• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.6
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• pp.797-805
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• 2019

Threats targeting cyberspace are becoming more intelligent and increasing day by day. To cope with such cyber threats, it is essential to improve the coping ability of system security officers. In this paper, we propose a simulated threat generator that automatically generates cyber threats for cyber defense training. The proposed Simulated Threat Generator is designed with MITRE ATT & CK(Adversarial Tactics, Techniques and Common Knowledge) framework to easily add an evolving cyber threat and select the next threat based on the threat execution result.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.99-110
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• 2023

This study proposed a classification of malicious network traffic using the cyber threat framework(Mitre ATT&CK) and machine learning to solve the real-time traffic detection problems faced by current security monitoring systems. We applied a network traffic dataset called UNSW-NB15 to the Mitre ATT&CK framework to transform the label and generate the final dataset through rare class processing. After learning several boosting-based ensemble models using the generated final dataset, we demonstrated how these ensemble models classify network traffic using various performance metrics. Based on the F-1 score, we showed that XGBoost with no rare class processing is the best in the multi-class traffic environment. We recognized that machine learning ensemble models through Mitre ATT&CK label conversion and oversampling processing have differences over existing studies, but have limitations due to (1) the inability to match perfectly when converting between existing datasets and Mitre ATT&CK labels and (2) the presence of excessive sparse classes. Nevertheless, Catboost with B-SMOTE achieved the classification accuracy of 0.9526, which is expected to be able to automatically detect normal/abnormal network traffic.

• Convergence Security Journal
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• v.23 no.4
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• pp.33-41
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• 2023

In recent years, advanced persistent threat (APT) attack organizations have exploited various vulnerabilities and attack techniques to target companies and institutions with national core technologies, distributing ransomware and demanding payment, stealing nationally important industrial secrets and distributing them on the black market (dark web), selling them to third countries, or using them to close the technology gap, requiring national-level security preparations. In this paper, we analyze the attack methods of attack organizations such as Kimsuky and Lazarus that caused industrial secrets leakage damage through APT attacks in Korea using the MITRE ATT&CK framework, and derive 26 cybersecurity-related administrative, physical, and technical security requirements that a company's security system should be equipped with. We also proposed a security framework and system configuration plan to utilize the security requirements in actual field. The security requirements presented in this paper provide practical methods and frameworks for security system developers and operators to utilize in security work to prevent leakage of corporate industrial secrets. In the future, it is necessary to analyze the advanced and intelligent attacks of various APT attack groups based on this paper and further research on related security measures.

• Convergence Security Journal
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• v.23 no.5
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• pp.209-221
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• 2023

Due to the rapid spread of the COVID-19 virus in December 2019, the working environment was rapidly converted to telecommuting. However, since the defense industry is an organization that handles technology related to the military, the network separation policy is applied, so there are many restrictions on the application of telecommuting. Telecommuting is a global change and an urgent task considering the rapidly changing environment in the future. Currently, in order for defense companies to implement telecommuting, VPN, VDI, and network interlocking systems must be applied as essential elements. Eventually, some contact points will inevitably occur, which will increase security vulnerabilities, and strong security management is important. Therefore, in this paper, attack types are selected and threats are analyzed based on the attack tactics of the MITER ATT&CK Framework, which is periodically announced by MITER in the US to systematically detect and respond to cyber attacks. Then, by applying STRIDE threat modeling, security threats are classified and specific security requirements are presented.

• Journal of the Korea Society of Computer and Information
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• v.25 no.9
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• pp.71-80
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• 2020

As societies become hyperconnected, we need more cyber security experts. To this end, in this paper, based on the analysis results of the real world cyber attacks and the MITRE ATT&CK framework, we developed CyTEA that can model cyber threats and generate simulated cyber threats in a cyber security training system. In order to confirm whether the simulated cyber threat has the effectiveness of the actual cyber threat level, the simulation level was examined based on procedural, environmental, and consequential similarities. in addition, it was confirmed that the actual defense training using cyber simulation threats is the same as the expected defense training when using real cyber threats in the cyber security training system.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.1
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• pp.99-107
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• 2022

In the current technological society, where various technologies are converged into one and being transformed into new technologies, new cyber attacks are being made just as they keep pace with the changes in society. In particular, due to the convergence of various attacks into one, it is difficult to protect the system with only the existing security system. A lot of information is being generated to respond to such cyber attacks. However, recklessly generated vulnerability information can induce confusion by providing unnecessary information to administrators. Therefore, this paper proposes a mechanism to assist in the analysis of emerging cyberattack convergence technologies by providing differentiated vulnerability information to managers by learning documents using deep learning-based language learning models, extracting vulnerability information and classifying them according to the MITRE ATT&CK framework.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.87-96
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• 2023

As the number of security vulnerabilities increases yearly, security threats continue to occur, and the vulnerability risk is also important. We devise a security threat score calculation reflecting trends to determine the risk of security vulnerabilities. The three stages considered key elements such as attack type, supplier, vulnerability trend, and current attack methods and techniques. First, it reflects the results of checking the relevance of the attack type, supplier, and CVE. Secondly, it considers the characteristics of the topic group and CVE identified through the LDA algorithm by the Jaccard similarity technique. Third, the latest version of the MITER ATT&CK framework attack method, technology trend, and relevance between CVE are considered. We used the data within overseas sites provide reliable security information to review the usability of the proposed final formula CTRS. The scoring formula makes it possible to fast patch and respond to related information by identifying vulnerabilities with high relevance and risk only with some particular phrase.