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Kim, Miran (김미란)

Department
Department of Computer Science and Engineering(컴퓨터공학과)
Website
https://sites.google.com/site/mirankim0618
Lab
Applied Cryptography Lab. (암호랩)
Research Keywords
암호론, 동형암호, 다자간 연산, 안전한 유전자 분석, 안전한 인공지능, Cryptology, Homomorphic Encryption, Multi-Party Computation, Secure Genome Analysis, Privacy-Preserving Artificial Intelligence
Research Interests
Our main field of research is secure computation, which aims to develop advanced cryptographic primitives to protect sensitive data of individuals. In particular, we are interested in "Homomorphic Encryption" which is an encryption scheme that allows for operations on encrypted inputs without decryption. Currently, we are working on the development of privacy-preserving protocols in a wide range of applications such as genome analysis and machine learning (action/face/voice recognition).
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Issue DateTitleAuthor(s)TypeViewAltmetrics
2020-12A secure system for genomics clinical decision supportKarimi, Seemeen; Jiang, Xiaoqian; Dolin, Robert H., et alARTICLE15 A secure system for genomics clinical decision support
2020-07Semi-Parallel logistic regression for GWAS on encrypted dataKim, Miran; Song, Yongsoo; Li, Baiyu, et alARTICLE16 Semi-Parallel logistic regression for GWAS on encrypted data
2020-07SCOR: A secure international informatics infrastructure to investigate COVID-19Raisaro, J L; Marino, Francesco; Troncoso-Pastoriza, Juan, et alARTICLE15 SCOR: A secure international informatics infrastructure to investigate COVID-19
2020-01Secure and Differentially Private Logistic Regression for Horizontally Distributed DataKim, Miran; Lee, Junghye; Ohno-Machado, Lucila, et alARTICLE433 Secure and Differentially Private Logistic Regression for Horizontally Distributed Data
2019-01SecureLR: Secure Logistic Regression Model via a Hybrid Cryptographic ProtocolJiang, Yichen; Hamer, Jenny; Wang, Chenghong, et alARTICLE17 SecureLR: Secure Logistic Regression Model via a Hybrid Cryptographic Protocol
2018-10Logistic regression model training based on the approximate homomorphic encryptionKim, Andrey; Song, Yongsoo; Kim, Miran, et alARTICLE43 Logistic regression model training based on the approximate homomorphic encryption
2018-04Secure Logistic Regression Based on Homomorphic Encryption: Design and EvaluationKim, Miran; Song, Yongsoo; Wang, Shuang, et alARTICLE20 Secure Logistic Regression Based on Homomorphic Encryption: Design and Evaluation
2017Secure searching of biomarkers through hybrid homomorphic encryption schemeKim, Miran; Song, Yongsoo; Cheon, Jung HeeARTICLE22 Secure searching of biomarkers through hybrid homomorphic encryption scheme
2016-01Optimized Search-and-Compute Circuits and Their Application to Query Evaluation on Encrypted DataCheon, Jung Hee; Kim, Miran; Kim, MyungsunARTICLE22 Optimized Search-and-Compute Circuits and Their Application to Query Evaluation on Encrypted Data
2016-01HEALER: homomorphic computation of ExAct Logistic rEgRession for secure rare disease variants analysis in GWASWang, Shuang; Zhang, Yuchen; Dai, Wenrui, et alARTICLE17 HEALER: homomorphic computation of ExAct Logistic rEgRession for secure rare disease variants analysis in GWAS
2015-12Private genome analysis through homomorphic encryptionKim, Miran; Kristin LauterARTICLE16 Private genome analysis through homomorphic encryption

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