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Huy Kang Kim

Korea University · 情報科学

研究室紹介

Professor Huy Kang Kim's research lab specializes in cybersecurity, with a focus on malware detection, mobile and industrial control system (ICS) security, and anomaly detection in complex systems. The lab develops innovative, behavior-based techniques—such as leveraging DNA sequence alignment algorithms and network science—to improve the accuracy and efficiency of identifying evolving cyber threats. A key emphasis is on incorporating real-world insights, like malware creators' patterns and system-level behavioral profiles, to enhance detection and attribution in dynamic environments.

malware detectionbehavior-based analysismobile securityindustrial control systemsanomaly detection

Research Overview

Papers
334
Total Citations
6,093
Papers (5y)
81
Primary Field
情報科学

Research Output Trend

Figures are computed from collected data and may differ slightly.

Publications per year (5y)
81total
2022
2023
2024
2025
2026
Citations per year (5y)
337total
20222023202420252026

Selected Papers

15
1
Article|551 citations·2019
In-vehicle network intrusion detection using deep convolutional neural network
Hyun Min Song, Jiyoung Woo, Huy Kang Kim
SJR Q1Vehicular Communications
Computer Networks and CommunicationsComputer Science
2
Article|378 citations·2021
Cybersecurity for autonomous vehicles: Review of attacks and defense
Kyounggon Kim, Jun Seok Kim, Seong Hoon Jeong, Jo-Hee Park, Huy Kang Kim
SJR Q1Computers & Security
Electrical and Electronic EngineeringEngineering
3
Article|262 citations·2015
A Novel Approach to Detect Malware Based on API Call Sequence Analysis
Youngjoon Ki, Eun‐jin Kim, Huy Kang Kim
SJR Q2International Journal of Distributed Sensor NetworksOA

In the era of ubiquitous sensors and smart devices, detecting malware is becoming an endless battle between ever-evolving malware and antivirus programs that need to process ever-increasing security related data. For malware detection, various approaches have been proposed. Among them, dynamic analysis is known to be effective in terms of providing behavioral information. As malware authors increasingly use obfuscation techniques, it becomes more important to monitor how malware behaves for its

Signal ProcessingComputer Science
4
Article|175 citations·2018
Anomaly intrusion detection method for vehicular networks based on survival analysis
Mee Lan Han, Byung Il Kwak, Huy Kang Kim
SJR Q1Vehicular Communications
Electrical and Electronic EngineeringEngineering
5
Article|152 citations·2015
Detecting and Classifying Android Malware Using Static Analysis along with Creator Information
Hyunjae Kang, Jae-wook Jang, Aziz Mohaisen, Huy Kang Kim
SJR Q2International Journal of Distributed Sensor NetworksOA

Thousands of malicious applications targeting mobile devices, including the popular Android platform, are created every day. A large number of those applications are created by a small number of professional underground actors; however previous studies overlooked such information as a feature in detecting and classifying malware and in attributing malware to creators. Guided by this insight, we propose a method to improve the performance of Android malware detection by incorporating the creator'

Signal ProcessingComputer Science
6
Article|94 citations·2012
Online game bot detection based on party-play log analysis
Ah Reum Kang, Jiyoung Woo, Juyong Park, Huy Kang Kim
SJR Q1Computers & Mathematics with Applications
Signal ProcessingComputer Science
7
Article|74 citations·2021
Convolutional neural network-based intrusion detection system for AVTP streams in automotive Ethernet-based networks
Seong Hoon Jeong, Boo-Sun Jeon, Boheung Chung, Huy Kang Kim
SJR Q1Vehicular Communications
Electrical and Electronic EngineeringEngineering
8
Article|61 citations·2021
AutoVAS: An automated vulnerability analysis system with a deep learning approach
Sanghoon Jeon, Huy Kang Kim
SJR Q1Computers & Security
Information SystemsComputer Science
9
Article|57 citations·2021
Unsupervised Fault Detection on Unmanned Aerial Vehicles: Encoding and Thresholding Approach
Kyung Ho Park, Eunji Park, Huy Kang Kim
SJR Q1SensorsOA

Unmanned Aerial Vehicles are expected to create enormous benefits to society, but there are safety concerns in recognizing faults at the vehicle's control component. Prior studies proposed various fault detection approaches leveraging heuristics-based rules and supervised learning-based models, but there were several drawbacks. The rule-based approaches required an engineer to update the rules on every type of fault, and the supervised learning-based approaches necessitated the acquisition of a

Artificial IntelligenceComputer Science
10
Article|56 citations·2020
Cosine similarity based anomaly detection methodology for the CAN bus
Byung Il Kwak, Mee Lan Han, Huy Kang Kim
SJR Q1Expert Systems with Applications
Electrical and Electronic EngineeringEngineering
11
Article|54 citations·2016
Andro-Dumpsys: Anti-malware system based on the similarity of malware creator and malware centric information
Jae-wook Jang, Hyunjae Kang, Jiyoung Woo, Aziz Mohaisen, Huy Kang Kim
SJR Q1Computers & Security
Signal ProcessingComputer Science
12
Article|48 citations·2015
Andro-AutoPsy: Anti-malware system based on similarity matching of malware and malware creator-centric information
Jae-wook Jang, Hyunjae Kang, Jiyoung Woo, Aziz Mohaisen, Huy Kang Kim
Digital Investigation
Signal ProcessingComputer Science
13
Article|47 citations·2009
DSS for computer security incident response applying CBR and collaborative response
Huy Kang Kim, Kwang Hyuk Im, Sang Chan Park
SJR Q1Expert Systems with Applications
Computer Networks and CommunicationsComputer Science
14
Article|41 citations·2012
Analysis of Context Dependence in Social Interaction Networks of a Massively Multiplayer Online Role-Playing Game
Seokshin Son, Ah Reum Kang, Hyun-chul Kim, Hyun-chul Kim, Taekyoung Kwon, Juyong Park, Huy Kang Kim, Huy Kang Kim
SJR Q1PLoS ONEOA

Rapid advances in modern computing and information technology have enabled millions of people to interact online via various social network and gaming services. The widespread adoption of such online services have made possible analysis of large-scale archival data containing detailed human interactions, presenting a very promising opportunity to understand the rich and complex human behavior. In collaboration with a leading global provider of Massively Multiplayer Online Role-Playing Games (MMO

Statistical and Nonlinear PhysicsPhysics and Astronomy
15
Article|40 citations·2022
STRIDE‐based threat modeling and DREAD evaluation for the distributed control system in the oil refinery
Kyoung Ho Kim, Kyounggon Kim, Huy Kang Kim
SJR Q2ETRI JournalOA

Industrial control systems (ICSs) used to be operated in closed networks, that is, separated physically from the Internet and corporate networks, and independent protocols were used for each manufacturer. Thus, their operation was relatively safe from cyberattacks. However, with advances in recent technologies, such as big data and internet of things, companies have been trying to use data generated from the ICS environment to improve production yield and minimize process downtime. Thus, ICSs ar

Information SystemsComputer Science

Research Areas

Signal ProcessingComputer Networks and CommunicationsInformation SystemsArtificial IntelligenceElectrical and Electronic EngineeringSociology and Political Science

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