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Patent Searching and Data


Title:
SYSTEM AND METHOD FOR LEARNING AND DETECTING ABNORMAL BEHAVIOR BY USING REGRESSION SECURITY CHECK
Document Type and Number:
WIPO Patent Application WO/2022/145838
Kind Code:
A1
Abstract:
Disclosed are a method and system for learning and detecting abnormal behavior by using a regression security check. The method comprises: a step for performing, by the system, a packet storage process for selectively storing at least some of a plurality of packets passing through a network; a zero-day penetration determination step for examining, by the system, storage packets stored through the packet storage process and determining whether there is zero-day penetration corresponding to a new security rule that is to be applied to the network; and a step for generating, by the system, normalization data on the basis of penetration behaviors that occur due to the zero-day penetration, wherein a behavior pattern determination model for determining a behavior pattern corresponding to the zero-day penetration is learned on the basis of the generated normalization data.

Inventors:
LEE SI YOUNG (KR)
Application Number:
PCT/KR2021/019355
Publication Date:
July 07, 2022
Filing Date:
December 20, 2021
Export Citation:
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Assignee:
XABYSS INC (KR)
International Classes:
G06F21/55; G06F21/57; G06N20/00
Foreign References:
KR20160002058A2016-01-07
KR100769221B12007-10-29
KR20200133644A2020-11-30
Other References:
OH, JINTAE ET AL.: "Real-time Response Technology to Prevent Zero-day Attack", JOURNAL OF THE KOREAN SOCIETY FOR INTERNET INFORMATION (KSII), vol. 9, no. 3, September 2008 (2008-09-01), Korea , pages 25 - 31, XP009538015, ISSN: 1598-0170
CHOI HEE-SIK, ET AL.: "Analysis of Security Problems of Deep Learning Technology", JOURNAL OF THE KOREA CONVERGENCE SOCIETY, vol. 10, no. 5, 30 May 2019 (2019-05-30), pages 9 - 16, XP055948446, ISSN: 2233-4890, DOI: 10.15207/JKCS.2019.10.5.009
Attorney, Agent or Firm:
SHIM, Choong Sup (KR)
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