• 융합보안논문지
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• 제14권4호
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• pp.101-108
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• 2014

최근 클라우드 컴퓨팅 기술은 전 세계적으로 중요한 이슈로 부각되고 있으며, 이산화탄소 배출을 경감하는 것으로도 많은 주목을 받고 있다. 그러나 클라우드 컴퓨팅의 탄소배출은 긍정적인 측면과는 달리, 여러 취약점들로 인해, 경감정도에 차이를 갖고 있다. 따라서 본 논문은 클라우드 컴퓨팅의 이산화탄소 배출과 관련한 보안 시스템의 배출량 측정 실험과 클라우드 이산화탄소 배출 관련 사례연구를 통해 배출 요인을 분석함으로써, 향후, 클라우드 컴퓨팅의 보안 설계와 성능 향상을 위한 자료로 활용될 것으로 기대한다.

• International Journal of Computer Science & Network Security
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• 제22권5호
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• pp.5-10
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• 2022

Photovoltaic systems provide a reliable green energy solution. The sustainability and low-maintenance of Photovoltaic systems motivate the integration of Photovoltaic systems into the electrical grid and further contribute to a greener environment, as the system does not cause any pollution or emissions. Developing methodologies based on machine learning techniques to assist in reducing the burden of studies related to integrating Photovoltaic systems into the electric grid are of interest. This research aims to develop a methodology based on a unsupervised machine learning algorithm that can reduce the burden of extensive studies and simulations related to the integration of Photovoltaic systems into the electrical grid.

• 한국항공운항학회지
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• 제9권2호
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• pp.55-62
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• 2001

A safe and secure civil aviation system is a critical component of the nation's overall security, physical infrastructure, and economic foundation. Although it is not fully known at this time what actually occurred or which of the weaknesses in the nation's aviation security apparatus contributed to the terrible events of 11 September in the U.S.A., it is clear that serious weaknesses exist in our aviation security system including regulation system. Actually, defectiveness of regulations structure and contents concerned in aviation security were discussed in various studies. On this study, we have identified defectiveness in aviation security regulation system by the comparative study between 14 CFR and Korean regulations. Finally, we are to provide some suggestions and alternatives to improve aviation security regulation system in this country.

• 정보화정책
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• 제30권4호
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• pp.3-39
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• 2023

정보/정보시스템의 중요성이 높아지면서, 정보보안에 대한 중요성이 강조되고 있고, 조직에 적합한 정보보안 수준을 유지하기 위한 도구로서 정보보안 감사의 중요성 또한 높아지고 있다. 본 연구의 목적은 정보보안 감사 분야의 국내외 학술 논문들을 분석하여 전반적인 연구 현황을 살펴보고 향후 연구 분야를 제시하는 것이다. 이를 위해 총 103편의 국내외 논문을 일반 기준과 연구 주제 관련 기준을 바탕으로 분석하였다. 주요한 분석 결과로는 연구 방법적인 측면에서 이 분야의 이론적인 발전을 위해 실증 연구의 비중을 높일 필요가 있다. 연구의 내용적인 측면에서 보면, 연구주제 '감사인/감사조직'의 경우, 연구의 누적적인 발전을 위해 역량과 같은 변수들에 대한 프레임워크를 제시하는 연구가 필요하다. 연구 주제 '감사 활동/절차'에 대해서는 감사의 세부 활동 과정/결과를 분석하는 연구를 수행할 필요가 있다. 연구 주제 '감사 대상'의 경우에는 해외 연구에서 분석한 신기술/특정 산업/특정 보안분야 등을 주목해 볼 가치가 있다. 연구 주제 '감사 목적/효과'의 경우, 현재 연구마다 서로 다르게 조작화되고 있는 성과/품질을 종합적이고 체계적으로 정의하는 연구가 필요하다. 연구 주제 '감사 기준/지침'의 경우, 국내에서는 2016년 이후로 지침/모델에 대한 연구가 없으므로, 지속적인 관심이 필요하다.

• 융합보안논문지
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• 제16권6_2호
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• pp.33-42
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• 2016

본 연구는 연구가설 "NCS 인식 ➩ NCS 교육 필요성 ➩ NCS 교육의 성과"를 설정하고 경호학과 학생들을 대상으로 NCS에 대한 인식 수준과 대학에서 경호관련 NCS 교육의 필요성을 살펴보기 위해 설문조사를 실시하였다. 내적일관성을 분석한 결과 Chronbach's Alpha 계수 값이 모두 0.8 이상 산출되어 내적 일관성을 확보한 것으로 나타났다. 타당성 검증에서는 모두 기준치 이상 산출되어 변수들 간 집중타당성 및 판별 타당성이 확보된 것으로 조사되었다. 연구모형을 검증하기 위해 구조방정식 모형을 사용한 결과 본 연구모형은 적합한 것으로 나타났다. 가설검증결과 각 연구가설의 표준화계수가 0.726과 0.870로 산출되어 각 연구가설의 관계가 각각 72.6%와 87%의 영향을 미치는 것으로 나타나 매우 높은 상호 연관성이 있는 것으로 분석되었다.

• 한국전자거래학회지
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• 제24권2호
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• pp.113-124
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• 2019

최근 많은 기업은 IoT가 적용된 제품들을 개발하여 판매하고 있으며, 외부의 위협으로부터 제품 및 사용자 정보를 보호하기 위해 기획 단계서부터 보안을 고려하고 있다. 그러나 IoT의 다양성으로 인해 제품별 보안요구사항 개발을 하기 위해 투자되는 시간과 인력의 한계가 있어 현재 낮은 수준의 보안이 적용되어 있다. IoT가 적용된 제품에서 취약점이 지속적으로 발표되고 있고, 이에 실제 Home IoT에 대한 보다 상세한 보안요구사항이 필요하게 되었다. 이를 위해 본 논문에서는 Microsoft사의 Threat Modeling Tool을 사용하여 Home IoT의 위협을 도출하였으며, 도출된 위협과 국내 외 취약점 평가 기준 및 논문 등과 비교 분석하여 실제 보안성 점검에 사용할 수 있는 항목을 개발하여 Home IoT 제품의 보안성 강화방안을 제시하였다. 또한 도출된 보안요구사항과 기존의 보안요구사항을 바탕으로 점검을 실시하여 효과성 검토를 하였으며, 그 결과 본 논문에서 도출된 보안요구사항의 취약점 발견 효과성이 대체로 높은 것으로 나타났다.

• 아동학회지
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• 제37권6호
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• pp.119-132
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• 2016

Objective: The purpose of this study was to analyze the operation and personal information management of public and private kindergarten homepages. Methods: A total of 2,846 kindergartens were selected from the I-Sarang portal service for analyzing operation, and 217 self-operating homepages were selected for evaluating management. Seven evaluation items from three domains (information gathering procedures and scope, information security, and management of file exposure protection) were used. Wireshark and Google were used for analyzing some evaluation items. Results: The operating ratio of kindergarten homepages was low and most of the kindergartens self-operated their homepages. The evaluation of the information gathering procedures and scope showed that the rule of consent process was not rigidly followed but that the rule of legality for information gathering was followed. Items related to information security were followed at very low levels. As for the management of file exposure protection, the evaluation of items related to the prevention of attachment disclosure showed that the rule of protecting personal information included in an attached file was followed but that the notice regarding information protection was not. Across all evaluation items, the level of personal information management was higher in public (vs. private) kindergartens. Conclusion: These results indicate methods to more securely and effectively manage personal information on kindergarten homepages.

• Asia pacific journal of information systems
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• 제18권4호
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• pp.1-26
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• 2008

Rapid progress of information technology and widespread use of the personal computers have brought various conveniences in our life. But this also provoked a series of problems such as hacking, malicious programs, illegal exposure of personal information etc. Information security threats are becoming more and more serious due to enhanced connectivity of information systems. Nevertheless, users are not much aware of the severity of the problems. Using appropriate password is supposed to bring out security effects such as preventing misuses and banning illegal users. The purpose of this research is to empirically analyze a research model which includes a series of factors influencing the effectiveness of passwords. The research model incorporates the concept of risk based on information systems risk analysis framework as the core element affecting the selection of passwords by users. The perceived risk is a main factor that influences user's attitude on password security, security awareness, and intention of security behavior. To validate the research model this study relied on questionnaire survey targeted on evening class MBA students. The data was analyzed by AMOS 7.0 which is one of popular tools based on covariance-based structural equation modeling. According to the results of this study, while threat is not related to the risk, information assets and vulnerability are related to the user's awareness of risk. The relationships between the risk, users security awareness, password selection and security effectiveness are all significant. Password exposure may lead to intrusion by hackers, data exposure and destruction. The insignificant relationship between security threat and perceived risk can be explained by user's indetermination of risk exposed due to weak passwords. In other words, information systems users do not consider password exposure as a severe security threat as well as indirect loss caused by inappropriate password. Another plausible explanation is that severity of threat perceived by users may be influenced by individual difference of risk propensity. This study confirms that security vulnerability is positively related to security risk which in turn increases risk of information loss. As the security risk increases so does user's security awareness. Security policies also have positive impact on security awareness. Higher security awareness leads to selection of safer passwords. If users are aware of responsibility of security problems and how to respond to password exposure and to solve security problems of computers, users choose better passwords. All these antecedents influence the effectiveness of passwords. Several implications can be derived from this study. First, this study empirically investigated the effect of user's security awareness on security effectiveness from a point of view based on good password selection practice. Second, information security risk analysis framework is used as a core element of the research model in this study. Risk analysis framework has been used very widely in practice, but very few studies incorporated the framework in the research model and empirically investigated. Third, the research model proposed in this study also focuses on impact of security awareness of information systems users on effectiveness of password from cognitive aspect of information systems users.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2014년도 추계학술발표대회
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• pp.464-465
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• 2014

Analysis of characteristics in software vulnerabilities can be used to assess security risks and to determine the resources needed to develop patches quickly to handle vulnerability discovered. Being a new research area, the quantitative aspects of software vulnerabilities and risk assessments have not been fully investigated. However, further detailed studies are required related to the security risk assessment, using rigorous analysis of actual data which can assist decision makers to maximize the returns on their security related efforts. In this paper, quantitative software vulnerability analysis has been presented for major Web browsers (Internet Explorer (IE), Firefox (FX), Chrome (CR) and Safari (SF)) with respect to the Common Vulnerability Scoring System (CVSS). The results show that, almost all the time, vulnerabilities are compromised from remote networks with no authentication required systems, and exploitation aftermath is getting worse.

• Journal of Information Processing Systems
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• 제17권3호
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• pp.571-585
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• 2021

Applications for object detection are expanding as it is automated through artificial intelligence-based processing, such as deep learning, on a large volume of images and videos. High dependence on training data and a non-transparent way to find answers are the common characteristics of deep learning. Attacks on training data and training models have emerged, which are closely related to the nature of deep learning. Privacy, integrity, and robustness for the extracted information are important security issues because deep learning enables object recognition in images and videos. This paper summarizes the security issues that need to be addressed for future applications and analyzes the state-of-the-art security studies related to robustness, privacy, and integrity of object detection for images and videos.