• 정보보호학회논문지
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• 제28권3호
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• pp.665-679
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• 2018

정보통신의 발전, 특히 무선인터넷 기술과 스마트폰의 보급에 따라 디지털 데이터가 증가하면서, 온라인 빅데이터 개인정보 문제 즉, 개인 민감정보의 온라인 노출과 이로 인한 프라이버시 침해에 대한 우려 역시 높아지고 있다. 본 논문은 포털 서비스를 중심으로 국내 인터넷 환경에 공개된 온라인 빅데이터의 개인정보 침해 현황에 대한 분석을 수행하고 프라이버시 침해 가능성을 평가하기 위한 척도를 제시하였다. 이를 위하여 본 연구팀은 포털 사이트에서 제공하는 서비스 컨텐츠 중 약 5천만건의 사용자 게시글을 수집하여 개인정보에 해당하는 정보를 추출하고, 추출된 개인 정보를 기반으로 각 사용자의 ID가 부분 익명화 되었음에도 개인을 특정할 수 있는 신상 정보가 노출될 수 있음을 확인하였다. 또한 부분 익명화된 ID를 사용하여 서비스간 개인 정보의 연결 가능성과 개인 신상 정보 노출 수준을 반영한 위험도 측정 척도를 제안하였다.

• 한국융합학회논문지
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• 제9권4호
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• pp.57-63
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• 2018

IoT 장치는 클라우드 환경에서 다양한 역할과 기능을 수행할 수 있도록 여러 분야에서 사용되고 있다. 그러나, IoT 장치를 안정적으로 제어할 수 있는 접근제어에 대한 방안은 아직 구체적으로 제시되고 있지 않은 상황이다. 본 논문에서는 클라우드 환경에서 사용되고 있는 IoT 장치의 안정적인 접근을 수행할 수 있는 계층적 기반의 다단계 속성 접근제어 기법을 제안한다. 제안 방법은 IoT 장치의 원활한 접근을 돕기 위해서 IoT Hub을 두어 IoT 장치에 고유한 ID 키(보안 토큰)를 제공할 뿐만 아니라 수 있도록 하는 X.509 인증서 및 개인 키를 IoT Hub에서 인증하도록 하여 IoT 장치의 개인키를 IoT 장치 외부에서 알 수 없도록 하였다. 성능평가 결과, 제안방법은 기존 기법보다 인증 정확도가 평균 10.5% 향상되었으며 처리 시간도 14.3% 낮은 결과를 얻었다. IoT 속성 수에 따른 IoT Hub의 오버헤드는 기존 기법보다 9.1% 낮은 결과를 얻었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권4호
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• pp.1307-1323
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• 2014

With the exhaustion of global IPv4 addresses, IPv6 technologies have attracted increasing attentions, and have been deployed widely. Meanwhile, new applications running over IPv6 networks will change the traditional traffic characteristics obtained from IPv4 networks. Traditional models obtained from IPv4 cannot be used for IPv6 network monitoring directly and there is a need to investigate those changes. In this paper, we explore the flow features of IPv6 traffic and compare its difference with that of IPv4 traffic from flow level. Firstly, we analyze the differences of the general flow statistical characteristics and users' behavior between IPv4 and IPv6 networks. We find that there are more elephant flows in IPv6, which is critical for traffic engineering. Secondly, we find that there exist many one-way flows both in the IPv4 and IPv6 traffic, which are important information sources for abnormal behavior detection. Finally, in light of the challenges of analyzing massive data of large-scale network monitoring, we propose a group flow model which can greatly reduce the number of flows while capturing the primary traffic features, and perform a comparative measurement analysis of group users' behavior dynamic characteristics. We find there are less sharp changes caused by abnormity compared with IPv4, which shows there are less large-scale malicious activities in IPv6 currently. All the evaluation experiments are carried out based on the traffic traces collected from the Northwest Regional Center of CERNET (China Education and Research Network), and the results reveal the detailed flow characteristics of IPv6, which are useful for traffic management and anomaly detection in IPv6.

• 융합보안논문지
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• 제7권2호
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• pp.9-16
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• 2007

오늘날 사회는 정보와 지식이 부가가치 창출의 원천이 되는 지식 정보사회로 그 패러다임이 전환되고 있다. 이러한 사회의 변화에 맞추어 학교 교육에서도 과거의 '공급자 중심에서 수요자중심'이라고 하는 커다란 변화를 요구받고 있다. 이에 본 논문은 중학교 기술과 전기의 발생 내용을 개별화 학습 및 자기 주도적 학습에 중점을 두고 멀티미디어 타이틀을 설계 및 구현하였다. 멀티미디어, 저작도구, 멀티미디어의 교육적 활용, CAI와 학습이론, 학습형태에 관하여 고찰하고 이를 바탕으로 기술과 교과관련 멀티미디어 요소를 추출 분석하여 각 단원별 학습목표, 학습내용, 단원평가, 관련 사이트로 구분되어 학습할 수 있도록 구성하고 문자, 음성, 영상, 애니메이션 등과 같은 여러 매체들을 병합하여 학생들이 학습에 흥미를 가지고 학습 과정에 능동적으로 참여하여 학습할 수 있도록 하였다.

• International Journal of Computer Science & Network Security
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• 제21권12spc호
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• pp.597-603
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• 2021

The current Sudanese preschool system depends on limited methods of education, children's education needs to be equipped to keep pace with technological development, also, the large gap that exists between the families and the Kindergartens, where many parents have no idea on how their child progresses in the KG context. The aim of this research is to integrate ICT in the preschool education to enhance and improve the preschool education, by building an Integrated Educational Application (Computerized Application for Preschool Education CAPE) which will help to improve the learning outcomes. The researchers used the Experimental Research Methodology, the characteristic of CAPE application is; suitable for children's age, the application style is more attractive to the children and contains a different way to help children get learning. Alawaeel and the Smart Child Kindergartens in Republic of Sudan were selected as a sample of the study, with sample size specifically, 50 children's. Also, the Central Bank of Sudan Kindergarten was selected as one of the institutional Kindergartens for easy communication with parents of children with a sample size 21 children. The study found that; using CAPE application in KG enables children to increase general learning effects and developing child's cognitive skills. Also, the children who were allowed to use CAPE by their parents are performed better in the overall evaluation of KG lessons. Also, using the CAPE in the Pre-School education helps the parents following their children's progress better and more reliable. The researcher recommends that to apply the computerized application and includes the second level. Also, converting the computerized program into an application to be used by children by their self, without the intervention of parents.

• 융합보안논문지
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• 제19권2호
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• pp.137-146
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• 2019

본 연구는 NCS 의사소통능력과 부사관과 의사소통 교육의 연관성을 규명하여 교육목표와 성취 수준에 대하여 고찰하고 이에 적합한 자료통합적 문서 교육에 대하여 살펴보고자 한다. 부사관과 의사소통 교육의 목표는 실질적인 부사관의 의사소통 상황과 연관성을 지닌 문서이해능력과 문서작성능력을 함양하는 것이며 이에 대한 '중' 이상의 성취 수준을 달성하는 것이다. 교육구성은 부사관과의 특성을 고려하여 하위능력 요소에 따른 주차별 세부사항으로 설계하여 교육목표와 수준을 달성하도록 구성하였다. 이에 적합한 부사관과 자료통합적 문서 교육은 문서의 주제제시-팀 활동-최종활동보고서 제출이라는 3단계로 이루어지며 지속적인 평가지를 작성하여 성취 수준을 확인할 수 있도록 구성하였다. 자료통합적 문서 교육은 NCS의 중요성이 강조되는 시점에서 NCS와 연계된 부사관과의 의사소통 교육방안을 제시한 것이다. 앞으로 부사관과 학생들의 문서작성 역량 향상을 모색할 수 있는 다양한 논의가 진행되기를 기대한다.

• 한국군사과학기술학회지
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• 제22권4호
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• pp.545-554
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• 2019

The purpose of this study is to develop a method of applying AR(Augmented Reality)/VR(Virtual Reality) to educational and training systems from a comprehensive perspective, rather than applying AR/VR technology to specific education and training systems. We suggested whether to apply AR or VR technology to education and training system, the level of application of technology when constructing using AR/VR technology, and the criteria of priority among many education and training systems. To do this, we presented the framework of application of AR/VR technology, the evaluation criteria for selecting priority of education and training system applying AR/VR, and the systematic procedure for utilization of developed method. This study is significant in that it has developed a method to determine the direction of systematic AR/VR technology application for all education and training systems operated by the military or organization. This is expected to contribute to the overall efficiency of the organization in terms of economical utilization of the limited budget as well as the various benefits of utilizing basic AR/VR technology.

• International Journal of Computer Science & Network Security
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• 제21권7호
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• pp.63-69
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• 2021

Flipped learning is necessary for modern education but quite difficult to implement. In pedagogical science, the question remains to what extent the practical work of the teacher in combination with the technologies of flipped learning will improve the quality of higher education. The aim of this article is to study the effectiveness and feasibility of using flipped learning technologies, assessing their perception by students (advantages and problems), identified an algorithm for introducing flipped learning technology in higher education institutions. Research methods. The main method is an experiment. An evaluation of the effectiveness of the study was conducted using a questionnaire and observation method. Statistical methods were used to evaluate the results of the experiment. The research hypothesis is that flipped learning allows the teacher to spend more time on an individual approach, to understand the real needs of students, and provide effective feedback, thereby improving the quality of learning and motivation of students, especially while studying complex material. The results of the study are to prove the effectiveness of the technology of flipped education in the study of complex disciplines, courses, topics. The use of flipped learning strategies improves the self-regulation of the educational process, group work skills, improves students' ability to learn, overcome difficulties. The technology of flipped learning in the presence of modern technical means and constant work on improving the level of digital literacy is an effective means for students to master complex topics and problematic issues that require additional consideration and discussion. The perspective of further research is the consideration of integrated approaches to the application of flipped learning technologies to the principles of STEAM-education, multilingual and multicultural programs, etc. It is also worth continuing to develop a set of methods aimed at enhancing the student's learning activities, the formation of group work skills, direct participation in creating the foundations of higher education.

• International Journal of Computer Science & Network Security
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• 제22권7호
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• pp.109-116
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• 2022

The article is devoted to perfecting the system of management of the financial potential of transport enterprises. It is established that transport as an integral part of the state economy has to organically enter the market economy and provide sustainable transport services to national economy enterprises regardless of ownership, as well as ensure passenger transportation. It is also determined that in the conditions of market relations, transport highways must perform their functions with sufficient economic benefit to keep their material and technical resources in good order, conduct an investment policy with extensive use of scientific and technological progress, as well as a social policy guaranteeing the conditions for employees' motivated work. The study reveals an association between the financial and strategic goals of transport enterprises and the minimization of their economic risks, the prevention of bankruptcy and profit margin shortfalls. It is found that transport enterprises need to strive for the overall improvement of their financial potential through increasing the components of financial potential and assessing the impact of risk factors on them: the capacity of fixed assets, the capacity of financial resources, the capacity of services, and the capacity of credit opportunities. These are the elements of transport enterprises' financial potential that ensure its desired level. It is demonstrated that of critical importance in managing the financial potential of a transport enterprise is the role of financial resources, as a subject cannot reach the desired strategic goals without them.

• International Journal of Computer Science & Network Security
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• 제23권3호
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• pp.49-56
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• 2023

Machine learning methods diversely applied to the Internet of Things (IoT) field have been successful due to the enhancement of computer processing power. They offer an effective way of detecting malicious intrusions in IoT because of their high-level feature extraction capabilities. In this paper, we proposed a novel feature selection method for malicious intrusion detection in IoT by using an evolutionary technique - Genetic Algorithm (GA) and Machine Learning (ML) algorithms. The proposed model is performing the classification of BoT-IoT dataset to evaluate its quality through the training and testing with classifiers. The data is reduced and several preprocessing steps are applied such as: unnecessary information removal, null value checking, label encoding, standard scaling and data balancing. GA has applied over the preprocessed data, to select the most relevant features and maintain model optimization. The selected features from GA are given to ML classifiers such as Logistic Regression (LR) and Support Vector Machine (SVM) and the results are evaluated using performance evaluation measures including recall, precision and f1-score. Two sets of experiments are conducted, and it is concluded that hyperparameter tuning has a significant consequence on the performance of both ML classifiers. Overall, SVM still remained the best model in both cases and overall results increased.