• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1205-1212
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• 2022

Cyber threat targeting ICS (Industrial Control System) has indicated drastic increases over the past decade and Cyber Incident in Critical Infrastructure such as Energy, Gas Terminal and Petrochemical industries can lead to disaster-level accidents including casualties and large-scale fires. In order to effectively respond to cyber attacks targeting ICS, a multi-layered defense-in-depth strategy considering Control System Architecture is necessary. In particular, the centralized security log system integrating OT (Operational Technology) and IT (Information Technology) plays an important role in the ICS incident response plan. The paper suggests the way of implementing centralized security log system that collects security events and logs using OPC Protocol from Level 0 to Level 5 based on IEC62443 Purdue Model to integrate ICS security logs with SIEM (Security Information Event Management) operated in IT environment.

• 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 Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.263-279
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• 2024

With the increasing trend of Cloud migration, security threats in the Cloud computing environment have also experienced a significant increase. Consequently, the importance of efficient incident investigation through log data analysis is being emphasized. In Cloud environments, the diversity of services and ease of resource creation generate a large volume of log data. Difficulties remain in determining which events to investigate when an incident occurs, and examining all the extensive log data requires considerable time and effort. Therefore, a systematic approach for efficient data investigation is necessary. CloudTrail, the Amazon Web Services(AWS) logging service, collects logs of all API call events occurring in an account. However, CloudTrail lacks insights into which logs to analyze in the event of an incident. This paper proposes an automated analysis framework that integrates Cloud Matrix and event information for efficient incident investigation. The framework enables simultaneous examination of user behavior log events, event frequency, and attack information. We believe the proposed framework contributes to Cloud incident investigations by efficiently identifying critical events based on the ATT&CK Framework.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4909-4926
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• 2020

Cyberattacks penetrate the server and perform various malicious acts such as stealing confidential information, destroying systems, and exposing personal information. To achieve this, attackers perform various malicious actions by infecting endpoints and accessing the internal network. However, the current countermeasures are only anti-viruses that operate in a signature or pattern manner, allowing initial unknown attacks. Endpoint Detection and Response (EDR) technology is focused on providing visibility, and strong countermeasures are lacking. If you fail to respond to the initial attack, it is difficult to respond additionally because malicious behavior like Advanced Persistent Threat (APT) attack does not occur immediately, but occurs over a long period of time. In this paper, we propose a technique that detects an unknown attack using an event log without prior knowledge, although the initial response failed with anti-virus. The proposed technology uses a combination of AutoEncoder and 1D CNN (1-Dimention Convolutional Neural Network) based on semi-supervised learning. The experiment trained a dataset collected over a month in a real-world commercial endpoint environment, and tested the data collected over the next month. As a result of the experiment, 37 unknown attacks were detected in the event log collected for one month in the actual commercial endpoint environment, and 26 of them were verified as malicious through VirusTotal (VT). In the future, it is expected that the proposed model will be applied to EDR technology to form a secure endpoint environment and reduce time and labor costs to effectively detect unknown attacks.

• Convergence Security Journal
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• v.2 no.2
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• pp.109-121
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• 2002

As the development of information technology and thus the growth of security incidents, there has been increasing demand on developing a system for centralized security management, also known as Enterprise Security Management(ESM), uniting functions of various security systems such as firewall, intrusion detection system, virtual private network and so on. Unfortunately, however, developers have been suffering with a lack of related standard. Although ISTF recently announced firewall system and intrusion detection system log format, it still needs for truly efficient ESM further development of the related standard including event and control messaging. This paper analyses ISTF standard and further suggests an additional event and control messaging standard for firewall and intrusion detection systems. It is expected that this effort would be helpful for the development of ESM and further related standard.

• Smart Media Journal
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• v.7 no.4
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• pp.70-78
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• 2018

Current trends in information system have led many companies to adopt security solutions. However, even with a large budget, they cannot function properly without proper security monitoring that manages them. Security monitoring necessitates a quick response in the event of a problem, and it is needed to design appropriate visualization dashboards for monitoring purposes so that necessary information can be delivered quickly. This paper shows how to visualize a security log using the open source program Elastic Stack and demonstrates that the proposed method is suitable for network security monitoring by implementing it as a appropriate dashboard for monitoring purposes. We confirmed that the dashboard was effectively exploited for the analysis of abnormal traffic growth and attack paths.

• 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 Internet Computing and Services
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• v.19 no.6
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• pp.73-82
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• 2018

We often experience complex presence of files within the compute environment. It could be an end-user's desktop environment or a professional part of file management. We would like to suggest one way to manage these different cases of duplicate files. It is a rule-based file management tool, and we want to use it as a tool to consolidate facility management log files. In this paper, we will describe the rule-based file management tools and show examples of how files are managed using them. We are interested in the management of the disaster environment and would like to apply this method to the management of log data related to facilities to be considered in the event of a disaster.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.2
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• pp.369-376
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• 2019

This paper studies desirable form of future e-government in terms of intelligent government research in response to new intelligent cyber security services in the fourth industrial revolution. Also, the strategic planning of the future e-government has been contemplated in terms of the centralization and intellectualization which are significant characteristics of the fourth industrial revolution. The new system construction which is applied with security analysis technology using big data through advanced relationship analysis is suggested in the paper. The establishment of the system, such as SIEM(Security Information & Event Management), which anticipatively detects security threat by using log information through big data analysis is suggested in the paper. Once the suggested system is materialized, it will be possible to expand big data object, allow centralization in terms of e-government security in the fourth industrial revolution, boost data process, speed and follow-up response, which allows the system to function anticipatively.

• The Journal of Society for e-Business Studies
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• v.23 no.4
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• pp.137-152
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• 2018

It is a measure to overcome limitations that occur in the activity of detecting and blocking abnormal information leakage activity by collecting the activity log generated by the security solution to detect the leakage of existing financial information and analyzing it by pattern analysis. First, it monitors real-time execution programs in PC that are used as information leakage path (read from the outside, save to the outside, transfer to the outside, etc.) in the PC. Second, it determines whether it is a normal controlled exception control circumvention by interacting with the related security control process at the time the program is executed. Finally, we propose a risk management model that can control the risk of financial information leakage through the process procedure created on the basis of scenario.