公开(公告)号：US20220366430A1

公开(公告)日：2022-11-17

申请号：US17321279

申请日：2021-05-14

Applicant: AT&T Intellectual Property I, L.P.

Inventor： Ryan Steckel ,  Ana Armenta ,  Prince Paulraj ,  Chih Chien Huang

IPC: G06Q30/00 ,  G06N20/00 ,  G06F21/45

Abstract: Data stream based event sequence anomaly detection for mobility customer fraud analysis is presented herein. A system obtains a sequence of events comprising respective modalities of communication that correspond to a subscriber identity associated with a communication service—the sequence of events having occurred within a defined period. Based on defined classifiers representing respective fraudulent sequences of events, the system determines, via a group of machine learning models corresponding to respective machine learning processes, whether the sequence of events satisfies a defined condition with respect to likelihood of representing a fraudulent sequence of events of the respective fraudulent sequences of events. In response to the sequence of events being determined to satisfy the defined condition, the system sends, via a user interface of the system, a notification indicating that the sequence of events has been determined to represent the fraudulent sequence of events.

公开(公告)号：US11979521B2

公开(公告)日：2024-05-07

申请号：US17321279

申请日：2021-05-14

Applicant: AT&T Intellectual Property I, L.P.

Inventor： Ryan Steckel ,  Ana Armenta ,  Prince Paulraj ,  Chih Chien Huang

IPC: H04M7/00 ,  H04L51/21 ,  H04M3/22 ,  G06Q20/40

CPC classification number: H04M7/0078 ,  H04L51/21 ,  H04M3/22 ,  G06Q20/4016

Abstract: Data stream based event sequence anomaly detection for mobility customer fraud analysis is presented herein. A system obtains a sequence of events comprising respective modalities of communication that correspond to a subscriber identity associated with a communication service—the sequence of events having occurred within a defined period. Based on defined classifiers representing respective fraudulent sequences of events, the system determines, via a group of machine learning models corresponding to respective machine learning processes, whether the sequence of events satisfies a defined condition with respect to likelihood of representing a fraudulent sequence of events of the respective fraudulent sequences of events. In response to the sequence of events being determined to satisfy the defined condition, the system sends, via a user interface of the system, a notification indicating that the sequence of events has been determined to represent the fraudulent sequence of events.