Invention Application
- Patent Title: Creating and Using Learning Models to Identify Botnet Traffic
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Application No.: US17102471Application Date: 2020-11-24
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Publication No.: US20220164697A1Publication Date: 2022-05-26
- Inventor: Ganesh Subramaniam , Robert Archibald , Richard Hellstern
- Applicant: AT&T Intellectual Property I, L.P. , AT&T Technical Services Company, Inc.
- Applicant Address: US GA Atlanta; US VA Vienna
- Assignee: AT&T Intellectual Property I, L.P.,AT&T Technical Services Company, Inc.
- Current Assignee: AT&T Intellectual Property I, L.P.,AT&T Technical Services Company, Inc.
- Current Assignee Address: US GA Atlanta; US VA Vienna
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06N5/02

Abstract:
Creating and using learning models to identify botnet traffic can include obtaining netflow data associated with a connecting device that is communicating with a carrier network. The netflow data can represent communications associated with the connecting device. Data features associated with the communications can be extracted. The data features can include statistical information associated with the communications. A learning model based on the data features extracted from the netflow data can be trained. A prediction using the learning model can be generated, and an action based on the prediction can be taken.
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