• 시스템엔지니어링학술지
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• 제18권2호
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• pp.149-159
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• 2022

This study investigated the relationship between economic growth and energy security risk levels in Korea using linear and non-linear ARDL methods. While there are many studies on the relationship between energy consumption and economic growth, few studies focus on the relationship between energy security and economic growth considering 4A dimensions of energy security such as energy availability, accessibility, acceptability, and affordability. Energy risk index from Global Energy Institue and GDP data from world bank are used for ARDL and NARDL analysis. Our result of ARDL shows that there is no long-term relationship between energy security risk levels and economic growth. On the other hand, NARDL result shows that there is an asymmetric relationship between economic growth and energy security risk levels in the long run. The results show the importance of expending further research on ensuring energy security to policymakers.

• International Journal of Computer Science & Network Security
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• 제23권2호
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• pp.89-95
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• 2023

Cloud computing today provides huge computational resources, storage capacity, and many kinds of data services. Data sharing in the cloud is the practice of exchanging files between various users via cloud technology. The main difficulty with file sharing in the public cloud is maintaining privacy and integrity through data encryption. To address this issue, this paper proposes an Enhanced RSA encryption schema (ERSA) for data sharing in the public cloud that protects privacy and strengthens data integrity. The data owners store their files in the cloud after encrypting the data using the ERSA which combines the RSA algorithm, XOR operation, and SHA-512. This approach can preserve the confidentiality and integrity of a file in any cloud system while data owners are authorized with their unique identities for data access. Furthermore, analysis and experimental results are presented to verify the efficiency and security of the proposed schema.

• International Journal of Computer Science & Network Security
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• 제23권11호
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• pp.162-168
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• 2023

As the old saying goes "a picture is worth a thousand words" data visualization is essential in almost every industry. Companies make Data-driven decisions and gain insights from visual data. However, there is a need to investigate the role of data visualization in human resource management. This review aims to highlight the power of data visualization in the field of human resources. In addition, visualize the latest trends in the research area of human resource and data visualization by conducting a bibliometric analysis. The study adopted a literature review on recent publications from 2017 to 2022 to address research questions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권10호
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• pp.2822-2843
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• 2023

All aspects of human life have become increasingly dependent on data in the last few decades. The development of several applications causes an enormous issue on data volume in current years. This information must be safeguarded and kept in safe locations. Massive volumes of data have been safely stored with cloud computing. This technology is developing rapidly because of its immense potentials. As a result, protecting data and the procedures to be handled from attackers has become a top priority in order to maintain its integrity, confidentiality, protection, and privacy. Therefore, it is important to implement the appropriate security measures in order to prevent security breaches and vulnerabilities. An improved version of Modular Encryption Standard (IMES) based on layered modelling of safety mechanisms is the major focus of this paper's research work. Key generation in IMES is done using a logistic map, which estimates the values of the input data. The performance analysis demonstrates that proposed work performs better than commonly used algorithms against cloud security in terms of higher performance and additional qualitative security features. The results prove that the proposed IMES has 0.015s of processing time, where existing models have 0.017s to 0.022s of processing time for a file size of 256KB.

• International Journal of Computer Science & Network Security
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• 제23권4호
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• pp.25-31
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• 2023

Fog computing diversifies cloud computing by using edge devices to provide computing, data storage, communication, management, and control services. As it has a decentralised infrastructure that is capable of amalgamating with cloud computing as well as providing real-time data analysis, it is an emerging method of using multidisciplinary domains for a variety of applications; such as the IoT, Big Data, and smart cities. This present study provides an overview of the security and privacy concerns of fog computing. It also examines its fundamentals and architecture as well as the current trends, challenges, and potential methods of overcoming issues in fog computing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권6호
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• pp.3055-3073
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• 2019

In this paper, a new user identification method is presented using real environmental human-computer-interaction (HCI) behavior data to improve method usability. User behavior data in this paper are collected continuously without setting experimental scenes such as text length, action number, etc. To illustrate the characteristics of real environmental HCI data, probability density distribution and performance of keyboard and mouse data are analyzed through the random sampling method and Support Vector Machine(SVM) algorithm. Based on the analysis of HCI behavior data in a real environment, the Multiple Kernel Learning (MKL) method is first used for user HCI behavior identification due to the heterogeneity of keyboard and mouse data. All possible kernel methods are compared to determine the MKL algorithm's parameters to ensure the robustness of the algorithm. Data analysis results show that keyboard data have a narrower range of probability density distribution than mouse data. Keyboard data have better performance with a 1-min time window, while that of mouse data is achieved with a 10-min time window. Finally, experiments using the MKL algorithm with three global polynomial kernels and ten local Gaussian kernels achieve a user identification accuracy of 83.03% in a real environmental HCI dataset, which demonstrates that the proposed method achieves an encouraging performance.

• 융합보안논문지
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• 제16권5호
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• pp.41-48
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• 2016

본 논문은 플로우 시각화 기반의 네트워크 보안 상황 감시 방법인 VisFlow를 제안하며, 기존 트래픽 플로우 시각화 기술의 단점인 대량 트래픽 발생 시의 직관성 상실 문제, 대칭적 주소 공간에 의한 반사현상 문제, 종단간 연결 의미의 상실 문제를 해결하고자 한다. VisFlow는 단순하고 효율적인 보안 시각화 인터페이스로써 플로우 시각화 기술을 활용하여 개별적인 트래픽 데이터들에서는 볼 수 없었던 다양한 네트워크 현상들을 패턴으로 형상화하고 관리 네트워크 내의 보안 상황을 실시간으로 분석 및 감시하는 방법이다. 트래픽 플로우의 포트 역할 분석 방법을 이용하여 노드 유형과 중요 정보를 식별 분류하고, 분류된 정보는 중요도에 따라 2D/3D 공간 상에 단순화 및 강조하여 표시함으로써 직관성과 실용성을 높인다. 또한, IP주소값에 기반한 비대칭적 노드 배치를 통해 반사현상 문제를 해결하고 노드간의 연결선을 활용하여 종단간의 세션 의미를 유지함으로써 정보성은 높인다. 관리자는 VisFlow를 통해 방대한 트래픽 데이터를 쉽게 탐색하고 전체 네트워크 상황을 직관적으로 파악함으로써 네트워크 보안 상황을 효과적으로 감시할 수 있다.

• 정보보호학회논문지
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• 제25권6호
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• pp.1485-1494
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• 2015

기존 데이터 은닉은 대용량 멀티미디어 파일에 데이터를 삽입하는 방식으로 이루어졌다. 하지만 최근 Microsoft Office 2003 이하 버전 제품의 문서파일은 구조가 파일시스템과 유사하여 데이터 은닉이 비교적 용이해 커버데이터(Cover data)로 사용되고 있다. 데이터가 은닉된 문서파일을 MS Office 프로그램으로 실행할 경우 은닉 사실을 모르는 사용자는 은닉 데이터를 눈으로 쉽게 확인할 수 없다. 이에 본 논문에서는 Microsoft Office 2003 이하 버전과 한컴오피스 문서파일에서 사용되는 복합문서 파일 이진형식(Compound File Binary Format) 파일 포맷 구조를 분석하여 데이터 삽입이 가능한 공간을 살펴보고 이를 탐지하기 위한 방안을 제시하고자 한다.

• 융합보안논문지
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• 제20권4호
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• pp.47-59
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• 2020

군은 4차 산업혁명을 통해 도약적 변혁을 추진해야 하지만, 군사보안측면 4차 산업혁명의 부작용과 역기능에 대한 준비도 필요하다. 이에 본 연구는 4차 산업혁명 선진국들의 '군사보안' 관련 연구의 방향과 국내연구와의 차이점과 보완요소가 없는지를 분석해 보았다. 이를 위해 빅데이터 텍스트마이닝과 의미연결망분석을 활용해 국내연구와 국외연구간의 차이점들을 추출해내었으며, 다음과 같은 7가지 과제를 도출해 내었다. 첫째, 민·관·군 및 산·학·연과의 융합연계 체계 강화, 둘째, 사이버보안 국제협력·공조 정보공유방안, 셋째, 군사혁신과 군(軍) 비대칭 사이버보안 혁신, 넷째, 4차 산업혁명에 따른 군사보안 융합연동접점 관리체계 구축, 다섯째, 기술공학에서 사회공학으로의 접근방식 전환, 여섯째, 군내 군사보안 거버넌스 체계 확립, 일곱째, 군사 디지털자료의 비밀등급 구체화 등이다. 이러한 대응방안에 대한 추가연구를 통해 4차 산업혁명 신기술 혁신의 시대에 군의 혁신과 함께 취약한 군사보안 측면에서의 보완적인 연구도 병행해서 이루어질 수 있기를 기대해 본다.

• Nuclear Engineering and Technology
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• 제55권6호
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• pp.2034-2046
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• 2023

Industrial control systems in nuclear facilities are facing increasing cyber threats due to the widespread use of information and communication equipment. To implement cyber security programs effectively through the RG 5.71, it is necessary to quantitatively assess cyber risks. However, this can be challenging due to limited historical data on threats and customized Critical Digital Assets (CDAs) in nuclear facilities. Previous works have focused on identifying data flows, the assets where the data is stored and processed, which means that the methods are heavily biased towards information security concerns. Additionally, in nuclear facilities, cyber threats need to be analyzed from a safety perspective. In this study, we use the system theoretic process analysis to identify system-level threat scenarios that could violate safety constraints. Instead of quantifying the likelihood of exploiting vulnerabilities, we quantify Security Control Measures (SCMs) against the identified threat scenarios. We classify the system and CDAs into four consequence-based classes, as presented in NEI 13-10, to analyze the adversary impact on CDAs. This allows for the ranking of identified threat scenarios according to the quantified SCMs. The proposed framework enables stakeholders to more effectively and accurately rank cyber risks, as well as establish security and response strategies.