• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.2
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• pp.60-69
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• 2013

Highlighted by recent security breaches including Google, Western Energy Company, and the Stuxnet infiltration of Iranian nuclear sites, Cyber warfare attacks pose a threat to national and global security. In particular, targeted attacks such as APT exploiting a high degree of stealthiness over a long period, has extended their victims from PCs and enterprise servers to government organizations and critical national infrastructure whereas the existing security measures exhibited limited capabilities in detecting and countermeasuring them. As a solution to fight against such attacks, we designed and implemented a security monitoring system, which shares security information and helps cooperative countermeasure. The proposed security monitoring system collects security event logs from heterogeneous security devices, analyses them, and visualizes the security status using 3D technology. The capability of the proposed system was evaluated and demonstrated throughly by deploying it under real network in a ISP for a week.

• Convergence Security Journal
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• v.6 no.3
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• pp.21-28
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• 2006

Beginning flag security it was limited in Firewall but currently many information security solutions like Anti-virus, IDS, Firewall are come to be many. For efficiently managing different kinds of information security products ESM (Enterprise Security management) are developed and operated. Recently over the integrated security management system, TMS (Threat Management System) is rising in new area of interest. It follows in change of like this information security product and also collection information is being turning out diversification. For managing cyber threats, we have to analysis qualitative information (like vulnerabilities and malware codes, security news) as well as the quantity event logs which are from information security products of past. Information Threats and Vulnerability Auto Collector raises the accuracy of cyber threat judgement and can be utilized to respond the cyber threat which does not occur still by gathering qualitative information as well as quantity information.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.5
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• pp.303-314
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• 2018

In the past few years, government agencies and corporations have succumbed to stealthy, tailored cyberattacks designed to exploit vulnerabilities, disrupt operations and steal valuable information. Security Information and Event Management (SIEM) is useful tool for cyberattacks. SIEM solutions are available in the market but they are too expensive and difficult to use. Then we implemented basic SIEM functions to research and development for future security solutions. We focus on collection, aggregation and analysis of real-time logs from host. This tool allows parsing and search of log data for forensics. Beyond just log management it uses intrusion detection and prioritize of security events inform and support alerting to user. We select Elastic Stack to process and visualization of these security informations. Elastic Stack is a very useful tool for finding information from large data, identifying correlations and creating rich visualizations for monitoring. We suggested using vulnerability check results on our SIEM. We have attacked to the host and got real time user activity for monitoring, alerting and security auditing based this security information management.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.4
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• pp.69-81
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• 2006

The Computer Forensics is a research area that finds the malicious users by collecting and analyzing the intrusion or infringement evidence of computer crimes such as hacking. Many researches about Computer Forensics have been done so far. But those researches have focussed on how to collect the forensic evidence for both analysis and poofs after receiving the intrusion or infringement reports of hosts from computer users or network administrators. In this paper, we describe how to collect the forensic evidence of good quality from observable and protective hosts at the time of infringement occurrence by malicious users. By correlating the event logs of Intrusion Detection Systems(IDSes) and hosts with the configuration information of hosts periodically, we calculate the value of infringement severity that implies the real infringement possibility of the hosts. Based on this severity value, we selectively collect the evidence for proofs at the time of infringement occurrence. As a result, we show that we can minimize the information damage of the evidence for both analysis and proofs, and reduce the amount of data which are used to analyze the degree of infringement severity.

• Journal of Platform Technology
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• v.11 no.3
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• pp.32-44
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• 2023

A blockchain bridge (hereinafter referred to as "bridge") is a service that enables the transfer of assets between blockchains. A bridge accepts virtual assets from users and delivers the same virtual assets to users on other blockchains. Users use bridges because they cannot transfer assets to other blockchains in the usual way because each blockchain environment is independent. Therefore, the movement of assets through bridges is not traceable in the usual way. If a malicious actor moves funds through a bridge, existing asset tracking tools are limited in their ability to trace it. Therefore, this paper proposes a method to obtain information on bridge usage by identifying the structure of the bridge and analyzing the event logs of bridge requests. First, to understand the structure of bridges, we analyzed bridges operating on Ethereum Virtual Machine(EVM) based blockchains. Based on the analysis, we applied the method to arbitrary bridge events. Furthermore, we created an automated tool that continuously collects and stores bridge usage information so that it can be used for actual tracking. We also validated the automated tool and tracking method based on an asset transfer scenario. By extracting the usage information through the tool after using the bridge, we were able to check important information for tracking, such as the sending blockchain, the receiving blockchain, the receiving wallet address, and the type and quantity of tokens transferred. This showed that it is possible to overcome the limitations of tracking asset movements using blockchain bridges.