Relationship graphs for telecommunication network fraud detection

A non-transitory computer-readable medium storing instructions which, when executed by a processing system including at least one processor, cause the processing system to perform operations, the operations comprising:

• maintaining a relationship graph that includes nodes and edges, the relationship graph representing a plurality of phone numbers and a plurality of device identifiers having associations with the plurality of phone numbers;
• obtaining an identification of a first phone number of the plurality of phone numbers or a first device identifier of the plurality of device identifiers for a fraud evaluation;
• extracting a plurality of features from the relationship graph, the plurality of features associated with at least one of the first phone number or the first device identifier, wherein the plurality of features includes:
• one or more device identifiers of the plurality of device identifiers associated with the first phone number, or one or more phone numbers of the plurality of phone numbers associated with the first device identifier;
• applying the plurality of features to a prediction model that is implemented by the processing system and that is configured to output a fraud risk value of the first phone number or the first device identifier;
• and
• implementing at least one remedial action in response to the fraud risk value.

An apparatus comprising:

• a processing system including at least one processor;
• and
• a non-transitory computer-readable medium storing instructions which, when executed by the processing system, cause the processing system to perform operations, the operations comprising:
• maintaining a relationship graph that includes nodes and edges, the relationship graph representing a plurality of phone numbers and a plurality of device identifiers having associations with the plurality of phone numbers;
• obtaining an identification of a first phone number of the plurality of phone numbers or a first device identifier of the plurality of device identifiers for a fraud evaluation;
• extracting a plurality of features from the relationship graph, the plurality of features associated with at least one of the first phone number or the first device identifier, wherein the plurality of features includes:
• one or more device identifiers of the plurality of device identifiers associated with the first phone number, or one or more phone numbers of the plurality of phone numbers associated with the first device identifier;
• applying the plurality of features to a prediction model that is implemented by the processing system and that is configured to output a fraud risk value of the first phone number or the first device identifier;
• and
• implementing at least one remedial action in response to the fraud risk value.