• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1157-1169
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• 2021

The disaster recovery refers to policies and procedures to ensure continuity of services and minimize loss of resources and finances in case of emergency situations such as natural disasters. In particular, the disaster recovery method by the cloud service provider has advantages such as management flexibility, high availability, and cost effectiveness. However, this method has a dependency on a service provider and has a structural limitation in which a user cannot be involved in personal data. In this paper, we propose a protocol using proxy re-encryption for data confidentiality by removing dependency on service providers by backing up user data using blockchain and distributed storage. The proposed method is implemented in Ethereum and IPFS environments, and presents the performance and cost required for backup and recovery operations.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.11
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• pp.305-310
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• 2021

Artificial intelligence technology in the medical field initially focused on analysis and algorithm development, but it is gradually changing to web application development for service as a product. This paper describes a Urinary Stone segmentation model in abdominal CT images and an artificial intelligence web application based on it. To implement this, a model was developed using U-Net, a fully-convolutional network-based model of the end-to-end method proposed for the purpose of image segmentation in the medical imaging field. And for web service development, it was developed based on AWS cloud using a Python-based micro web framework called Flask. Finally, the result predicted by the urolithiasis segmentation model by model serving is shown as the result of performing the AI web application service. We expect that our proposed AI web application service will be utilized for screening test.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.2
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• pp.43-50
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• 2022

As the use of mobile data increases, the proportion of video content is increasing steeply. In order to solve problems that arise when mobile users receive data from geographically remote cloud servers, methods of caching data in advance to edge servers geographically close to the users are attracting lots of attention. In this paper, we present a caching policy that stores data on Small Cell Base Station(SBS) to effectively provide content files to mobile users by applying a delayed offloading scheme in a cellular network. The goal of the proposed policy is to minimize the size of data transmitted from Macro Base Station(MBS) because the delayed offloading scheme requires more cost than when downloaded from MBS than from SBS. The caching policy is proposed to determine the size of content file and which content file to be cached to SBS using the probability of mobile users' paths and the popularity of content files, and to replace content files in consideration of the overlapping coverage of SBS. In addition, through performance evaluation, it has been proven that the proposed policy reduces the size of data downloaded from MBS compared to other algorithms.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.6
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• pp.189-196
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• 2023

Today, in the era of the 4th industrial revolution based on the paradigm of hyper-connectivity, super-intelligence, and superconvergence, the remote work environment is becoming central based on technologies such as mobile, cloud, and big data. This remote work environment has been accelerated by the demand for non-face-to-face due to COVID-19. Since the remote work environment can perform various tasks by accessing services and resources anytime and anywhere, it has increased work efficiency, but has caused a problem of incapacitating the traditional boundary-based network security model by making the internal and external boundaries ambiguous. In this paper, we propse a method to improve the limitations of the traditional boundary-oriented security strategy by building a security model centered on core components and their relationships based on the zero trust idea that all actions that occur in the network beyond the concept of the boundary are not trusted.

• KNOM Review
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• v.22 no.1
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• pp.1-10
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• 2019

The process to determine the required number of resources depends on the factors being considered. Autoscaling is one such mechanism that uses a wide range of factors to decide and is a critical process in NFV. As the networks are being shifted onto the cloud after the invention of SDN, we require better resource managers in the future. To solve this problem, we propose a solution that allows the VNFMs to autoscale the system resources depending on the factors such as overhead of hyperthreading, number of requests, execution-times for the virtual network functions. It is a known fact that the hyperthreaded virtual-cores are not fully capable of performing like the physical cores. Also, as there are different types of core having different frequencies so the process to calculate the number of cores needs to be measured accurately and precisely. The platform independency is achieved by proposing another solution in the form of a monitoring microservice, which communicates through APIs. Hence, by the use of our autoscaling application and a monitoring microservice, we enhance the resource provisioning process to meet the criteria of future networks.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.222-227
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• 2022

In this paper, we implemented a Korean text generation and classification model based on a deep learning algorithm that can be applied to various industries. It consists of two implemented GAN-based Korean handwriting generation models and CNN-based Korean handwriting classification models. The GAN model consists of a generator model for generating fake Korean handwriting data and a discriminator model for discriminating fake handwritten data. In the case of the CNN model, the model was trained using the 'PHD08' dataset, and the learning result was 92.45. It was confirmed that Korean handwriting was classified with % accuracy. As a result of evaluating the performance of the classification model by integrating the Korean cursive data generated through the implemented GAN model and the training dataset of the existing CNN model, it was confirmed that the classification performance was 96.86%, which was superior to the existing classification performance.

• Convergence Security Journal
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• v.23 no.1
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• pp.109-115
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• 2023

The future outlook for defense faces various and challenging environments such as the acceleration of uncertainty in the global security landscape and limitations in domestic social and economic conditions. In response, the Ministry of National Defense seeks to address the problems and threats through defense innovation based on scientific and technological advancements such as artificial intelligence, drones, and robots. To introduce advanced AI-based technology, it is essential to integrate and utilize data on IT environments such as cloud and 5G. However, existing traditional security policies face difficulties in data sharing and utilization due to mainly system-oriented security policies and uniform security measures. This study proposes a paradigm shift to a data value-based security policy based on theoretical background on data valuation and life-cycle management. Through this, it is expected to facilitate the implementation of scientific and technological innovations for national defense based on data-based task activation and new technology introduction.

• Journal of Internet of Things and Convergence
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• v.9 no.3
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• pp.21-26
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• 2023

The development and distribution approach of applications is transitioning from a monolithic architecture to microservices and containerization, a lightweight virtualization technology, is becoming a core IT technology. However, unlike traditional virtual machines based on hypervisors, container technology does not provide concrete security boundaries as it shares the same kernel. According to various preceding studies, there are many security vulnerabilities in most container images that are currently shared. Accordingly, attackers may attempt exploitation by using security vulnerabilities, which may seriously affect the system environment. Therefore, in this study, we propose an efficient automated deployment pipeline design to prevent the distribution of container images with security vulnerabilities, aiming to provide a secure container environment. Through this approach, we can ensure a safe container environment.

• Design Convergence Study
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• v.15 no.2
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• pp.237-250
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• 2016

Along with rapid development, progress of the network technology and digital information technology, human are stepping into the intelligent society of internet. Thereby the quality of living environment and working environment are keep improving. Under the big background of internet era, the timeliness and convenience of smart home system has been improved greatly. While lots of smart products have gradually penetrated into people's daily life. The household appliances are among most popular ones. This paper is intended to compare smart features of household living products among most representative brands in China, Japan and South Korea. The smart features include self-learning, self-adapting, self-coordinating, self-diagnosing, self-inferring, self-organizing, and self adjusting. As result, most smart features of these products showed great similarity. While some features were dominated according to countries such as remote control feature in Korea, energy saving feature in Japan, and one button operation feature in China.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.480-480
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• 2021

본 연구에서는 도시재생지역의 재난재해 위험성 및 회복성 분석과 현황 분석을 위한 기초 데이터의 관리와 활용성 증대를 목적으로 데이터를 등록하고 다운로드 할 수 있는 공유 플랫폼을 개발하고자 하였다. 도시재생 데이터 플랫폼은 재난재해, 지역현황, 문서 항목으로 구분하여 도시재생 정보를 서비스한다. 재난재해 항목은 폭우, 폭설, 폭염, 강풍, 지진 5개 자연재해 유형과 이로 인해 추가 피해가 발생할 수 있는 화재, 붕괴, 폭발 사회재난 3개 유형으로 구성되어있으며, 총8 종류의 재난재해 유형에 대한 위험성과 회복성 분석 DB를 제공한다. 지역현황 정보에서는 유휴공간 및 지역자산정보 등 도시재생 현황분석에 필요한 행정(통계)데이터, 시설물정보 등을 제공한다. 아울러 본 연구를 통해 산출되는 논문 및 보고서 등을 문서 항목에서 서비스한다. 데이터셋 등록 시, 시스템에 설정된 재난재해 유형, 시설물 등을 선택해 카테고리를 분류하고, 이력관리를 목적으로 데이터명과 생산년월 등에 대한 필수항목을 입력해야만 등록이 가능하도록 설정하였다. 또한 GIS 기반 공간자료 등록 시에는 가시화 서비스를 위하여 공간자료의 포맷과 좌표체계, 생산년월, 생산기관 등을 필수 입력하도록 하였으며, GIS tool을 활용한 자료 분석에 어려움이 없도록 하였다. 쇠퇴지역의 재난재해 대비/대응을 위한 도시재생 데이터 플랫폼은 금년 시범운영 후, 차년에는 클라우드 서비스 기능을 탑재해 계정 권한과 장소에 제약을 받지 않고 도시재생 업무를 수행하는 모든 사용자가 재난재해 정보를 비롯한 도시재생 관련 정보를 수집·활용할 수 있는 데이터 공유의 장을 구현함으로써 도시재생지역의 효과적인 재난재해 대비/대응 체계를 마련하고자 하였다.