• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.7
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• pp.830-837
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• 2020

With the rapid development of information and communication technology, information exchange between ships and shore has become faster and more convenient, However, accessing ship information has also become easier and concerns about cyber security attacks are growing. When a ship suffers a cyber-attack, it may cause considerable damage and incurs enormous costs and time to repair. In response to this threat, the maritime industry now demands that a cyber security officer be assigned to each ship to take charge of cyber security management onboard. In order to reduce the damage cause by an attack and to respond effectively, a specialized training course for the ship's cyber security officer is required. The purpose of this study was to present a training course for the position of the ship's cyber security officer, and to highlight the necessity of amending current legislation, To this end, domestic and foreign trends, ship cyber security incident cases, and cyber security training courses were investigated, and based on the results a standard training course for a ship's cyber security of icer was developed. Additionally, recommendations on the related amendments to legislation ware established. The results of the study can be used as basic data to establish future training courses for cyber security officers.

• Convergence Security Journal
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• v.11 no.6
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• pp.53-58
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• 2011

There is increasing use of common commercial operation system and standard PCs to control industrial production systems, and cyber security threat for industrial facilities have emerged as a serious problem. Now these network connected ICS(Industrial Control Systems) stand vulnerable to the same threats that the enterprise information systems have faced and they are exposed to malicious attacks. In particular Stuxnet is a computer worm targeting a specific industrial control system, such as a gas pipeline or power plant and in theory, being able to cause physical damage. In this paper we present an overview of the general configuration and cyber security threats of a SCADA and investigate the attack tree analysis to identify and assess security vulnerabilities in SCADA for the purpose of response to cyber attacks in advance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.1052-1057
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• 2020

With the development of new ICT technology, smart keys for vehicles are terminals with ICT technology. Therefore, when the vehicle and the smart key communicate with RF, a cyber hacking attack is possible. Cyber-attacks on smart keys can pose a threat to vehicle theft and vehicle control. Therefore, it is necessary to study hacking attacks and vulnerabilities of smart keys for autonomous vehicles. In this paper, we analyze the cyber attack case of RF communication for vehicles and smart keys. In addition, a real RF cyber attack on the smart key is performed, and the vulnerability of radio wave replication in the same frequency band is found. In this paper, we analyze the vulnerability of RF communication between vehicles and smart keys, and propose a countermeasure against cyber security. In the future, plans to strengthen cyber attacks and security through the popularization of autonomous vehicles will become basic data to protect human and vehicle safety.

• 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 Institute of Electronics and Information Engineers
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• v.50 no.9
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• pp.92-99
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• 2013

As a recent cyber attack has a characteristic that is intellectual, advanced, and complicated attack against precise purpose and specified object, it becomes extremely hard to recognize or respond when accidents happen. Since a scale of damage is very large, a corresponding system about this situation is urgent in national aspect. Existing data center or integration security framework of computer lab is evaluated to be a behind system when it corresponds to cyber attack. Therefore, this study suggests a better sophisticated next generation convergence security framework in order to prevent from attacks based on advanced persistent threat. Suggested next generation convergence security framework is designed to have preemptive responses possibly against APT attack consisting of five hierarchical steps in domain security layer, domain connection layer, action visibility layer, action control layer and convergence correspondence layer. In domain connection layer suggests security instruction and direction in domain of administration, physical and technical security. Domain security layer have consistency of status information among security domain. A visibility layer of Intellectual attack action consists of data gathering, comparison, decision, lifespan cycle. Action visibility layer is a layer to control visibility action. Lastly, convergence correspond layer suggests a corresponding system of before and after APT attack. An introduction of suggested next generation convergence security framework will execute a better improved security control about continuous, intellectual security threat.

• Convergence Security Journal
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• v.20 no.1
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• pp.15-24
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• 2020

Cyber terror and cyberwarfare are no longer virtual, but real, and as an actual security situation, it is necessary to have new understanding through expanding the concept of war to neutralize not only the other country's military command system, but also the country's main functions such as telecommunications, energy, finance, and transport systems, and it also needs to establish the future development strategy of cyber terror response at the national level. Through analysis of cyberwarfare trends in each country and current status of cyberwarfare in Korea, it will systematically explore the demand of new policy based on laws and systems, including the strategies of cyber security technology development, industry promotion, and manpower training and existing information protection policies. through this, it effectively manages a sustainable national crisis, and it suggests to establish a future strategy for the medium and long term cyber security that can effectively and actively respond to cyberwarfare.

• Review of KIISC
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• v.29 no.6
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• pp.75-80
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• 2019

2018년까지 알려진 표적공격 그룹은 꾸준히 증가하여 현재 155개로 2016년 대비 39개가 증가하였고, 침해사고의 평균 체류시간(dwell-time)은 2016년 172일에서 2018년 204일로 32일이 증가하였다. 점점 다양해지고 심화되고 있는 APT(Advanced Persistent Threat)공격에 대응하기 위하여 국내외 기업들의 사이버 위협 인텔리전스(CTI; Cyber Threat Intelligence) 활용이 증가하고 있는 추세이다. 현재 KISA에서는 글로벌 동향에 발맞춰 CTI를 활용할 수 있는 시스템을 개발 중에 있다. 본 논문에서는 효율적인 CTI 활용을 위한 OSINT(Open Source Intelligence)기반 사이버 위협 정보 수집 및 연관관계 표현 시스템을 소개하고자 한다.

• The Journal of the Korea Contents Association
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• v.20 no.7
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• pp.618-628
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• 2020

The purpose of this paper is to propose a new security orchestration service model by combining various security solutions that have been introduced and operated individually as a basis for cyber security framework. At present, in order to respond to various and intelligent cyber attacks, various single security devices and SIEM and AI solutions that integrate and manage them have been built. In addition, a cyber security framework and a security control center were opened for systematic prevention and response. However, due to the document-oriented cybersecurity framework and limited security personnel, the reality is that it is difficult to escape from the control form of fragmentary infringement response of important detection events of TMS / IPS. To improve these problems, based on the model of this paper, select the targets to be protected through work characteristics and vulnerable asset identification, and then collect logs with SIEM. Based on asset information, we established proactive methods and three detection strategies through threat information. AI and SIEM are used to quickly determine whether an attack has occurred, and an automatic blocking function is linked to the firewall and IPS. In addition, through the automatic learning of TMS / IPS detection events through machine learning supervised learning, we improved the efficiency of control work and established a threat hunting work system centered on big data analysis through machine learning unsupervised learning results.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.2
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• pp.65-73
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• 2014

An overall responding security-centered framework is necessary required for infringement accidents, failures, and cyber threats. On the other hand, the correspondence structures of existing administrative, technical, physical security have weakness in a system responding to complex attacks because each step is performed independently. This study will recognize all internal and external users as a potentially threatening element. To perform connectivity analysis regarding an action, an intelligent convergence security framework and road map is suggested. A suggested convergence security framework was constructed to be independent of an automatic framework, such as the conventional single solution for the priority defense system of APT of the latest attack type, which makes continuous reputational attacks to achieve its goals. This study suggested the next generation convergence security framework to have preemptive responses, possibly against an APT attack, consisting of the following five hierarchical layers: domain security, domain connection, action visibility, action control, and convergence correspondence. In the domain, the connection layer suggests a security instruction and direction in the domains of administrative, physical and technical security. The domain security layer has consistency of status information among the security domain. A visibility layer of an intelligent attack action consists of data gathering, comparison and decision cycle. The action control layer is a layer that controls the visibility action. Finally, the convergence corresponding layer suggests a corresponding system of before and after an APT attack. The administrative security domain had a security design based on organization, rule, process, and paper information. The physical security domain is designed to separate into a control layer and facility according to the threats of the control impossible and control possible. Each domain action executes visible and control steps, and is designed to have flexibility regarding security environmental changes. In this study, the framework to address an APT attack and load map will be used as an infrastructure corresponding to the next generation security.

• Journal of Convergence for Information Technology
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• v.8 no.6
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• pp.165-171
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• 2018

The most threatening attack that has become a hot topic of recent IT security is APT Attack.. So far, there is no way to respond to APT attacks except by using artificial intelligence techniques. Here, we have implemented a machine learning algorithm for analyzing cyber threat data using machine learning method, using a data set that collects cyber attack cases using Scikit Learn, a big data machine learning framework. The result showed an attack classification accuracy close to 70%. This result can be developed into the algorithm of the security control system in the future.