김휘강 교수
Huy Kang Kim
고려대학교 정보보호대학원 · 컴퓨터과학
연구실 소개
김휘강 교수의 연구실은 사이버 보안 분야에서 핵심적인 과제인 악성코드 탐지 및 공격 대응 기술을 연구하고 있습니다. 특히 모바일 악성코드의 생성자 특성 분석, 동적 분석 기반의 효율적 행동 분류, 그리고 산업 제어 시스템의 보안 취약점 진단에 초점을 맞추고 있습니다. 최근에는 스마트 기기와 IOT 환경에서 발생하는 보안 위협에 대응하기 위한 하이브리드 분석 기법과 네트워크 과학 기반 사용자 행동 분석도 함께 진행하고 있습니다. 기술적 혁신과 실질적 보안 적용을 융합한 연구를 지속하고 있습니다.
연구 현황
연구 성과 추이
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
주요 논문
15In 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
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'
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
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
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
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