Enhanced capabilities within a telephone network are made accessible to a telecommunications device. The telecommunications device is used to dial a sequence. A network server receives and identifies the sequence invokes an advanced network function. A advanced network function server in communication with the network server provides instructions as to how the network server is to provide the advanced network function. The network server processes the call in accordance with the received instructions to provide the particular advanced network function.

Enhanced capabilities within a telephone network are made accessible to a telecommunications device. The telecommunications device is used to dial a sequence. A network server receives and identifies the sequence invokes an advanced network function. A advanced network function server in communication with the network server provides instructions as to how the network server is to provide the advanced network function. The network server processes the call in accordance with the received instructions to provide the particular advanced network function.

Systems and methods are disclosed for using machine-learning techniques for labeling incoming calls with categories relating to a risk level. A model is generated using call log data. The call log data is augmented using information from additional data sources to generate features for the model. The model may then be used to categorize additional incoming calls. The model may be used in real-time to categorize incoming calls, or categorization results may be stored for a plurality of calling numbers. Various embodiments provide various technical advantages by virtue of how the components of the system are deployed between an endpoint communication device, a telephony provider system, and possibly other systems.

Pre-authorized communication services and/or transactions are provided via a plurality of networks in response to a request received from a user to provide at least one of a communication service, a transaction and user account information via a plurality of networks of different types. Prior to processing the request, there is verification of the user's authorization to receive the at least one of the communication service, the transaction, and the user account information, and that an account associated with the user has a sufficient amount currently available for payment of the at least one of the communication service and the transaction. After verification, an authorized account associated with the user is charged in real time as the at least one of the communication service and the transaction is provided.

Systems and methods for using machine-learning techniques for labeling incoming calls with categories relating to a risk level. A model is generated using call log data. The call log data is augmented using information from additional data sources to generate features for the model. The model may then be used to categorize additional incoming calls. The model may be used in real-time to categorize incoming calls, or categorization results may be stored for a plurality of calling numbers. Various embodiments provide various technical advantages by virtue of how the components of the system are deployed between an endpoint communication device, a telephony provider system, and possibly other systems.

Aspects of the invention determining a threat score of a call traversing a telecommunications network by leveraging the signaling used to originate, propagate and terminate the call. Outer-edge data utilized to originate the call may be analyzed against historical, or third party real-time data to determine the propensity of calls originating from those facilities to be categorized as a threat. Storing the outer edge data before the call is sent over the communications network permits such data to be preserved and not subjected to manipulations during traversal of the communications network. This allows identification of threat attempts based on the outer edge data from origination facilities, thereby allowing isolation of a compromised network facility that may or may not be known to be compromised by its respective network owner. Other aspects utilize inner edge data from an intermediate node of the communications network which may be analyzed against other inner edge data from other intermediate nodes and/or outer edge data.

The present disclosure is directed to consolidation of STP pairs without deploying new STP pairs and without making changes at a Service Switching Point to reflect the consolidation. In one aspect, a method includes identifying a first pair of signal transfer point devices to be decommissioned from a telecommunication network; identifying a second pair of signal transfer point devices to assume, in part, functionalities of the first pair of signal transfer point devices, each signal transfer point device of the first pair and the second pair having at least one primary point code and at least one secondary point code assigning a temporary secondary point code to each signal transfer point device of the first pair; and modifying at least one secondary point code of each signal transfer point device of the second pair with a primary point code of at least one signal transfer point device of the first pair.

Aspects of the invention determining a threat score of a call traversing a telecommunications network by leveraging the signaling used to originate, propagate and terminate the call. Outer-edge data utilized to originate the call may be analyzed against historical, or third party real-time data to determine the propensity of calls originating from those facilities to be categorized as a threat. Storing the outer edge data before the call is sent over the communications network permits such data to be preserved and not subjected to manipulations during traversal of the communications network. This allows identification of threat attempts based on the outer edge data from origination facilities, thereby allowing isolation of a compromised network facility that may or may not be known to be compromised by its respective network owner. Other aspects utilize inner edge data from an intermediate node of the communications network which may be analyzed against other inner edge data from other intermediate nodes and/or outer edge data.

Enhanced capabilities within a telephone network are made accessible to a telecommunications device. The telecommunications device is used to dial a sequence. A network server receives and identifies the sequence invokes an advanced network function. A advanced network function server in communication with the network server provides instructions as to how the network server is to provide the advanced network function. The network server processes the call in accordance with the received instructions to provide the particular advanced network function.

Systems and methods are disclosed for using machine-learning techniques for labeling incoming calls with categories relating to a risk level. A model is generated using call log data. The call log data is augmented using information from additional data sources to generate features for the model. The model may then be used to categorize additional incoming calls. The model may be used in real-time to categorize incoming calls, or categorization results may be stored for a plurality of calling numbers. Various embodiments provide various technical advantages by virtue of how the components of the system are deployed between an endpoint communication device, a telephony provider system, and possibly other systems.