• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.5
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• pp.537-544
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• 2021

Cyber threats can bypass existing cyber-protection systems and are rapidly developing by exploiting new technologies such as artificial intelligence. In order to respond to such cyber threats, it is important to improve the ability to detect unknown cyber threats by correlating heterogeneous cyber protection systems. In this paper, to enhance cyber-attack response capabilities, we proposed command and control that enables rapid decision-making and response before the attack objectives are achieved, using Lockheed Martin's cyber kill chain and MITRE ATT&CK to analyze the purpose and intention of the attacker.

• Convergence Security Journal
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• v.21 no.1
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• pp.63-72
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• 2021

The hospital biomedical engineering team is responsible for establishing and regulating the Medical Device Management Program (MEMP) to ensure that medical devices are safe and reliable. As technology advances, medical devices such as artificial intelligence and precision medicine are developing into a form that allows connection between objects anytime, anywhere, and as various technologies converge, internal and external security threats continue to increase. In this paper, we present a study of the Medical Device Management Program (Secure-MEMP) method, considering that the security threat of medical devices continues to increase due to advances in technology.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.286-289
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• 2020

정보통신 기술의 발달로 무분별한 사이버 공격에 노출되어 있기 때문에 정보보안의 기술이 중요해지고 있다. 이중 침입 탐지 시스템은 방화벽과 더불어 시스템 및 네트워크 보안을 위한 대표적인 수단으로, 현재까지 네트워크 기반인 NIDS와 호스트 기반인 HIDS에 대한 많은 연구가 이루어졌다. 이러한 침입 탐지에 대한 CTI(Cyber Threat Intelligence)를 공유하기 위해 다양한 CTI 프레임워크를 사용하여 CTI 정보를 공유하는 연구가 진행되고 있다. 이에 본 논문에서는 CVE기반의 OpenIOC와 Snort 및 OSSEC에서 생성된 Raw Data를 결합하여 새로운 CTI 프레임 워크를 제안한다. 제안된 시스템을 테스트하기 위해서는 CVE 분석을 기반으로한 Kali Linux로 공격을 진행한다, 이를 통해 생성된 데이터는 시간이 지남에 따라 축적된 데이터를 저장 및 검색을 위해 대규모 분산 처리 시스템과도 결합이 필요할 것으로 예상되며 추후 딥러닝 기술을 활용하면 지능형 지속 위협을 분석하는데 용이할 것으로 예상된다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.187-189
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• 2023

IoT(Internet of Things), 빅데이터, AI(Artificial Intelligence), 클라우드와 같은 ICT(Information and Communications Technology) 기술이 발전함에 따라 ICT와 제조기술이 융합된 스마트팩토리가 발전하고 있다. 이는 2개의 영역과 5개의 계층으로 구성되어 기타 환경들과 상이한 구조를 가지고 있으며, 각 영역·계층별 발생 가능한 보안위협도 상이하다. 또한, 각 영역과 계층이 연결됨에 따라 발생 가능한 보안위협이 증가하고 있으며, 이에 대한 효율적인 대응을 위하여 스마트팩토리 영역·계층별 환경을 고려한 대응체계 마련이 필요한 실정이다. 따라서, 본 논문에서는 스마트팩토리 영역·계층별 발생 가능한 보안위협을 분석하고, 이에 대응하기 위한 대응체계 도출 기법을 제안한다.

• Journal of the Korea Institute of Building Construction
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• v.16 no.4
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• pp.341-348
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• 2016

The aim of this study is to suggest design requirements on the military barriers which are installed to reduce critical damage on protective facilities against sudden pin-point attacks caused by North Korean artilleries. For this purpose, site investigation and review of design drawings associated with barriers built in the contact areas are conducted. With identified data concerning barriers, the geometric modeling, which is used in the structural analysis, is performed. And then, the possible threat of North Korea is determined based on intelligence preparation of battlefields. Once the structural modeling and threat analysis are completed, structural damage on barriers and protective facilities are assessed in terms of impact, penetration, scabbing, and blast pressure effects. According to the analysis results, the thickness of barriers should be 450mm at least and current established barriers need to be structurally reinforced via sectional enlargement.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.1087-1098
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• 2023

The rapid advancement of artificial intelligence (AI) technology has led to its proactive utilization across various fields. However, this widespread adoption of AI-based systems has raised concerns about the increasing threat of attacks on these systems. In particular, deep neural networks, commonly used in deep learning, have been found vulnerable to adversarial attacks that intentionally manipulate input data to induce model errors. In this study, we propose a method to protect image classification models from visually imperceptible One-Pixel attacks, where only a single pixel is altered in an image. The proposed defense technique utilizes an autoencoder model to remove potential threat elements from input images before forwarding them to the classification model. Experimental results, using the CIFAR-10 dataset, demonstrate that the autoencoder-based defense approach significantly improves the robustness of pretrained image classification models against One-Pixel attacks, with an average defense rate enhancement of 81.2%, all without the need for modifications to the existing models.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.2
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• pp.471-484
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• 2018

Recently, cyber threats are frequently occurring in ICS(industrial control systems) of government agencies, infrastructure, and manufacturing companies. In order to cope with such cyber threats, it is necessary to apply CTI to ICS. For this purpose, a security information collection system is needed. However, it is difficult to install security solution in control devices such as PLC. Therefor, it is difficult to collect security information of ICS. In addition, there is a problem that the security information format generated in various assets is different. Therefore, in this paper, we propose an efficient method to collect ICS security information. We utilize CybOX/STIX/TAXII CTI models that are easy to apply to ICS. Using this model, we designed the formats to collect security information of ICS assets. We created formats for system logs, IDS logs, and EWS application logs of ICS assets using Windows and Linux. In addition, we designed and implemented a security information collection system that reflects the designed formats. This system can be used to apply monitoring system and CTI to future ICS.

• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.201-208
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• 2019

In the phono-sapiens era of the intelligence information society, most business activities are increasingly dependent on networks and information systems. SMEs, which occupy the majority of Korean companies, are increasingly possessing the value and technology of their information assets, and their ability to protect core technologies that are the driving force of corporate growth will be the most important competitiveness of enterprises. Accordingly, the Ministry of Science and ICT and the Korea Internet & Security Agency(KISA) provides a foundation for minimizing the damage from cyber threats such as hacking and information leakage by evaluating the current information protection level of SMEs and enhancing information protection capability by supporting a high level of customized information protection consulting. In this study, we analyze the effectiveness of information protection based on the results of KISA SMEs consulting. In addition, by identifying problems and limitations derived from SMEs information protection consulting results, SMEs should propose measures to improve information security of SMEs that can manage information protection management system more efficiently and effectively.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.2
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• pp.447-463
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• 2022

Artificial Intelligence (AI) technology is a major technology that develops smart ships into autonomous ships in the marine industry. Autonomous ships recognize a situation with the information collected without human judgment which allow them to operate on their own. Existing ship systems, like control systems on land, are not designed for security against cyberattacks. As a result, there are infringements on numerous data collected inside and outside the ship and potential cyber threats to AI technology to be applied to the ship. For the safety of autonomous ships, it is necessary to focus not only on the cybersecurity of the ship system, but also on the cybersecurity of AI technology. In this paper, we analyzed potential cyber threats that could arise in AI technologies to be applied to existing ship systems and autonomous ships, and derived categories that require security risks and the security of autonomous ships. Based on the derived results, it presents future directions for cybersecurity research on autonomous ships and contributes to improving cybersecurity.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.411-425
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• 2023

Today, AI (Artificial Intelligence) technology is widely used in various fields, performing classification and regression tasks according to the purpose of use, and research is also actively progressing. Especially in the field of security, unexpected threats need to be detected, and unsupervised learning-based anomaly detection techniques that can detect threats without adding known threat information to the model training process are promising methods. However, most of the preceding studies that provide interpretability for AI judgments are designed for supervised learning, so it is difficult to apply them to unsupervised learning models with fundamentally different learning methods. In addition, previously researched vision-centered AI mechanism interpretation studies are not suitable for application to the security field that is not expressed in images. Therefore, In this paper, we use a technique that provides interpretability for detected anomalies by searching for and comparing optimization references, which are the source of intrusion attacks. In this paper, based on reference, we propose additional logic to search for data closest to real data. Based on real data, it aims to provide a more intuitive interpretation of anomalies and to promote effective use of an anomaly detection model in the security field.