USING MACHINE LEARNING FOR SECURITY ANOMALY DETECTION AND USER EXPERIENCE INFERENCE

Invention Application

US20230067756A1 USING MACHINE LEARNING FOR SECURITY ANOMALY DETECTION AND USER EXPERIENCE INFERENCE 有权

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Patent Title: USING MACHINE LEARNING FOR SECURITY ANOMALY DETECTION AND USER EXPERIENCE INFERENCE
Application No.: US17465028

Application Date: 2021-09-02
Publication No.: US20230067756A1

Publication Date: 2023-03-02
Inventor: Wei Wang
Applicant: AT&T Intellectual Property I, L.P.
Applicant Address: US GA Atlanta
Assignee: AT&T Intellectual Property I, L.P.
Current Assignee: AT&T Intellectual Property I, L.P.
Current Assignee Address: US GA Atlanta
Main IPC: H04L12/24
IPC: H04L12/24 ; H04L12/46 ; G06Q30/02

USING MACHINE LEARNING FOR SECURITY ANOMALY DETECTION AND USER EXPERIENCE INFERENCE

Abstract:

The system may obtain log data and other device/statistical information and automatically identify a normal user experience, positive user experience, negative user experience, or the like. For the negative user experience, different groups of anomalies can be further identified as different types of negative user experiences. Such a system can initiate more targeted user experience study, identify software bugs, configuration issues, or security risks.

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