• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.257-259
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• 2022

디지털트윈 기술은 실제의 공간과 사물을 디지털상에 복제함으로써 사용자의 최적 운영을 위한 시뮬레이션과 최적화, 모니터링을 제공한다. 4차 산업혁명이 진행됨에 따라 해상물류 분야에서도 자율주행 선박과 관련한 사물인터넷, 빅데이터, 혼합현실(MR) 등 여러 첨단기술의 적용이 검토되고 있다. 또한 자율운항선박이 도입됨에 따라 선원의 업무가 자동화되며 육상 지원의 비중이 늘어나며, 완전 자율운항선박의 경우 선박의 모든 제어가 육상에서 이루어지게 된다. 따라서 육상지원자가 선박을 모니터링하고 최적 운영하기 위해 선박의 디지털트윈 모델의 개발이 필요하다. 따라서 선박에 적용가능한 디지털트윈 아키텍처를 구성하고 이를 기반으로 클라우드 기반의 혼합현실 프로토타입 애플리케이션을 개발했다. 이를 통해 본 논문에서 제안한 디지털 트윈 아키텍처를 활용하여 선박의 디지털 트윈 시스템을 구현할 수 있음을 확인하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.216-218
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• 2019

클라우드 서비스 기반의 시스템은 기존의 물리적 인프라 기반의 서비스에 비해 전사관점의 투자 Risk 를 줄이고 보다 효율적인 시스템의 구축과 운영을 가능하게 한다. 그러나 이러한 장점을 제공하기 위한 클라우드 서비스의 서비스모델과 기술적 관점의 특징으로 인해 기존보다 더 많은 보안 취약점에 노출될 수 있다. 이러한 보안 취약점에 효과적인 대응을 하기 위해서는 이러한 클라우드 서비스의 특징을 이해하고 이를 기반으로 한 기술적/관리적 보안 대응책을 정의하고 실행하는 것이 필요하다. 이에 본 고에서는 클라우드 서비스의 특징을 살펴보고 이를 기반으로 하는 보안 취약점을 파악 이에 대한 대응 방안에 대해 제시하도록 한다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.17-23
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• 2019

IaaS is well known as a very cost effective computing service which enables required infrastructures to be rented on demand without ownership of real hardwares. It is very suitable for price sensitive services due to pay-per-use style. Operators of such services would want to adjust utilization policy quickly by estimating costs for cloud infrastructures as soon as possible. However, swift response is not possible due to that cloud service providers provide a dozen or so hours delayed billing information. Our work proposes a realtime IaaS cost estimation model based on usages monitored by virtual machine instance. We operate PC laboratory service on a public cloud during full semester to validate our suggested model. From that experiment, an averaged disparity between estimation and actual cost is less than 5.2%.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.2
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• pp.67-71
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• 2023

Recently, there are increasing cases of managing software labs by assigning virtual PCs in the cloud instead of physical PCs to each student. In this paper, we design and implement a Linux-based software practice platform that allows students to efficiently build their environments in the cloud. In our platform, instructors can create and control virtual machine templates for all students at once, and students practice on their own machines as administrators. Instructors can also troubleshoot each machine and restore its state. Meanwhile, the biggest obstacle to implementing this approach is the difficulty of predicting the costs of cloud services instantly. To cope with this situation, we propose a model that can estimate the cost of cloud resources used. By using daemons in each user's virtual machine, we instantly estimate resource usage and costs. Although our model has very low overhead, the predicted results are very close to the actual resource usage measured by cloud service providers. To further validate our model, we used the proposed platform in a Linux practice lecture for a semester and confirmed that the proposed model is very accurate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.10
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• pp.2331-2340
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• 2015

In this paper, we propose a social-based collaboration systems for business process management in the mobile cloud. This XMDR-DAI is to provide services for data sharing and exchange between local systems that operate independently in a cloud environment, take charge of a social-based collaborative business process management. Social-based collaborative business processes are handled in a collision among a structure such as unit conversion, meaning conflict, and the schema mapping data resulting from the inner query. The conflict was resolved by mapping process which takes in each XMDR-DAI.

• Smart Media Journal
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• v.12 no.2
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• pp.66-75
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• 2023

Recently, the number of cloud web applications is increasing owing to the accelerated migration of enterprises and public sector information systems to the cloud. Traditional network attacks on cloud web applications are characterized by Denial of Service (DoS) attacks, which consume network resources with a large number of packets. However, HTTP DoS attacks, which consume application resources, are also increasing recently; as such, developing security technologies to prevent them is necessary. In particular, since low-bandwidth HTTP DoS attacks do not consume network resources, they are difficult to identify using traditional security solutions that monitor network metrics. In this paper, we propose a new detection model for detecting HTTP DoS attacks on cloud web applications by collecting the application metrics of web servers and learning them using machine learning. We collected 18 types of application metrics from an Apache web server and used five machine learning and two deep learning models to train the collected data. Further, we confirmed the superiority of the application metrics-based machine learning model by collecting and training 6 additional network metrics and comparing their performance with the proposed models. Among HTTP DoS attacks, we injected the RUDY and HULK attacks, which are low- and high-bandwidth attacks, respectively. As a result of detecting these two attacks using the proposed model, we found out that the F1 scores of the application metrics-based machine learning model were about 0.3 and 0.1 higher than that of the network metrics-based model, respectively.

• Journal of Digital Convergence
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• v.16 no.8
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• pp.161-167
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• 2018

The purpose of this study is to investigate how the advertising campaign is spreading in social networks, and how the advertising model plays an important role in advertisement diffusion. In order to grasp the diffusion patterns of advertising, a text mining and social network analysis were conducted using the beer brand 'Kloud' as a collection keyword. After analyzing the social data for two months since the on-air of 'Good Body' advertisement, which was the first ad that "Sulhyun" appeared in. After the launch of the ad, Kloud has been mainly associated with keywords such as 'yavis & trendy style', 'beer brand', 'beer matching food', 'luxury beer drinking place', 'leisure trend', and 'SNS activity', etc. In addition, "Sul Hyun" also showed that an advertising model contributes to the spread of advertisement on social media in terms of image transition as well as brand's name and unique selling point.

• The Journal of the Korea Contents Association
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• v.15 no.5
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• pp.570-581
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• 2015

In recent years, many institutions predict that cloud services and big data will be popular IT trends in the near future. A number of leading IT vendors are focusing on practical solutions and services for cloud and big data. In addition, cloud has the advantage of unrestricted in selecting resources for business model based on a variety of internet-based technologies which is the reason that provisioning and virtualization technologies for active resource expansion has been attracting attention as a leading technology above all the other technologies. Big data took data prediction model to another level by providing the base for the analysis of unstructured data that could not have been analyzed in the past. Since what cloud services and big data have in common is the services and analysis based on mass amount of data, efficient operation and designing of mass data has become a critical issue from the early stage of development. Thus, in this paper, I would like to establish data processing architecture based on technological requirements of mass data for cloud and big data services. Particularly, I would like to introduce requirements that must be met in order for distributed file system to engage in cloud computing, and efficient compression technology requirements of mass data for big data and cloud computing in terms of cost-saving, as well as technological requirements of open-source-based system such as Hadoop eco system distributed file system and memory database that are available in cloud computing.

• Journal of the Korea Society of Computer and Information
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• v.25 no.11
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• pp.139-146
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• 2020

Cloud computing technology provides economic and efficient system operation and management features to deal with rapidly changing IT technologies. However, this is less used in institutes and companies due to low security of cloud computing service. It is recognized that storing and managing important information, which is confidential in external systems is vulnerable to security threats. In order to enhance security of this cloud computing service, this paper suggests a system and user authentication reinforcement model. The suggested technology guarantees integrity of user authentication information and provides users with convenience by creating blocks for each cloud service and connecting service blocks with chains. The block chain user authentication model offers integrity assurance technology of block chains and system access convenience for SSO users. Even when a server providing cloud computing is invaded, this prevents chained invasions not to affect other systems.

• Electronics and Telecommunications Trends
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• v.24 no.4
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• pp.41-54
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• 2009

인터넷 서비스 데이터량의 지속적인 증가로 대량의 원시 데이터로부터 정보를 가공 처리하는 과정, 체계화된 정보의 저장 관리 및 유용한 정보를 추출하기 위한 분석 등에 분산 컴퓨팅 기술을 적용하는 움직임이 활발히 진행되고 있다. 기존의 RDBMS 기술, MPI 분산 처리 기술 등은 대규모 데이터 처리 환경에 적용하기에는 운영 환경, 기능/성능면에서 확장성 혹은 고비용 문제가 따른다. 그러므로 저가의 서버들로 구성된 대규모 클러스터 환경을 기반으로 분산 컴퓨팅 기술을 적용한 새로운 시스템들이 대규모 데이터 처리를 요하는 인터넷 서비스 응용에 이용되고 있다. 이를 기반으로 바이오인포매틱스, 과학 시뮬레이션, 비즈니스 인텔리전스 등 다른 응용 영역으로 확대하여 클라우드 서비스로 제공하려는 비즈니스 모델이 제시되고 있다. 본 논문에서는 이와 같은 분산 컴퓨팅 기술을 적용한 대규모 데이터 저장 관리 및 처리 기술 동향을 조사하고 클라우드 기반 서비스로의 발전 방향을 서술한다.