Title:
MALWARE DETECTION MODEL TRAINING METHOD AND MALWARE DETECTION METHOD
Document Type and Number:
WIPO Patent Application WO/2022/097898
Kind Code:
A1
Abstract:
The present disclosure provides a malware detection model training method and a malware detection method. According to one aspect of the present disclosure, provided is a method for training a malware detection model and a method for detecting malware by converting code of an app into native code, extracting a pair of instructions code from the native code, and extracting a common feature from a plurality of feature extraction algorithms on the basis of the pair of instructions code.
Inventors:
PAK WOOGUIL (KR)
Application Number:
PCT/KR2021/012224
Publication Date:
May 12, 2022
Filing Date:
September 08, 2021
Export Citation:
Assignee:
INDUSTRY ACADEMIC COOPERATION FOUNDATION OF YEUNGNAM UNIV (KR)
International Classes:
G06F21/56; G06N20/00
Foreign References:
| KR20170087007A | 2017-07-27 | |||
| KR20180001878A | 2018-01-05 | |||
| US20150205626A1 | 2015-07-23 |
Other References:
SHAHID ALAM; ZHENGYANG QU; RYAN RILEY; YAN CHEN; VAIBHAV RASTOGI: "DroidNative: Semantic-Based Detection of Android Native Code Malware", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 15 February 2016 (2016-02-15), 201 Olin Library Cornell University Ithaca, NY 14853 , XP080683703
SIMEN RUNE BRAGEN: "Malware detection through opcode sequence analysis using machine learning", MASTER'S THESIS, GJøVIK UNIVERSITY COLLEGE, 1 January 2015 (2015-01-01), Gjøvik University College, , XP055712359, Retrieved from the Internet [retrieved on 20200707]
SIMEN RUNE BRAGEN: "Malware detection through opcode sequence analysis using machine learning", MASTER'S THESIS, GJøVIK UNIVERSITY COLLEGE, 1 January 2015 (2015-01-01), Gjøvik University College, , XP055712359, Retrieved from the Internet
Attorney, Agent or Firm:
LEE, Un Cheol (KR)
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