US 12,696,095 B2Granted

Detecting fraudulent SIM card activity while roaming outside a telecommunications network

AssigneeMicrosoft Technology Licensing, LLC

InventorsAndrew John Robinson Hodges, Edmund Richard James Pringle, Keith Stuart Wansbrough, Martin George Davidson

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Abstract

The present disclosure generally relates to predicting and remediating fraudulent activity associated with a roaming SIM card. Systems described herein involve detecting potential fraud signals associated with a roaming SIM card and applying one or more machine learning models to those signals to generate a fraud prediction. In one or more examples, the potential fraud signals are detected in connection with one or more core network components of a 5G telecommunication network and provide unique insight into the network activities of a user equipment where the roaming SIM card is installed. As such, the systems described herein generate fraud predictions that take into account signals that are not necessarily indicative of fraud by themselves. Once fraud is predicted, the systems described herein execute various remediation actions to correct the fraudulent activities.

Claims19

Dependent claims

In a telecommunication network including one or more subscriber data management functions, a method for detecting fraudulent subscriber identity module (SIM) card usage comprising:

registering a user equipment with the telecommunication network based on one or more interactions with a SIM card installed on the user equipment;
receiving, from a user plane function (UPF) implemented on the telecommunication network, latency data collected by the UPF for communications associated with the user equipment;
detecting a combination of potential fraud signals associated with the SIM card based on a combination of subscriber data received from one or more subscriber data management functions and the latency data collected by the UPF, wherein the subscriber data is obtained when registering the user equipment with the telecommunication network;
applying one or more machine learning models to the combination of potential fraud signals to generate a fraud prediction associated with the SIM card, the fraud prediction being based at least in part on an observed latency from the latency data exceeding an expected latency for the user equipment by a threshold amount, the expected latency being based on the subscriber data;
and
executing one or more remediation actions associated with the user equipment based on the fraud prediction.

3 more elements

A system comprising:

at least one processor:
memory in electronic communication with the at least one processor;
and
instructions stored in the memory, the instructions being executable by the at least one processor to:
register a user equipment with a telecommunication network based on one or more interactions with a subscriber identity module (SIM) card installed on the user equipment;
receive, from a user plane function (UPF) implemented on the telecommunication network, latency data collected by the UPF for communications associated with the user equipment;
detect a combination of potential fraud signals associated with the SIM card based on a combination of subscriber data received from one or more subscriber data management functions and latency data collected by the UPF, wherein the subscriber data is obtained when registering the user equipment with the telecommunication network;
applying one or more machine learning models to the combination of potential fraud signals to generate a fraud prediction associated with the SIM card, the fraud prediction being based at least in part on an observed latency from the latency data exceeding an expected latency for the user equipment by a threshold amount, the expected latency being based on the subscriber data;
and
execute one or more remediation actions associated with the user equipment based on the fraud prediction.

7 more elements

In a fifth generation (5G) mobile communication network including one or more subscriber data management functions, a method for detecting fraudulent subscriber identity module (SIM) card usage comprising:

registering a user equipment with the 5G mobile communication network based on one or more interactions with a SIM card installed on the user equipment;
receiving, from a user plane function (UPF) implemented on the 5G mobile communication network, latency data collected by the UPF for communications associated with the user equipment;
detecting a combination of potential fraud signals associated with the SIM card based on a combination of subscriber data received from one or more subscriber data management functions and the latency data collected by the UPF, wherein the subscriber data is being obtained when registering the user equipment with the 5G mobile communication network;
applying one or more machine learning models to the combination of potential fraud signals to generate a fraud prediction associated with the SIM card, the fraud prediction being based at least in part on an observed latency from the latency data exceeding an expected latency for the user equipment by a threshold amount, the expected latency being based on the subscriber data;
and
generating and transmitting a fraud alert associated with the user equipment based on the fraud prediction.

3 more elements

Dependencies are inferred from the claim text.