• Convergence Security Journal
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• v.24 no.2
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• pp.133-140
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• 2024

The spread of Direct-to-Consumer (DTC) genetic testing, where users request tests directly, has been increasing. With growing demand, certification systems have been implemented to grant testing qualifications to non-medical institutions, and the scope of tests has been expanded. However, unlike cases in less regulated foreign countries, disease-related tests are still excluded from the domestic regulations. The existing de-identification method does not adequately ensure the uniqueness and familial sharing of genomic information, limiting its practical utility. Therefore, this study proposes the application of fully homomorphic encryption in the analysis process to guarantee the usefulness of genomic information while minimizing the risk of leakage. Additionally, to safeguard the individual's right to self-determination, a privacy preservation model based on Opt-out is suggested. This aims to balance genomic information protection with maintainability of usability, ensuring the availability of information in line with the user's preferences.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.285-288
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• 2017

비식별화 모델은 데이터 공유를 위한 모델로 원본데이터를 비식별화 변환 처리하여 개인정보를 보호함과 동시에 분석에 필요한 데이터를 외부에 제공하는 모델로 연구되어 왔다. 변환 방법으로는 삭제, 일반화, 범주화 기술 등이 주로 사용되며 변환 과정 중에는 재식별 가능성을 최소화하기 위해 k-익명성, l-다양성, t-근접성 혹은 differential privacy 등의 프라이버시 모델이 적용되고 있다. 하지만 변환된 비식별 데이터 세트는 필연적으로 원본 데이터 세트와 다른 값을 가지며 이는 결과적으로 최종 분석 결과에 영향을 주게 된다. 이를 위해 두 데이터 세트 간의 차이를 상이도(dissimilarity) 혹은 정보 손실율(information loss)이라는 지표로 측정 하고 있으며 본 지표는 비식별 데이터의 활용성을 평가 하는 데에 매우 중요한 역할을 한다. 본 연구에서는 비식별 데이터와 원본 데이터와 간의 차이를 도메인 기반의 절대적인 기준대비로 표현한 상이도 측정 방법을 제안하며, 그 유효성을 실데이터 기반의 실험을 통해 검증하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.924-926
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• 2021

AI (Artificial Intelligence) is being utilized in various fields and services to give convenience to human life. Unfortunately, there are many security vulnerabilities in today's ML (Machine Learning) systems, causing various privacy concerns as some AI models need individuals' private data to train them. Such concerns lead to the interest in ML systems which can preserve the privacy of individuals' data. This paper introduces the latest research on various attacks that infringe data privacy and the corresponding defense techniques.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.1
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• pp.75-82
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• 2015

Recently, many public auditing schemes have been proposed to support public auditability that enables a third party auditor to verify the integrity of data stored in the remote cloud server. To improve the performance of the auditor, several public auditing schemes support batch auditing which allows the auditor to handle simultaneously multiple auditing delegations from different users. However, when even one data is corrupted, the batch auditing will fail and individual and repeated auditing processes will be required. It is difficult to identify the corrupted data from the proof in which distinct data blocks and authenticators of distinct users are intricately aggregated. In this paper, we extend a public auditing scheme of Wang et al. to support batch auditing for multi-cloud and multi-user. We propose an identification scheme of the corrupted cloud when the data of a single cloud is corrupted in the batch auditing of multi-cloud and multi-user.

• Journal of Digital Convergence
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• v.16 no.1
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• pp.159-164
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• 2018

Biometric information does not need to be stored separately, and there is no risk of loss and no theft. For this reason, it has been attracting attention as an alternative authentication means for existing authentication means such as passwords and authorized certificates. However, there may be a privacy problem due to leakage of personal information stored in the server. To overcome these weaknesses, FIDO solved the problem of leakage of personal information on the server by using biometric information stored on the user device and authenticating. In this paper, we propose a multiple biometric authentication method that can be used in FIDO environment. In order to utilize multiple biometric information, fingerprints and EEG signals can be generated and used in FIDO system. The proposed method can solve the problem due to limitations of existing 2-factor authentication system by authentication using multiple biometric information.

• Journal of the Korean Institute of Landscape Architecture
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• v.41 no.1
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• pp.82-92
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• 2013

This paper presents a landscape design proposal for the Kyeongsang National University Hospital in Changwon, Kyeongsangnam-do. The site is located at 555 Samjeongja-dong, Seongsan-gu, Changwon, Kyeongsangnam-do, and its area is approximately $79,743.1m^2$. The goal of the design was to create a landscape that helps the patients' recovery and public well-being as well as respects the surrounding environment. In order to achieve this goal, three design subjects were considered: maximizing the healing functions of the landscape, promoting ecologically regenerative landscape, and increasing the aesthetic value of the landscape based on the local context. For the healing aspect, first, therapeutic plants were carefully selected and various healing programs were introduced to the open space area such as the sensory garden, meditative space, the medicinal herb garden, outdoor acupressure treatment facilities, remedial playground etc. In addition, as the importance of patient's privacy is emphasized in research, the space and circulation patterns were divided according to the characteristics of the users. For ecological consideration, the design proposed to preserve and extend the existing ridgeline with pine forest, and recover the natural water system and recycle the water for the landscape management. For the aesthetic experience of the people, in contrast to the surrounding evergreen forest, diverse deciduous and flowering plants were introduced to arouse a sense of the season, and fruit bearing trees for wildlife to create a specific mood of being in nature so that people can listen to the songs of the birds and watch squirrels play etc. In addition, all the spaces and facilities were designed and placed according to universal design principles so that there would be no barrier for the patients to use them. Also, a sustainable management scheme was suggested to maintain the landscape in ecological and economical ways.

• The Transactions of the Korea Information Processing Society
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• v.13 no.7
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• pp.291-298
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• 2024

Despite its wide application, cloud computing raises privacy leakage concerns because users should send their private data to the cloud. Homomorphic encryption (HE) can resolve the concerns by allowing cloud servers to compute on encrypted data without decryption. However, due to the huge computation overhead of HE, simply executing an entire cloud program with HE causes significant computation. Manually partitioning the program and applying HE only to the partitioned program for the cloud can reduce the computation overhead. However, the manual code partitioning and HE-transformation are time-consuming and error-prone. This work proposes a new homomorphic encryption enabled annotation-guided code partitioning compiler, called Heapa, for privacy preserving cloud computing. Heapa allows programmers to annotate a program about the code region for cloud computing. Then, Heapa analyzes the annotated program, makes a partition plan with a variable list that requires communication and encryption, and generates a homomorphic encryptionenabled partitioned programs. Moreover, Heapa provides not only two region-level partitioning annotations, but also two instruction-level annotations, thus enabling a fine-grained partitioning and achieving better performance. For six machine learning and deep learning applications, Heapa achieves a 3.61 times geomean performance speedup compared to the non-partitioned cloud computing scheme.