user data. The present invention may be configured to determine resources associated with the user and identify, from the resources associated with the user, relevant resources associated with an entity in proximity to the location of the user device. The present invention may be configured to generate, based on the emotional state of the user, notifications including information regarding the relevant resources and present, using an output device of the user device, the notifications to the user.

Abstract: Systems, computer program products, and methods are described herein for monitoring an artificial intelligence (AI) engine. The present invention is configured to receive, from a first network device, a first set of decision parameters associated with an AI engine; encrypt the first set of decision parameters, generating an encrypted dataset; store the encrypted dataset on a transaction object; receive, from a second network device, an output associated with the AI engine; update the transaction object based on the output associated with the AI engine; and transmit a notification to the first network device, wherein the notification comprises a decrypted dataset.

Abstract: Systems, computer program products, and methods are described herein for authentication and monitoring of an artificial intelligence (AI) engine. The present invention is configured to receive, from a first network device, a first set of binary data associated with an AI engine; calculate, based on the first set of binary data, an engine hash value; store the engine hash value; receive, from a second network device, an approval of the first set of binary data; update an approval status of the engine hash value; receive, from a network device associated with a final user, a second set of binary data; determine that a second hash value associated with the second set of binary data matches the engine hash value; and transmit a notification to the network device associated with the final user, wherein the notification instructs the network device to allow the final user to launch the AI engine.

Abstract: Systems, computer program products, and methods are described herein for machine learning based network session interaction. The present disclosure is configured to receive, from an end-point device, a user input, wherein the user input comprises natural language data; extract a first set of attributes associated with the user input; determine, using a machine learning (ML) subsystem, a first set of adaptive response actions to the user input based on the first set of attributes; and execute the first set of adaptive response actions.

Abstract: Systems, computer program products, and methods are described herein for authentication and monitoring of an artificial intelligence (AI) engine. The present invention is configured to receive, from a first network device, a first set of binary data associated with an AI engine; calculate, based on the first set of binary data, an engine hash value; store the engine hash value; receive, from a second network device, an approval of the first set of binary data; update an approval status of the engine hash value; receive, from a network device associated with a final user, a second set of binary data; determine that a second hash value associated with the second set of binary data matches the engine hash value; and transmit a notification to the network device associated with the final user, wherein the notification instructs the network device to allow the final user to launch the AI engine.

Abstract: Various aspects of the disclosure relate to monitoring a physical location to determine and/or predict anomalous activities. One or more machine learning algorithms may be used to analyze inputs from one or more sensors, cameras, audio recording equipment, and/or any other types of sensors to detect anomalous measurements/patterns. Notifications may be sent one or more devices in a network based on the detection.

Abstract: Aspects of the disclosure relate to a dynamic caching platform. The dynamic caching platform may train a machine learning model based on historical complexity score information. The dynamic caching platform may receive information streams from a client metaverse device and a metaverse host system. The dynamic caching platform may generate a complexity score based on the interaction information streams using the machine learning model. The dynamic caching platform may compare the complexity score to complexity thresholds. Based on the comparison, the dynamic caching platform may identify caching rules. The dynamic caching platform may cache interaction information based on the caching rules. The dynamic caching platform may update the complexity score using the machine learning model. The dynamic caching platform may update the caching rules based on the updated complexity score. The dynamic caching platform may cache interaction information based on the updated caching rules.

Abstract: Aspects of the disclosure relate to computing hardware and software for uniform security access. A computing platform may receive, from a 5G device, a request to access a collaborative experience service. The computing platform may identify whether the 5G device is authenticated. Based on identifying that the 5G device is authenticated, the computing platform may grant the 5G device access to an API that may be used to access the collaborative experience service. The computing platform may identify that attributes of the 5G device comply with a stored security policy, and grant access to the collaborative experience service in response. The computing platform may receive user interaction information from the 5G device, and may input the user interaction information into an anomaly detection model. Based on identifying that the interactions do not comprise an anomaly for the user, the computing platform may maintain the access to the collaborative experience service.

Abstract: Systems for item validation and image evaluation are provided. In some examples, a system may receive an instrument and associated data. The instrument may be received and at least one of a bill pay profile and a user profile may be retrieved. The bill pay profile and user profile may each include a plurality of previously processed instruments that have been determined to be valid and/or authentic. The instrument may be compared to the plurality of previously processed instruments to determine whether one or more elements of the instrument being evaluated match one or more corresponding elements of the plurality of previously processed instruments. Matching or non-matching elements may be identified. In some examples, one or more user interfaces may be generated displaying the instruments and including any highlighting or enhancements identifying matching or non-matching elements.

Abstract: Aspects of the disclosure relate to using machine-learning models to authenticate users and protect enterprise-managed information and resources. In some embodiments, a computing platform may receive user interaction data from enterprise computing infrastructure and may train one or more authentication models based on this data. Subsequently, the computing platform may receive, from a first application server, a request to authenticate a first user to a first user account in a first usage session hosted by the first application server. In response to receiving this request, the computing platform may identify whether session-specific interaction data for the first usage session is valid based on the one or more authentication models. If the interaction data is identified as being valid, the computing platform may generate and send one or more commands directing the first application server to allow the first user to access the first user account in the first usage session.

Abstract: A method for consolidating backup status data associated with backup operations performed at a specialty backup service platform into a centralized backup service platform may be provided. The method may include receiving data feeds associated with each backup operation, each data feed comprising backup status data associated with a backup operation performed at the specialty backup service platform. The method may also include extracting the backup status data from each data feed and following the extracting, conforming the backup status data at the centralized backup service platform to be consistent with the standardized format. The method may also include for each data feed received from the specialty backup service platform, running a performance-scan on the backup status data within the data feed for determining whether the backup operation was a success or a failure.

Abstract: Systems, computer program products, and methods are described herein for network traffic routing and load balancing in an electronic network. The present disclosure is configured to identify, by an application layer, at least one website access request by a user account, wherein a website access request comprises a website identifier; transmit the website access request to a traffic routing layer; identify, by the traffic routing layer, a plurality of potential websites; determine, by the traffic routing layer, whether a routing identifier is present for the user account and in response to determining the routing identifier, pin the user account to a pinned website of the potential websites based on the routing identifier; and determine, by the traffic routing layer, whether the pinned website comprises an up attribute or down attribute, and to direct the website access request based on at least this up or down attribute.