• Smart Media Journal
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• v.6 no.4
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• pp.41-49
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• 2017

According to the occurrence of many security incidents, the SOC(Security Operation Center) and SIEM(Security Information & Event Management) are concentrated recently. The various studies and commercial products of the information security industry are being released. As reflected in this situation, NIST in the US is publishing and revising the document about the Cybersecurity Framework. In this study, we investigated the NIST's Cyberseurity Framework, trends in SOC and SIEM security technologies and solutions, and also introduce the open source Apache Metron of a real-time Bigdata security tool.

• Convergence Security Journal
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• v.24 no.2
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• pp.39-45
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• 2024

The purpose of security control in the public sector is to secure the safety of administrative services for the public by preventing resource loss or information infringement in information systems and information and communication networks. The security control system is a process that performs real-time detection, analysis, response, and reporting through system vulnerability analysis and security system detection pattern optimization. This study aims to objectively identify the current situation of the mismatch between the supply and demand of cyber security control centers currently in operation and specialized security control companies that can be entrusted to operate them, and to derive and propose practical and institutional improvement measures. Considering that the operation of security control centers in the public sector is expected to increase in the future, research on the practical supplementation required for the operation process of security control centers and the improvement of the designation system of security control specialized organizations has fundamental and timely significance, and it is an area that requires continuous research in terms of strategic industrialization.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.4
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• pp.587-596
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• 2024

Cyber Attack and Cyber Threat are getting confused and evolved. Therefore, using AI(Artificial Intelligence), which is the most important technology in Fourth Industry Revolution, to build a Cyber Threat Detection System is getting important. Especially, Government's SOC(Security Operation Center) is highly interested in using AI to build SOAR(Security Orchestration, Automation and Response) Solution to predict and build CTI(Cyber Threat Intelligence). In this thesis, We introduce the Cyber Threat Detection System by analyzing Network Traffic and Web Application Firewall(WAF) Log data. Additionally, we apply the well-known TF-IDF(Term Frequency-Inverse Document Frequency) method and AutoML technology to classify Web traffic attack type.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.3
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• pp.465-479
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• 2020

Regardless of the domestic and foreign governments/companies, SOC (Security Operation Center) has operated 24 hours a day for the entire year to ensure the security for their IT infrastructures. However, almost all SOCs have a critical limitation by nature, caused from heavily depending on the manual analysis of human agents with the text-based monitoring architecture. Even though, in order to overcome the drawback, technologies for a comprehensive visualization against complex cyber threats have been studying, most of them are inappropriate for the security monitoring in large-scale networks. In this paper, to solve the problem, we propose a novel visual approach for intuitive threats monitoring b detecting suspicious IP address, which is an ultimate challenge in cyber security monitoring. The approach particularly makes it possible to detect, trace and analysis of suspicious IPs statistically in real-time manner. As a result, the system implemented by the proposed method is suitably applied and utilized to the real-would environment. Moreover, the usability of the approach is verified by successful detecting and analyzing various attack IPs.