해킹대응기술연구실 (Hacking and Countermeasure Research Lab.)
http://ocslab.hksecurity.net
세부 연구 분야는 다음과 같습니다. 첫째, 데이터마이닝과 머신러닝 기술을 보안분야에 접목하여, 온라인게임 서비스 분야에서는 게임봇과 작업장을 탐지하는 연구를 전세계에서 가장 많이 수행하고 있습니다. 둘째, CAN 트래픽 데이터 분석을 기반으로 자동차용 침입탐지 분야 연구를 하고 있으며, 전세계에서 유일한 실제 차량 주행 및 공격 데이터를 가지고 있습니다. 최근 ITU-T SG17에서 자동차 보안의 국제표준화 활동을 하고 있습니다. 셋째, 소액 결제 및 간편결제 등 금융 결제 데이터를 분석하여 이상 거래를 탐지하는 Fraud Detection System을 개발하였으며, 지속적으로 산학협력을 통해 발전시켜 나가고 있습니다. 넷째, 대규모 데이터 분석을 토대로 악성코드 프로파일링, 해커 프로파일링, 침해사고 프로파일링을 하는 사이버게놈 시스템 (Cyber-Genome System)을 개발하였으며, 지속적으로 사이버위협 인텔리전스 (Cyber Threat Intelligence) 및 보안 시각화 (Security Visualization) 분야의 연구를 수행하고 있습니다.
해킹대응기술 연구실은 국제공동연구 및 산학협력연구를 활발히 진행하고 있으며, WWW (the Web Conference), NDSS, IEEE Trans. on Information Forensics and Security 등 top conference 및 journal 에 지속적으로 연구결과를 게재하고 있습니다.
Hacking and Countermeasure Research Lab (HCR Lab)’s main research area is data-driven security which is based on machine learning and data mining technology to extract and learn useful knowledge from massive data. Especially, HCR Lab has its unique and valuable dataset collected from real-world service, for example, online game service data, mobile payment and e-commerce transaction data, car-driving and attack data. HCR Lab is continuously contributing to the data-driven security field by sharing this dataset to the public. One of HCR Lab’s contributions is holding and maintaining Information Security R&D Data challenge (http://datachallenge.kr/) from 2017.
HCR Lab’s research items in detail are as follows. First, HCR Lab conducts data mining and machine learning technology to information security field. First, HCR Lab’s main research focuses on online game bot detection and GFGs (Gold-Farming Groups) detection; HCR Lab is one of the best research group in this field, in the world. Secondly, based on CAN traffic data analysis, HCR Lab develops intrusion detection system (IDS) for automotive. HCR Lab is the only research group which has real vehicle driving and attack dataset in the world. Also, HCR Lab recently becomes an editor of ITSSEC-4 of ITU-T SG17 which is working on the international standardization of automobile security. Third, HCR Lab develops fraud detection system (FDS) for detecting suspicious financial transactions and mobile payment transactions. Fourth, HCR Lab developed Cyber-Genome System which can build cyber threat intelligence (CTI) from malicious code profiling, hacker profiling and incident case profiling based on large-scale data analysis and security visualization techniques.
We are actively doing international joint research and industry-academia cooperation research. Our recent results are published in top conferences and journals such as WWW (Web Conference), NDSS, IEEE Trans. on Information Forensics and Security.
Hacking and Countermeasure Research Lab (HCR Lab)’s main research area is data-driven security which is based on machine learning and data mining technology to extract and learn useful knowledge from massive data. Especially, HCR Lab has its unique and valuable dataset collected from real-world service, for example, online game service data, mobile payment and e-commerce transaction data, car-driving and attack data. HCR Lab is continuously contributing to the data-driven security field by sharing this dataset to the public. One of HCR Lab’s contributions is holding and maintaining Information Security R&D Data challenge (http://datachallenge.kr/) from 2017.
HCR Lab’s research items in detail are as follows. First, HCR Lab conducts data mining and machine learning technology to information security field. First, HCR Lab’s main research focuses on online game bot detection and GFGs (Gold-Farming Groups) detection; HCR Lab is one of the best research group in this field, in the world. Secondly, based on CAN traffic data analysis, HCR Lab develops intrusion detection system (IDS) for automotive. HCR Lab is the only research group which has real vehicle driving and attack dataset in the world. Also, HCR Lab recently becomes an editor of ITSSEC-4 of ITU-T SG17 which is working on the international standardization of automobile security. Third, HCR Lab develops fraud detection system (FDS) for detecting suspicious financial transactions and mobile payment transactions. Fourth, HCR Lab developed Cyber-Genome System which can build cyber threat intelligence (CTI) from malicious code profiling, hacker profiling and incident case profiling based on large-scale data analysis and security visualization techniques.
We are actively doing international joint research and industry-academia cooperation research. Our recent results are published in top conferences and journals such as WWW (Web Conference), NDSS, IEEE Trans. on Information Forensics and Security.
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