The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Apr. 20, 2021

Filed:

Nov. 20, 2018
Applicant:

Institute for Information Industry, Taipei, TW;

Inventors:

Wei-Chao Hsu, Taipei, TW;

Ying-Tsun Ke, Taipei, TW;

Jiann-Liang Chen, Taipei, TW;

Yu-Hung Chen, Kaohsiung, TW;

Yan-Ju Chen, Keelung, TW;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04L 29/06 (2006.01); G06K 9/62 (2006.01); G06F 21/56 (2013.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
G06K 9/6257 (2013.01); G06F 21/56 (2013.01); G06N 20/00 (2019.01); H04L 63/1425 (2013.01);
Abstract

A malicious software recognition apparatus and method are provided. The malicious software recognition apparatus stores a training dataset, which includes a plurality of network flow datasets. Each network flow dataset corresponds to one of a plurality of software categories, and the software categories include a plurality of malicious software categories. The malicious software recognition apparatus tests a malicious software recognition model and learns that a plurality of recognition accuracies of a subset of the malicious software categories are low, determines that an overlap degree of the network flow datasets corresponding to the subset is high, updates the software categories by combining the malicious software categories corresponding to the subset, updates the training dataset by integrating the network flow datasets corresponding to the subset, trains the malicious software recognition model according to the updated training dataset. The trained malicious software recognition model is deployed to the real world.


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