• Korean Security Journal
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• no.25
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• pp.185-208
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• 2010

This study is to suggest the current security education programs and improvement of industrial security curriculums in Korea. We live in a world of insecurity; the world is changing at an ever accelerating pace. Life, society, economics, international relations, and security risk are becoming more and more complex. The nature of work, travel, recreation, and communication is radically changing. We live in a world where, seemingly with each passing year, the past is less and less's guide to the future. Security is involved in on one way or another in virtually every decision we make and every activity we undertake. The global environment has never been more volatile, and societal expectations for industrial security and increasing if anything. The complexities of globalization, public expectation, regulatory requirements, transnational issues, jurisdictional risks, crime, terrorism, advances in information technology, cyber attacks, and pandemics have created a security risk environment that has never been more challenging. We had to educate industrial security professional to cope with new security risk. But, how relevant is a college education to the security professional? A college degree will not guarantee a job or advancement opportunities. But, with a college and professional training, a person has improved chances for obtaining a favored position. Commonly, Security education and experience are top considerations to find a job so far, also training is important. Today, Security is good source to gain competitive advantage in global business. The future of security education is prospect when one considers the growth evident in the field. Modern people are very security-conscious today, so now we had to set up close relevant industrial security programs to cope with new security risk being offered in colleges or several security professional educational courses.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.664-673
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• 2018

The industrial control system (ICS) has operated as a closed network in the past, but it has recently been linked to information and communications services and has been causing damage due to cyber attacks. As a countermeasure, the Information Communication Infrastructure Protection Act was enacted, but it cannot be applied to various real control environments because there is only a one-way policy-from a control network to a business network. In addition, IEC62443 defines an industrial control system reference model as an international standard, and suggests an area security model using a firewall. However, there is a limit to linking an industrial control network, operating as a closed network, to an external network only through a firewall. In this paper, we analyze the security model and research trends of the industrial control system at home and abroad, and propose an industrial control system security model that can be applied to the actual interworking environments of various domestic industrial control networks. Also, we analyze the security of firewalls, industrial firewalls, network connection equipment, and one-way transmission systems. Through a domestic case and policy comparison, it is confirmed that security is improved. In the era of the fourth industrial revolution, the proposed security model can be applied to security management measures for various industrial control fields, such as smart factories, smart cars, and smart plants.

• Convergence Security Journal
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• v.17 no.3
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• pp.73-81
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• 2017

In April 2009, in the wake of President Obama's Prague speech, the international community held four nuclear sec urity summits from 2010 to 2016 to promote nuclear security and prevent nuclear terrorism. The Nuclear Security S ummit has made significant progress in preventing terrorists from attempting to acquire nuclear weapons or fissile materials, but it still has limitations and problems. To solve this problem, the international community should resume the joint efforts for strengthening bilateral cooperation and multilateral nuclear security regime, and the participating countries should strive to protect their own nuclear materials and fulfill their commitments to secure nuclear facilitie s. Second, the United Nations(UN), the IAEA(International Atomic Energy Agency), International Criminal Police Or ganization(INTERPOL), the Global Initiative to Combat Nuclear Terrorism(GICNT), and the Global Partnership(G P) must continue their missions to promote nuclear security in accordance with the five action plans adopted at the Fourth Nuclear Security Summit. Third, the participating countries should begin discussions on the management and protection of military nuclear materials that could not be covered by the Nuclear Security Summit. Fourth, the intern ational community must strive to strengthen the implementation of the Convention on the Physical Protection of Nuc lear Material(CPPNM) Amendment and International Convention for the Suppression of Acts of Nuclear Terrori sm(ICSANT), prepare for cyber attacks against nuclear facilities, and prevent theft, illegal trading and sabotage invo lving nuclear materials.

• Journal of Internet Computing and Services
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• v.18 no.1
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• pp.11-20
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• 2017

Recently, developments in the various fields of cloud computing technology has been utilized. Whereas the demand for cloud computing services is increasing, security threats are also increasing in the cloud computing environments. Especially, in case when the hosts interconnected in the cloud environments are infected and propagated through the attacks by malware. It can have an effect on the resource of other hosts and other security threats such as personal information can be spreaded and data deletion. Therefore, the study of malware analysis to respond these security threats has been proceeded actively. This paper proposes a type of attack clustering method of Zeus botnet using the k-means clustering algorithm for malware analysis that occurs in the cloud environments. By clustering the malicious activity by a type of the Zeus botnet occurred in the cloud environments. it is possible to determine whether it is a malware or not. In the future, it sets a goal of responding to an attack of the new type of Zeus botnet that may occur in the cloud environments.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.6
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• pp.1185-1195
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• 2014

Domestic and international CERTs are carrying out security monitoring and response services based on security devices for intrusion incident prevention and damage minimization of the organizations. However, the security monitoring and response service has a fatal limitation in that it is unable to detect unknown attacks that are not matched to the predefined signatures. In recent, many approaches have adopted the darknet technique in order to overcome the limitation. Since the darknet means a set of unused IP addresses, no real systems connected to the darknet. Thus, all the incoming traffic to the darknet can be regarded as attack activities. In this paper, we present a collection and analysis method of malicious URLs based on darkent traffic for advanced security monitoring and response service. The proposed method prepared 8,192 darknet space and extracted all of URLs from the darknet traffic, and carried out in-depth analysis for the extracted URLs. The analysis results can contribute to the emergence response of large-scale cyber threats and it is able to improve the performance of the security monitoring and response if we apply the malicious URLs into the security devices, DNS sinkhole service, etc.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.29-39
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• 2021

As damages to individuals, private sectors, and businesses increase due to newly occurring cyber attacks, the underlying network security problem has emerged as a major problem in computer systems. Therefore, NIDS using machine learning and deep learning is being studied to improve the limitations that occur in the existing Network Intrusion Detection System. In this study, a deep learning-based NIDS model study is conducted using the Convolution Neural Network (CNN) algorithm. For the image classification-based CNN algorithm learning, a discrete algorithm for continuity variables was added in the preprocessing stage used previously, and the predicted variables were expressed in a linear relationship and converted into easy-to-interpret data. Finally, the network packet processed through the above process is mapped to a square matrix structure and converted into a pixel image. For the performance evaluation of the proposed model, NSL-KDD, a representative network packet data, was used, and accuracy, precision, recall, and f1-score were used as performance indicators. As a result of the experiment, the proposed model showed the highest performance with an accuracy of 85%, and the harmonic mean (F1-Score) of the R2L class with a small number of training samples was 71%, showing very good performance compared to other models.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.3
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• pp.629-643
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• 2019

In the era of the 4th industrial revolution, countries around the world are conducting projects to rapidly expand smart factory to secure competitiveness in manufacturing industries. However, unlike existing factories where the network environment was closed, smart factories can be vulnerable because internal and external objects are interconnected and various ICT technologies are used. And smart factories are likely to be the subject of cyber-attacks that are designed to cause monetary damage to certain targets because economic damage is so serious when an accident occurs. Therefore, it is necessary to study and apply security for smart factories, but there is no specific smart factory system architecture, so there is no establish for smart factory security requirements. In order to solve these problems, this paper derives the smart factory architecture that can extract and reflect the main characteristics of a smart factory based on the domestic and foreign reference model of smart factories. And this paper identifies the security threats based on the derived smart factory architecture and present the security requirements to cope with them for contributing to the improvement of the security of the smart factory.

• Journal of Korean Society of Disaster and Security
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• v.11 no.2
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• pp.9-15
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• 2018

From natural disasters such as floods, heavy rains, and strong winds and social disasters such as 911 U.S. terrorism and cyber attacks that could have a fatal impact on corporate continuity, it is necessary to introduce and implement a Business Continuity Management System (BCMS) within a firm to maintain continuity of business and to change the organizational structure for an emergency state in order to operate and manage it systematically and efficiently. therefore, this study analyzed and verified the impact of introducing a Business Continuity Management System (BCMS) on the change in the recognition structure of an organization in four categories, including personal recognition, organizational culture, organizational structure, and organizational strategy, in order to analyse the impact and effect of introducing a Business Continuity Management System (BCMS) on the change in the recognition structure of each category. through this study, we believe that the introduction of a Business Continuity Management System (BCMS) within a firm could effectively change the organization's perception of an emergency state and help it maintain its continuity as well as improve its value.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.504-509
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• 2019

Recently, both wireless communications technology and the performance of small devices have developed exponentially, while the number of services using various types of Internet of Things (IoT) devices has also massively increased in line with the ongoing technological and environmental changes. Furthermore, ever more devices that were previously used in the offline environment-including small-size sensors and CCTV-are being connected to the Internet due to the huge increase in IoT services. However, many IoT devices are not equipped with security functions, and use vulnerable open source software as it is. In addition, conventional network equipment, such as switches and gateways, operates with vulnerabilities, because users tend not to update the equipment on a regular basis. Recently, the simple vulnerability of IoT devices has been exploited through the distributed denial of service (DDoS) from attackers creating a large number of botnets. This paper proposes a system that is capable of identifying Internet-connected devices quickly, analyzing and managing the vulnerability of such devices using Internet-wide scan technology. In addition, the vulnerability analysis rate of the proposed technology was verified through collected banner information. In the future, the company plans to automate and upgrade the proposed system so that it can be used as a technology to prevent cyber attacks.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1115-1130
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• 2020

Modern vehicles are equipped with a number of ECUs(Electronic Control Units), and ECUs can control vehicles efficiently by communicating each other through CAN(Controller Area Network). However, CAN bus is known to be vulnerable to cyber attacks because of the lack of message authentication and message encryption, and access control. To find these security issues related to vehicle hacking, CAN Fuzzing methods, that analyze the vulnerabilities of ECUs, have been studied. In the existing CAN Fuzzing methods, fuzzing inputs are randomly generated without considering the structure of CAN messages transmitted by ECUs, which results in the non-negligible fuzzing time. In addition, the existing fuzzing solutions have limitations in how to monitor fuzzing results. To deal with the limitations of CAN Fuzzing, in this paper, we propose a Non-Random CAN Fuzzing, which consider the structure of CAN messages and systematically generates fuzzing input values that can cause malfunctions to ECUs. The proposed Non-Random CAN Fuzzing takes less time than the existing CAN Fuzzing solutions, so it can quickly find CAN messages related to malfunctions of ECUs that could be originated from SW implementation errors or CAN DBC(Database CAN) design errors. We evaluated the performance of Non-Random CAN Fuzzing by conducting an experiment in a real vehicle, and proved that the proposed method can find CAN messages related to malfunctions faster than the existing fuzzing solutions.