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公开(公告)号：US20240080689A1
公开(公告)日：2024-03-07
申请号：US18388546
申请日：2023-11-10
Applicant: Verizon Patent and Licensing Inc.
Inventor： Subham Biswas , Bharatwaaj Shankar , Sudhakar X. Lanka , Eswara P. Somarouthu , Keerthi Gudur
CPC classification number: H04W24/08 , G06N20/00 , H04W4/24 , H04W12/06 , H04W24/10 , H04W28/0252 , H04W64/003 , H04W72/51
Abstract: One or more computing devices, systems, and/or methods for identifying anomalous behavior of users are provided. In an example, users of a telecommunication service provider may be segmented into a plurality of user segments based upon telecommunication service metrics associated with the users. A machine learning model may be trained using telecommunication service information associated with users of the first user segment to generate a trained machine learning model. Using the trained machine learning model, a forecast of telecommunication service usage associated with a first user segment of the plurality of user segments. A telecommunication service usage metric, associated with a user belonging to the first user segment, may be compared with a range indicated by the forecast. The user may be flagged as having anomalous behavior based upon a determination that one or more telecommunication usage metrics, associated with the user, are outside one or more ranges indicated by the forecast.
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公开(公告)号：US11832119B2
公开(公告)日：2023-11-28
申请号：US17462602
申请日：2021-08-31
Applicant: Verizon Patent and Licensing Inc.
Inventor： Subham Biswas , Bharatwaaj Shankar , Sudhakar X. Lanka , Eswara P. Somarouthu , Keerthi Gudur
CPC classification number: H04W24/08 , G06N20/00 , H04W4/24 , H04W12/06 , H04W24/10 , H04W28/0252 , H04W64/003 , H04W72/51
Abstract: One or more computing devices, systems, and/or methods for identifying anomalous behavior of users are provided. In an example, users of a telecommunication service provider may be segmented into a plurality of user segments based upon telecommunication service metrics associated with the users. A machine learning model may be trained using telecommunication service information associated with users of the first user segment to generate a trained machine learning model. Using the trained machine learning model, a forecast of telecommunication service usage associated with a first user segment of the plurality of user segments. A telecommunication service usage metric, associated with a user belonging to the first user segment, may be compared with a range indicated by the forecast. The user may be flagged as having anomalous behavior based upon a determination that one or more telecommunication usage metrics, associated with the user, are outside one or more ranges indicated by the forecast.
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公开(公告)号：US20230065889A1
公开(公告)日：2023-03-02
申请号：US17462602
申请日：2021-08-31
Applicant: Verizon Patent and Licensing Inc.
Inventor： Subham Biswas , Bharatwaaj Shankar , Sudhakar X. Lanka , Eswar P. Somarouthu , Keerthi Gudur
Abstract: One or more computing devices, systems, and/or methods for identifying anomalous behavior of users are provided. In an example, users of a telecommunication service provider may be segmented into a plurality of user segments based upon telecommunication service metrics associated with the users. A machine learning model may be trained using telecommunication service information associated with users of the first user segment to generate a trained machine learning model. Using the trained machine learning model, a forecast of telecommunication service usage associated with a first user segment of the plurality of user segments. A telecommunication service usage metric, associated with a user belonging to the first user segment, may be compared with a range indicated by the forecast. The user may be flagged as having anomalous behavior based upon a determination that one or more telecommunication usage metrics, associated with the user, are outside one or more ranges indicated by the forecast.
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