Výsledky vyhledávání - "Gun-Yoon Shin"

Akademický článek

Dark Side of the Web: Dark Web Classification Based on TextCNN and Topic Modeling Weight

Autor: Gun-Yoon Shin, Younghoan Jang, Dong-Wook Kim, Sungjin Park, A-Ran Park, Younghwan Kim, Myung-Mook Han

Publikováno v: IEEE Access, Vol 12, Pp 36361-36371 (2024)

The Dark Web is an internet domain that ensures user anonymity and has increasingly become a focal point for illegal activities and a repository for information on cyberattacks owing to the challenges in tracking its users. This study examined the cl

Externí odkaz: https://doaj.org/article/60d307afa1304f298efbfed9af9b62ac

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Akademický článek

Framework for Network Topology Generation and Traffic Prediction Analytics for Cyber Exercises

Autor: Dong-Wook Kim, Gun-Yoon Shin, Young-Hoan Jang, Seungjae Cho, Kwangsoo Kim, Jaesik Kang, Myung-Mook Han

Publikováno v: IEEE Access, Vol 12, Pp 23869-23880 (2024)

Today’s cyber-attacks have become increasingly sophisticated and diverse, targeting systems that hold sensitive information, creating the need for continuous cyber exercise and skill development for cyber professionals. Because cyber exercises requ

Externí odkaz: https://doaj.org/article/7b428991a65242aea66ed2671f5d7058

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Akademický článek

An Investigation of Learning Model Technologies for Network Traffic Classification Design in Cyber Security Exercises

Autor: Younghoan Jang, Dong-Wook Kim, Gun-Yoon Shin, Seungjae Cho, Kwangsoo Kim, Jaesik Kang, Myung-Mook Han

Publikováno v: IEEE Access, Vol 11, Pp 138712-138731 (2023)

With the proliferation of network systems, the boundaries between cyber and physical environments are blurring, leading to an increased risk of sophisticated cyber-attacks equipped with advanced technologies. In particular, as advancements in artific

Externí odkaz: https://doaj.org/article/ea2eb63ef4374a8c95c210efd9a7a63e

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Akademický článek

Open Set Recognition With Dissimilarity Weight for Unknown Attack Detection

Autor: Gun-Yoon Shin, Dong-Wook Kim, Myung-Mook Han

Publikováno v: IEEE Access, Vol 11, Pp 102381-102390 (2023)

The continuous advancement of information technology has improved user convenience but has also made it more vulnerable to cyber attacks. In particular, attackers use advanced techniques to perform new attacks. In cyber security, such attacks are def

Externí odkaz: https://doaj.org/article/cb58f4f006c1447d92d4fe6e306273b2

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Akademický článek

Data Discretization and Decision Boundary Data Point Analysis for Unknown Attack Detection

Autor: Gun-Yoon Shin, Dong-Wook Kim, Myung-Mook Han

Publikováno v: IEEE Access, Vol 10, Pp 114008-114015 (2022)

Researchers have continuously sought effective ways to detect unknown (zero-day) cyberattacks in real time. Most current methods rely on pattern-recognition to identify known threats when they appear. Recently, machine learning anomaly detection tool

Externí odkaz: https://doaj.org/article/795080a09dc743cba34652e3ac2f78fd

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Akademický článek

Network Security Node-Edge Scoring System Using Attack Graph Based on Vulnerability Correlation

Autor: Gun-Yoon Shin, Sung-Sam Hong, Jung-Sik Lee, In-Sung Han, Hwa-Kyung Kim, Haeng-Rok Oh

Publikováno v: Applied Sciences, Vol 12, Iss 14, p 6852 (2022)

As network technology has advanced, and as larger and larger quantities of data are being collected, networks are becoming increasingly complex. Various vulnerabilities are being identified in such networks, and related attacks are continuously occur

Externí odkaz: https://doaj.org/article/b92fdde1cda6446d9f435d804154f96c

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