Abstract: Aspects of the subject disclosure may include, for example: obtaining first information identifying a first path between a source node located in a network and a destination node located in the network, wherein the first path comprises a first plurality of nodes including at least one first intermediate node between the source node and the destination node, and wherein the first information comprises first latency information that identifies a first travel latency that exists on the first path between the source node and the destination node; obtaining second information identifying a second path between the source node and the destination node, wherein the second path comprises a second plurality of nodes including at least the source node and the destination node, and wherein the second information comprises second latency information that identifies a second travel latency that exists on the second path between the source node and the destination node; and selecting as a selected path either the first path

Abstract: Aspects of the subject disclosure may include, for example, receiving, from a machine learning model, information about an event causing a service degradation in a cellular network, wherein the event is external to the cellular network, determining one or more event categories associated with the event causing the service degradation, determining, based on the one or more event categories, likely affected customers, the likely affected customers being likely to experience the service degradation, determining, by the machine learning model, proper resources for resolution of the service degradation, wherein the determining proper resources is based on the one or more event categories, and dispatching the proper resources for resolution of the service degradation. Other embodiments are disclosed.

Abstract: Concepts and technologies disclosed herein are directed to event-based wireless emergency alerts (“WEAs”). According to one aspect disclosed herein, a WEA-capable device can receive an event-based wireless emergency alert that includes an event code and alert content. The WEA-capable device can parse the event code from the event-based WEA. The WEA-capable device can determine, via execution of an event-based WEA function, a WEA format based upon the event code. The WEA-capable device can then output the alert content in the WEA format. In some embodiments, the event code identifies a weather-related emergency event (e.g., a hurricane or tornado warning). In other embodiments, the event code identifies a non-weather-related emergency event (e.g., a child abduction alert). The WEA format can be an event-specific spoken language, an event-specific symbol, an event-specific haptic feedback, or a combination thereof.

Abstract: Aspects of the subject disclosure may include, for example, monitoring status of a network configured to provide end-to-end delivery of services to priority user equipment authorized according to a prioritized class of service and other user equipment not authorized for the prioritized class of service. The prioritized class of service extends a reserved network capacity for end-to-end delivery of a service via first domain including first network slices and a second domain including second network slices. A network interruption compromising the reserved capacity is determined based on the monitored status and integration of an alternate group of slices into one of the first network domain, the second network domain, or both to replace the compromised group of slices, is orchestrated. Integration of the alternate group of slices restores reserved network capacity according to the prioritized class of service. Other embodiments are disclosed.

Abstract: A security management service for Internet-of-things devices can obtain, from an Internet-of-things device and via a cellular network, a request by the Internet-of-things device to register with the cellular network, the Internet-of-things device including a universal integrated circuit card that stores a unique identifier for the Internet-of-things device and a cellular transceiver. The security management service can obtain behavioral data describing activity associated with the Internet-of-things device and can determine, based on the identity data and the behavioral data, if the Internet-of-things device is operating normally and as expected and if the Internet-of-things device is under the control of any unauthorized entity before allowing the Internet-of-things device to register with the cellular network.

Abstract: Aspects of the subject disclosure may include, for example, a device in a messaging core, that includes: a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations including receiving a short messaging system (SMS) message from an application-to-person (A2P) service to a mobile device of a subscriber; verifying an origin of the SMS message; identifying the SMS message as bearing a one-time passcode (OTP); preventing delivery of the SMS message to a messaging application on the mobile device; and delivering the SMS message to an application running on the mobile device. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a device including a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of: receiving domain name system (DNS) record changes; identifying errors from the DNS record changes; discarding the DNS record changes responsive to the errors identified; scheduling the DNS record changes responsive to a lack of errors identified; translating the DNS record changes into protocol specific formats; and provisioning the protocol specific formats of the translated DNS record changes. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, receiving a first request from a first communication orchestrator of a first protected environment to provide a secure and authenticated connection between a first resource of the first protected environment and a second resource of a second protected environment, accessing first encryption information from the first communication orchestrator and second encryption information from a second communication orchestrator of the second protected environment, verifying a capability for secure quantum communications of an encryption technique of the first communication orchestrator and the second communication orchestrator according to the first encryption information and the second encryption information, and enabling the first communication orchestrator and the second communication orchestrator to initiate a secure and authenticated communication channel via quantum communications. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a system including a cross-segment slice controller (CSSC) configured to interface with a software-defined network (SDN) controller and a software-defined radio (SDR) controller. The SDN controller may be associated with a core network and the SDR controller may be associated with a radio access network (RAN). The system further includes a machine learning (ML) component configured to obtain and analyze data regarding the core network and the RAN, and an intelligent end-to-end (E2E) orchestration platform (IEOP) configured to coordinate with the SDN controller and the SDR controller via the CSSC based on outputs of the ML component to provide dynamic cross-segment network slice management. Other embodiments are disclosed.

Abstract: Various embodiments disclosed herein provide for facilitating scheduling of uplink data using demodulation reference signal and scheduled resources. According to an embodiment, a system can comprise configuring a network device with a periodic rate of specified sounding reference signals with a periodicity using radio resource control signaling. The system can further facilitate estimating channel state information associated with a channel via which the network device communicates. The system can further facilitate transmitting an uplink grant with uplink transmission parameters to set up a physical uplink shared channel, wherein the uplink transmission parameters are determined based on the channel state information. The system can further facilitate estimating scheduling parameters based on a first estimation information associated with the physical uplink shared channel.

Abstract: Aspects of the subject disclosure may include, for example, transmitting a first request that includes a key, wherein the key identifies: a processing system that is a targeted recipient of an advertisement, a stream in which a primary content item is being provisioned to the processing system, and a service provider, based at least in part on the transmitting of the first request, obtaining information pertaining to an advertisement from a device of the service provider, and inserting the information within a portion of the stream corresponding to a break in the primary content item. Other embodiments are disclosed.

Abstract: A UE can enable a VoWIFI service, receive hidden SSID information, and register with a core network via a RAN. The UE can monitor a first signal strength of a first signal from the RAN. The UE can scan for a second signal from a WLAN, and when found, can measure a second signal strength of the second signal. The UE can determine whether the first signal strength is at or below a first threshold. If so, and if the WLAN is untrusted, the UE can probe it with the hidden SSID information. If the untrusted WLAN responds, the UE can send an access request to an untrusted WLAN access point. The UE can receive, via the untrusted WLAN access point, an authentication challenge from an ePDG. If the UE passes the authentication challenge, the UE can register with the core network via the untrusted WLAN and the ePDG.

Abstract: An example method includes monitoring a status of a long term evolution network connection and a status of a fifth generation network connection over which a user endpoint device is simultaneously receiving data using an evolved-universal terrestrial radio access new radio dual connectivity configuration, detecting, based on the monitoring, that a performance metric of one of: the long term evolution network or the fifth generation network falls below a predefined threshold metric, and terminating, in response to the detecting, the long term evolution network connection or the fifth generation network connection to terminate the evolved-universal terrestrial radio access new radio dual connectivity configuration.

Abstract: Concepts and technologies disclosed herein are directed to image classification attack mitigation. According to one aspect of the concepts and technologies disclosed herein, a system can obtain an original image and reduce a resolution of the original image to create a reduced resolution image. The system can classify the reduced resolution image and output a first classification. The system also can classify the original image via deep learning image classification and output a second classification. The system can compare the first classification and the second classification. In response to determining that the first classification and the second classification match, the system can output the second classification of the original image. In response to determining that the first classification and the second classification do not match, the system can output the first classification of the original image.

Abstract: Aspects of the subject disclosure may include, for example, determining that one or more tests are to be executed for a core network of a telecommunications system, based on the determining, transmitting one or more test initiation commands to a set of user equipment (UEs) of a plurality of UEs communicatively coupled to the core network, wherein the one or more test initiation commands cause the set of UEs to execute the one or more tests, obtaining, from the set of UEs, results associated with the one or more tests, analyzing the results based on one or more machine learning (ML) models to identify a network issue, and responsive to the analyzing, performing one or more actions to address the network issue. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, receiving, over a communication network, a first message utilizing a first messaging application from a first communication device associated with a first user and identifying a recipient of the first message as a second user associated with a second communication device. Further embodiments can include determining that the second user utilizes a second message application to exchange a first group of messages via the second communication device resulting in a first determination, and transmitting, over the communication network, the first message to the second communication device utilizing the second messaging application based on the first determination. Other embodiments are disclosed.

Abstract: Creating scent models and using scent models in cross-reality environments can include capturing experience data identifying a scent detected and a context in which the scent was detected. The experience data can be provided to a scent modeling service to generate a scent model that can represent perceived scents and perceived scent intensities for a user. The scent model can be used to generate cross-reality session data to be used in a cross-reality session presented by a cross-reality device. The cross-reality device can include a scent generator and can generate the cross-reality session using data obtained from the user device. The cross-reality device can generate a further scent during the cross-reality session based on the scent model.

Abstract: Aspects of the subject disclosure may include, for example, determining, by a processing system including a processor, that a first resource of a first radio access network is accommodating load in an amount less than a first threshold, resulting in a first determination, determining, by the processing system, that a signal strength of a signal emitted by the first resource is greater than a second threshold, resulting in a second determination, and based on the first determination and the second determination, causing, by the processing system, a voice call initiated by a first user equipment to be supported by the first resource, wherein prior to the causing the first user equipment obtained communication services via a second resource of a second radio access network. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, determining that a network load would consume a first amount of power if supported by a first frequency band of a network, resulting in a first determination, determining that the network load would consume a second amount of power if supported by a second frequency band of the network that is different from the first frequency band, resulting in a second determination, the second amount of power being less than the first amount of power, and based at least on the first determination and the second determination, allocating the network load to the second frequency band. Other embodiments are disclosed.

Abstract: Providing and using a user login protection service can include detecting, during a login creation process, input that indicates that a computing device has opted-in for protection for a login being created. During the login creation process, the login can be stored at a first data storage location, the login including an address that identifies a location of a distributed ledger and a password, and a reset password at a second data storage location comprising a secure data storage device. In response to detecting an attempt to log in to the third party device to access the resource, a value associated with the distributed ledger can be obtained, the value indicating a status of a trigger condition associated with the login. If the value is zero, the attempt to log in can be allowed to proceed. If the value is one, the attempt to log in can be blocked.