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:
Oct. 10, 2023

Filed:

Nov. 20, 2020
Applicant:

Electronics and Telecommunications Research Institute, Daejeon, KR;

Inventors:

Jung-Tae Kim, Daejeon, KR;

Ji-Hyeon Song, Daejeon, KR;

Ik-Kyun Kim, Daejeon, KR;

Young-Su Kim, Daejeon, KR;

Jong-Hyun Kim, Daejeon, KR;

Jong-Geun Park, Sejong, KR;

Sang-Min Lee, Daejeon, KR;

Jong-Hoon Lee, Daejeon, KR;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 21/56 (2013.01); G06N 5/04 (2023.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
G06F 21/563 (2013.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01); G06F 2221/033 (2013.01);
Abstract

Disclosed herein are an apparatus and method for detecting a malicious script. The apparatus includes one or more processors and executable memory for storing at least one program executed by the one or more processors. The at least one program is configured to extract token-type features, each of which corresponds to a lexical unit, and tree-node-type features of an abstract syntax tree from an input script, to train two learning models to respectively learn two pieces of learning data that are generated in consideration of features extracted respectively from the token-type features and the node-type features as having the highest frequency, and to detect whether the script is a malicious script based on the result of ensemble-based malicious script detection performed for the script, which is acquired using an ensemble detection model generated from the two learning models.


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