Invention Grant
- Patent Title: Detecting malicious code in sections of computer files
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Application No.: US15249702Application Date: 2016-08-29
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Publication No.: US10169581B2Publication Date: 2019-01-01
- Inventor: Wen-Kwang Tsao , PingHuan Wu , Wei-Zhi Liu
- Applicant: Trend Micro Incorporated
- Applicant Address: JP Tokyo
- Assignee: Trend Micro Incorporated
- Current Assignee: Trend Micro Incorporated
- Current Assignee Address: JP Tokyo
- Agency: Okamoto & Benedicto LLP
- Main IPC: G06F21/56
- IPC: G06F21/56 ; G06N99/00

Abstract:
A training data set for training a machine learning module is prepared by dividing normal files and malicious files into sections. Each section of a normal file is labeled as normal. Each section of a malicious file is labeled as malicious regardless of whether or not the section is malicious. The sections of the normal files and malicious files are used to train the machine learning module. The trained machine learning module is packaged as a machine learning model, which is provided to an endpoint computer. In the endpoint computer, an unknown file is divided into sections, which are input to the machine learning model to identify a malicious section of the unknown file, if any is present in the unknown file.
Public/Granted literature
- US20180060576A1 DETECTING MALICIOUS CODE IN SECTIONS OF COMPUTER FILES Public/Granted day:2018-03-01
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