The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Sep. 30, 2025

Filed:

Nov. 10, 2023
Applicant:

Verizon Patent and Licensing Inc., Basking Ridge, NJ (US);

Inventors:

Subham Biswas, Maharashtra, IN;

Bharatwaaj Shankar, Chennai, IN;

Sudhakar X. Lanka, Hyderabad, IN;

Eswara P. Somarouthu, Plano, TX (US);

Keerthi Gudur, Thiruvallur, IN;

Assignee:

Verizon Patent and Licensing Inc., Basking Ridge, NJ (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
H04W 24/08 (2009.01); G06N 20/00 (2019.01); H04W 4/24 (2018.01); H04W 12/06 (2021.01); H04W 24/10 (2009.01); H04W 28/02 (2009.01); H04W 64/00 (2009.01); H04W 72/51 (2023.01);
U.S. Cl.
CPC ...
H04W 24/08 (2013.01); G06N 20/00 (2019.01); H04W 4/24 (2013.01); H04W 12/06 (2013.01); H04W 24/10 (2013.01); H04W 28/0252 (2013.01); H04W 64/003 (2013.01); H04W 72/51 (2023.01);
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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