• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.39-49
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• 2014

Cyber threats on the Internet are tremendously increasing and their techniques are also evolving constantly. Intrusion Detection System (IDS) is one of the powerful solutions for detecting and analyzing the cyber attacks in realtime. Most organizations deploy it into their networks and operate it for security monitoring and response service. However, IDS has a fatal problem in that it raises a large number of alerts and most of them are false positives. In order to cope with this problem, many approaches have been proposed for the purpose of automatically identifying whether the IDS alerts are caused by real attacks or not. In this paper, we present an alert verification method based on correlation analysis between vulnerability inspection results for real systems that should be protected and the IDS alerts. In addition, we carry out practical experiments to demonstrate the effectiveness of the proposed verification method using two types of real data, i.e., the IDS alerts and the vulnerability inspection results.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.3
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• pp.507-522
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• 2014

Domestic CERTs are carrying out monitoring and response against cyber attacks using security devices(e.g., IDS, TMS, etc) based on signatures. Particularly, in case of public and research institutes, about 30 security monitoring and response centers are being operated under National Cyber Security Center(NCSC) of National Intelligence Service(NIS). They are mainly using Threat Management System(TMS) for providing security monitoring and response service. Since TMS raises a large amount of security events and most of them are not related to real cyber attacks, security analyst who carries out the security monitoring and response suffers from analyzing all the TMS events and finding out real cyber attacks from them. Also, since the security monitoring and response tasks depend on security analyst's know-how, there is a fatal problem in that they tend to focus on analyzing specific security events, so that it is unable to analyze and respond unknown cyber attacks. Therefore, we propose automated verification method of security events based on their empirical analysis to improve performance of security monitoring and response.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.6
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• pp.1489-1497
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• 2018

Web application services have diversified. At the same time, research on intrusion detection is continuing due to the surge of cyber threats. Also, As a single-defense system evolves into multi-level security, we are responding to specific intrusions by correlating security events that have become vast. However, it is difficult to check the OS, service, web application type and version of the target system in real time, and intrusion detection events occurring in network-based security devices can not confirm vulnerability of the target system and success of the attack A blind spot can occur for threats that are not analyzed for problems and associativity. In this paper, we propose the validation of effectiveness for intrusion detection events using TF-IDF. The proposed scheme extracts the response traffics by mapping the response of the target system corresponding to the attack. Then, Response traffics are divided into lines and weights each line with an TF-IDF weight. we checked the valid intrusion detection events by sequentially examining the lines with high weights.

• Journal of the Korea Society of Computer and Information
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• v.19 no.7
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• pp.47-57
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• 2014

In order to publicly notify the information security (Internet or Cyber) threat level, the security companies have developed the Threat Meters. As the physical security devices are getting more intelligent and can be monitored and managed through networks, we propose a physical security threat meter (PSTM) to determine the current threat level of physical security; that is a very similar compared with the one of information security. For this purpose, we investigate and prioritize the physical security events, and consider the impact of temporal correlation among multiple security events. We also present how to determine the threshold values of threat levels, and then propose a practical PSTM using the threshold based decision. In particular, we show that the proposed scheme is fully implementable through showing the block diagram in detail and the whole implementation processes with the access controller and CCTV+video analyzer system. Finally the simulation results show that the proposed PSTM works perfectly under some test scenarios.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06d
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• pp.66-70
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• 2008

진화되고 위협적인 사이버공격 및 피해가 증가함에 따라 기업이나 기관의 정보보호에 대한 책임도 증가하게 되었다. 이에 종합적인 컴퓨터 범죄 재현과 정확한 침입경로 및 피해규모, 정보의 신뢰성을 파악하기 위한 컴퓨터 포렌식에 대한 연구가 활발해 지고 있다. 이에 대부분의 기업이나 조직에서 이기종의 보안장비에서 발생하는 다량의 경보와 이벤트를 효과적으로 수집, 통합하고 상호연관분석 할 수 있는 통합보안관리시스템(ESM)을 도입하여 운영하고 있으나 많은 경보발생으로 인해 적절한 판단이나 분석 및 효율적인 대응이 이루어지고 있지 않다. 이에 본 논문에서는 수집되는 증거의 범위를 재 정의하고, 이벤트 상관분석을 통해 발생된 침해경보에 대해 경보검증을 적용하여 경보의 오탐율을 감소시켰으며, 검증된 경보에 대해서 신속히 분석 및 대응이 이루어지는 포렌식 모델을 제안한다. 이를 통해 오탐율 감소는 물론 신속하고 신뢰성 있는 탐지 및 침해 분석이 가능하다.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.11a
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• pp.1059-1062
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• 2005

보안위협은 갈수록 심각해지고 다양한 정보보호시스템들을 통합하는 통합보안관리시스템에 관한 연구 개발도 활발히 진행 중이다. 이기종 정보보호시스템에서 발생하는 다량의 경보와 이벤트를 효과적으로 수집, 통합하고 상호연관 분석할 수 있는 방법이 절실하다. 현재 연구되고 있는 상호연관분석 방법들에 대해서 조사 분류하고 각 분류별로 장단점을 분석하여 이기종 통합보안관리에 적합한 상호연관분석 방법을 제안한다. 보안 경보 검증과정과 분산화된 경보처리방법으로 실시간 상호연관분석이 가능하도록 설계하였다.

• Convergence Security Journal
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• v.21 no.3
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• pp.13-23
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• 2021

The attacker's techniques and tools are becoming intelligent and sophisticated. Existing Anti-Virus cannot prevent security accident. So the security threats on the endpoint should also be considered. Recently, EDR security solutions to protect endpoints have emerged, but they focus on visibility. There is still a lack of detection and responsiveness. In this paper, we use real-world EDR event logs to aggregate knowledge-based MITRE ATT&CK and autoencoder-based anomaly detection techniques to detect anomalies in order to screen effective analysis and analysis targets from a security manager perspective. After that, detected anomaly attack signs show the security manager an alarm along with log information and can be connected to legacy systems. The experiment detected EDR event logs for 5 days, and verified them with hybrid analysis search. Therefore, it is expected to produce results on when, which IPs and processes is suspected based on the EDR event log and create a secure endpoint environment through measures on the suspicious IP/Process.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.1
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• pp.382-389
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• 2012

The fabricated report attack will not only cause false alarms that waste real-world response efforts such as sending response teams to the event location, but also drains the finite amount of energy in a wireless sensor network. In this paper, we propose a probabilistic filtering method for sensor network security (PFSS) to deal with filtering for the fabricated report. On the basis of filtering scheme, PFSS combines cluster-based organization and probabilistic verification node assignment using distance of from cluster head to base station for energy efficiency and hot spot problem. Through both analysis and simulation, we demonstrate that PFSS could achieve efficient protection against fabricated report attack while maintaining a sufficiently high filtering power.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.2
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• pp.385-395
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• 2018

With the development of Internet, cyber attack has become a major threat. To detect cyber attacks, intrusion detection system(IDS) has been widely deployed. But IDS has a critical weakness which is that it generates a large number of false alarms. One of the promising techniques that reduce the false alarms in real time is machine learning. However, there are problems that must be solved to use machine learning. So, many machine learning approaches have been applied to this field. But so far, researchers have not focused on features. Despite the features of IDS alerts are important for performance of model, the approach to feature is ignored. In this paper, we propose new feature set which can improve the performance of model and can be extracted from a single alarm. New features are motivated from security analyst's know-how. We trained and tested the proposed model applied new feature set with real IDS alerts. Experimental results indicate the proposed model can achieve better accuracy and false positive rate than SVM model with ordinary features.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2003.12a
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• pp.91-96
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• 2003

업무 편의성 요구 증가와 웹 서비스의 발전으로 웹 기반 원격근무 업무 시스템이 증가하고 있는 반면, 웹 취약점의 확산과 개방형 환경으로 인해 잠재적 위협이 증가되고 있다. 이러한 위협에 적절히 대응하기 위해서는 개발 단계 전반에서 보안 요소를 고려하여 안전한 업무 시스템을 구축해야 한다. 이를 위해 본 논문에서는 업무 시스템이 요구하는 보안 수준에 부합하는 보안 목표를 설정하고, 요구 보안 수준을 충족할 수 있도록 전체 개발 프로세스 상의 보안 관리 활동을 정의한다. 또한, 신원 인증 및 접근제어, 세션 관리, 이벤트 로깅, 데이터 검증, 알려진 취약점 대응, 그리고 프라이버시 보호와 같은 보안 요소들을 분석하여 시스템의 안전한 구축 방법을 제시한다.