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이광규 (사)디지털산업정보학회 2022 디지털산업정보학회논문지 Vol.18 No.3
DID(Decentralized Identity Identification) is a system in which users voluntarily manage their identity, etc., and control the scope and subject of submission of identity information based on a block chain. In the era of the 4th industrial revolution, where the importance of protecting personal information is increasing day by day, DID will surely be positioned as the industrial center of the Internet and e-business. However, when managing personal information, DID is highly likely to cause a large amount of personal information leakage due to electronic infringement, such as hacking and invasion of privacy caused by the concentration of user's identity information on global service users. Therefore, there are a number of challenges to be solved before DID settles into a stable standardization. Therefore, in this paper, we try to examine what problems exist in order to positively apply the development of DID technology, and analyze the improvement plan to become a stable service in the future.
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스마트폰을 이용한 영지식증명 블록체인 개인정보 인증에 관한 연구
이광규 (사)디지털산업정보학회 2023 디지털산업정보학회논문지 Vol.19 No.3
In the future society, a means to verify the identity of the information owner is required at the beginning of most services that the information owner encounters, and the emergence and gradual spread of digital identification that proves the identity of the information owner is essential. In addition, as the utilization value of personal information increases, discussions on how to provide personal information are active. Therefore, there is a need for a personal information management method necessary for building a hyper-connected society that is safe from various hacking, forgery, alteration, and theft by allowing the owner to directly manage and provide personal information management. In this study, a decentralized identity information management model that overcomes the problems and limitations of the centralized identity management method of personal information and manages and selectively provides personal information by the information owner himself and implemented a smart personal information provision system(SPIPS: Smart Personal Information Provision System) using a smartphone.
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이광규 한국전기전자학회 2019 전기전자학회논문지 Vol.23 No.2
The FCM algorithm finds the optimal solution through iterative optimization technique. In particular, there is adifference in execution time depending on the initial center of clustering, the location of noise, the location and numberof crowded densities. However, this method gradually updates the center point, and the center of the initial cluster isshifted to one side. In this paper, we propose a TI-FCM(Triangular Inequality-Fuzzy C-Means) clustering algorithm thatdetermines the cluster center density by maximizing the distance between clusters using triangular inequality. Theproposed method is an effective method to converge to real clusters compared to FCM even in large data sets. Experiments show that execution time is reduced compared to existing FCM. FCM 알고리즘은 반복 최적화 기법을 통해 최적해를 찾는다. 특히, 클러스터링 초기 중심과 잡음의 위치, 몰려있는 밀도의위치, 개수에 따라 실행시간 차이가 난다. 하지만 이 방법은 중심점을 점차 갱신해 나가는 방법으로 초기 클러스터 중심이한 쪽으로 치우치게 되고 클러스터링 결과의 편차가 심해 클러스터링 대푯값의 신뢰도가 떨어진다. 따라서 본 논문에서는 삼각부등식을 이용하여 클러스터 간 거리를 최대한 멀어지게 하여 클러스터 중심 밀도를 결정하는 TI-FCM(TriangularInequality-Fuzzy C-Means:삼각부등식-FCM)클러스터링 알고리즘을 제안한다. 제안된 방법은 대용량의 빅데이터에서도FCM에 비해 실제 클러스터에 수렴하는 효과적인 방법이고 실험을 통해 기존 FCM보다 실행시간이 감소됨을 보였다
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