Yunhee Kang

Prof. Dr. Yunhee Kang

Baekseok university
orcid

Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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27 September 2021 in Applied Sciences
Verified
Journal Article
Open access
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YKYunhee Kang
Yunhee Kang
JCJaehyuk Cho
Jaehyuk Cho
YPYoung B. Park
Young B. Park
The Conventional Cloud Common Data Model (CDM) uses a centralized method of user identification and credentials. This needs to be solved in a decentralized way because there are limitations in interoperability such as closed identity management and identity leakage. In this paper, we propose a DID (Decentralized Identifier)-based cloud CDM that allows researchers to securely store medical research information by authenticating their identity and to access the CDM reliably. The proposed service model is used to provide the credential of the researcher in the process of creating and accessing CDM data in the designed secure cloud. This model is designed on a DID-based user-centric identification system to support the research of enrolled researchers in a cloud CDM environment involving multiple hospitals and laboratories. The prototype of the designed model is an extension of the encrypted CDM delivery method using DID and provides an identification system by limiting the use cases of CDM data by researchers registered in cloud CDM. Prototypes built for agent-based proof of concept (PoC) are leveraged to enhance security for researcher use of ophthalmic CDM data. For this, the CDM ID schema and ID definition are described by issuing IDs of CDM providers and CDM agents, limiting the IDs of researchers who are CDM users. The proposed method is to provide a framework for integrated and efficient data access control policy management. It provides strong security and ensures both the integrity and availability of CDM data.

29 September 2022 in Applied Sciences
Verified
Journal Article
Open access
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YKYunhee Kang
Yunhee Kang
YPYoung B. Park
Young B. Park
Public healthcare has transformed from treatment to preventive care and disease management. The Common Data Model (CDM) provides a standard data structure defined to utilize hospitals’ data. Digital identity takes a significant role as the body of information about an individual used by computer systems to identify and establish trust among organizations. The CDM research network, composed of users handling medical information, has several digital identities associated with their activity. A high central authority cost can be reduced by Distributed Ledger Technology (DLT). It enables users to control their identities independently of a third party. To preserve the privacy of researchers in clinical studies, secure identification is the main concern of identifying the researcher and its agents. To do so, they should pose a legally verifiable credential in the cloud CDM. By presenting the proof represented by the capability that the user has, each identity has access control that is linked to an authentication credential that the cloud CDM can verify. Assurance in one’s identity is confirmed by asserting claims with the identity and its capability, providing its verifiable credential to the authentication entity in the cloud CDM. This paper describes the user-centric claim-based identity operation model based on use cases to handle researcher identity in the cloud CDM. In this model, credentials are designed as a capability and presented to them to access SPs in the cloud CDM. To provide well-controlled access control in the cloud CDM, we build and prototype a capability based CDM management system.

13 October 2020 in Applied Sciences
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Journal Article
Open access
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JCJaehyuk Cho
Jaehyuk Cho
YKYunhee Kang
Yunhee Kang
YPYoung B. Park
Young B. Park
The Common Data Model (CDM) is being used to deal with problems caused by the various electronic medical record structures in the distributed hospital information system. The concept of CDM is emerging as a collaborative method of exchanging data from each hospital in the same format and conducting various clinical studies based on shared data. The baseline of a CDM system is centralized with an infrastructure typically controlled by a single entity with full authority. The characteristics of this centralized system can pose serious security issues. Therefore, the proposed SC-CDM system is designed as a platform for distributed ledger and provides data with a high level of confidentiality, security, and scalability. This framework provides a reference model that supports multiple channels, using secure CDM as an encryption method. The data confidentiality of CDM is guaranteed by asymmetric and symmetric protocols. Delivering CDM is protected by a symmetric key signed by the CDM creator and maintains lightweight distributed ledger transactions on Inter Planetary File System (IPFS), which acts as a file share. To deliver an encrypted CDM on the SC-CDM platform, the CDM is encrypted with a block cipher by a random symmetric key and Initialization Vector (IV). The symmetric key protocol is used for the fast encryption of large-capacity data. The SC-CDM is implemented the repository with IPFS for storing the encrypted CDM, in which symmetric key, two hash values, and IV are shared through blockchain. Data confidentiality of SC-CDM is guaranteed by only registered users accessing the data. In conclusion, the SC-CDM is the first approach to demultiplexing with the data confidentiality proof based on asymmetric key cryptography. We analyze and verify the security of SC-CDM by comparing qualitative factors and performance with existing CDM. Moreover, we adopt a byte-level processing method with encryption to ensure efficiency while handling a large CDM.

31 July 2022 in Journal of Digital Contents Society
Verified
Journal Article
Open access
MHMyoung-Woo Hong
Myoung-Woo Hong
YKYunhee Kang
Yunhee Kang

31 December 2013 in The Journal of Korean Institute of Information Technology
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Journal Article
Closed access
YKYunhee Kang
Yunhee Kang

29 January 2026 in Journal of Web Engineering
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Journal Article
Open access
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DHDongNyeong Heo
DongNyeong Heo
YKYunhee Kang
Yunhee Kang
CHChul Heo
Chul Heo
HCHeeyoul Choi
Heeyoul Choi
KJKyounghun Jung
Kyounghun Jung
It is challenging to understand Literary Sinitic text from the Joseon dynasty, since there is a lack of explicit word separators, which creates significant semantic ambiguity. To address this, both sentence segmentation and named entity recognition (NER) are essential. We propose a Transformer-based analyzer that performs these two tasks simultaneously. Trained on a labeled corpus from the Seungjeongwon Ilgi, our model effectively segments sentences and identifies named entities, thereby significantly improving the understanding of sentence structure and overall context.