Invention Grant
- Patent Title: Prudent ensemble models in machine learning with high precision for use in network security
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Application No.: US16377129Application Date: 2019-04-05
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Publication No.: US11669779B2Publication Date: 2023-06-06
- Inventor: Dianhuan Lin , Rex Shang , Changsha Ma , Kevin Guo , Howie Xu
- Applicant: Zscaler, Inc.
- Applicant Address: US CA San Jose
- Assignee: Zscaler, Inc.
- Current Assignee: Zscaler, Inc.
- Current Assignee Address: US CA San Jose
- Agency: Baratta Law PLLC
- Agent Lawrence A. Baratta, Jr.; Ryan Odessa
- Main IPC: H04L29/00
- IPC: H04L29/00 ; G06N20/20 ; G06F21/55

Abstract:
Systems and methods include receiving a content item between a user device and a location on the Internet or an enterprise network; utilizing a trained machine learning ensemble model to determine whether the content item is malicious; responsive to the trained machine learning ensemble model determining the content item is malicious or determining the content item is benign but such determining is in a blind spot of the trained ensemble model, performing further processing on the content item; and, responsive to the trained machine learning ensemble model determining the content item is benign with such determination not in a blind spot of the trained machine learning ensemble model, allowing the content item. A blind spot is a location where the trained machine learning ensemble model has not seen any examples with a combination of features at the location or has examples with conflicting labels.
Public/Granted literature
- US20200320438A1 Prudent ensemble models in machine learning with high precision for use in network security Public/Granted day:2020-10-08
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