• Convergence Security Journal
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• v.16 no.7
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• pp.101-111
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• 2016

The recent cyber threats are becoming real threats to our lives. This gloomy situation from cyber threats necessarily demands the establishment of the cyber threat information sharing system between the public and private area. Key countries, like the US, Japan and the UK, are stabilizing the cyber threat information sharing systems by founding exclusive organizations for sharing information and setting up and implementing relevant measures. In this thesis, I would like to propose the model for cyber threat information sharing in order to cope efficiently with the ever-intensifying cyber threats. My model would include key elements for the efficient information sharing, such as the clear designation of main operator of information sharing system, the management of collaboration system between the public and private sector, the build-up of the integrated and automated system and the supplementation of legal system including the grant of privilege, and so on.

• Review of KIISC
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• v.26 no.6
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• pp.42-50
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• 2016

Critical infrastructure (CI) such as the electrical grid, transportation systems and water resource systems are controlled by Industrial Control and SCADA (Supervisory Control and Data Acquisition) networks. During the last few years, cyber attackers have increasingly targeted such CI systems. This is of great concern because successful attacks have wide ranging impact and can cause widespread destruction and loss of life. As a result, there is a critical requirement to develop enhanced algorithms and tools to detect cyber threats for SCADA networks. Such tools have key differences with the tools utilized to detect cyber threats in regular IT networks. This paper discusses key factors which differentiate network security for SCADA networks versus regular IT networks. The paper also presents various approaches used for SCADA security and some of the advancements in the area.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.3
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• pp.639-648
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• 2015

SInce 2000, Instrumentation and Control(I&C) systems of Nuclear Power Plant(NPP) based on analog technology began to be applied to the digital technology. NPPs under construction in the country with domestic APR1400 I&C system, most devices were digitalized. Cyber security of NPP I&C systems has emerged as an important issue because digital devices compared to the existing analog equipment are vulnerable to cyber attacks. In this paper, We proposed the risk rating process of cyber security threats in NPP I&C system and applied the proposed process to the Reactor Protection System(RPS) developed through Korea Nuclear Instrumentation & Control System(KINCS) project for evaluating the risk of cyber security threats.

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.64-72
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• 2024

In recent times cyber attackers can use Artificial Intelligence (AI) to boost the sophistication and scope of attacks. On the defense side, AI is used to enhance defense plans, to boost the robustness, flexibility, and efficiency of defense systems, which means adapting to environmental changes to reduce impacts. With increased developments in the field of information and communication technologies, various exploits occur as a danger sign to cyber security and these exploitations are changing rapidly. Cyber criminals use new, sophisticated tactics to boost their attack speed and size. Consequently, there is a need for more flexible, adaptable and strong cyber defense systems that can identify a wide range of threats in real-time. In recent years, the adoption of AI approaches has increased and maintained a vital role in the detection and prevention of cyber threats. In this paper, an Ensemble Deep Restricted Boltzmann Machine (EDRBM) is developed for the classification of cybersecurity threats in case of a large-scale network environment. The EDRBM acts as a classification model that enables the classification of malicious flowsets from the largescale network. The simulation is conducted to test the efficacy of the proposed EDRBM under various malware attacks. The simulation results show that the proposed method achieves higher classification rate in classifying the malware in the flowsets i.e., malicious flowsets than other methods.

• Convergence Security Journal
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• v.24 no.2
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• pp.9-17
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• 2024

This paper examines the security threats to enterprise Generative Artificial Intelligence systems and proposes countermeasures. As AI systems handle vast amounts of data to gain a competitive edge, security threats targeting AI systems are rapidly increasing. Since AI security threats have distinct characteristics compared to traditional human-oriented cybersecurity threats, establishing an AI-specific response system is urgent. This study analyzes the importance of AI system security, identifies key threat factors, and suggests technical and managerial countermeasures. Firstly, it proposes strengthening the security of IT infrastructure where AI systems operate and enhancing AI model robustness by utilizing defensive techniques such as adversarial learning and model quantization. Additionally, it presents an AI security system design that detects anomalies in AI query-response processes to identify insider threats. Furthermore, it emphasizes the establishment of change control and audit frameworks to prevent AI model leakage by adopting the cyber kill chain concept. As AI technology evolves rapidly, by focusing on AI model and data security, insider threat detection, and professional workforce development, companies can improve their digital competitiveness through secure and reliable AI utilization.

• Convergence Security Journal
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• v.16 no.3_2
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• pp.33-42
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• 2016

While evolving information-oriented society provides a lot of benefits to the human life, new types of threats have been increasing. Particularly, cyber terrorism, happen on the network that is composed of a computer system and information communication network, and the mean and scale of damage has reached a serious level. In other words, it is hard to locate cyber terror since it occurs in the virtual space, not in the real world, so identifying "Who is attacking?" (Non-visibility, non-formulas), or "Where the attack takes place?" (trans-nation) are hard. Hackers, individuals or even a small group of people, who carried out the cyber terror are posing new threats that could intimidate national security and the pace and magnitude of threats keep evolving. Scale and capability of North Korea's cyber terrorism are assessed as world-class level. Recently, North Korea is focusing on strengthen their cyber terrorism force. So improving a response system for cyber terror is a key necessity as North Korea's has emerged as a direct threat to South Korean security. Therefore, Korea has to redeem both legal and institutional systems immediately to perform as a unified control tower for preemptive response to cyber terrors arise from North Korea and neighboring countries.

• Journal of the Korea Society of Computer and Information
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• v.25 no.8
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• pp.39-45
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• 2020

Despite the increasing interest in cyber security in recent years, the emergence of new technologies has led to a shortage of professional personnel to efficiently perform the cyber security. Although various methods such as cyber rage are being used to cultivate cyber security experts, there are problems of limitation of virtual training system, scenario-based practice content development and operation, unit content-oriented development, and lack of consideration of learner level. In this paper, we develop a fuzzy rule-based user-customized training scenario automatic generation system for improving user's ability to respond to infringement. The proposed system creates and provides scenarios based on advanced persistent threats according to fuzzy rules. Thus, the proposed system can improve the trainee's ability to respond to the bed through the generated scenario.

• Journal of Digital Convergence
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• v.17 no.8
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• pp.221-228
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• 2019

The importance of security for virtualization products has been increased with the activation policy of cloud computing and it is necessary to analyze cyber security threats and develop security requirements for virtualization products to provide with more secure cloud environments. This paper is a preliminary study with the purpose of developing security functional requirements through analyzing security features and cyber security threats as well as comparison of foreign countries' cases for virtualization products. To do this, the paper compares evaluation schemes for virtualization products in US and UK foreign countries, and analyzes the cyber security threats, security objectives and security requirements in both countries. Furthermore, it proposes the essential checking items and processes for developing security functional requirements about security features of virtualization products to contribute to its more secure development and the establishment of related security evaluation standards.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1167-1187
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• 2020

We are facing the situation where cyber threats such as hacking, malware, data leakage, and theft, become an important issue in the perspective of personal daily life, business, and national security. Although various efforts are being made to response to the cyber threats in the national and industrial sectors, the problems such as the industry-academia skill-gap, shortage of cybersecurity professionals are still serious. Thus, in order to overcome the skill-gap and shortage problems, we propose a Cybersecurity technical response Job Competency(CtrJC) framework by adopting the concept of cybersecurity personnel's job competency. As a sample use-case study, we implement the CtrJC against to personals who are charged in realtime cybersecurity response, which is an important job at the national and organization level, and verify the our framework's effects. We implement a sample model, which is a CtrJC against to realtime cyber threats (We call it as CtrJC-R), and study the verification and validation of the implemented model.

• 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.