Approximate Homomorphic Encryption
Approximate Homomorphic Encryption is a type of homomorphic encryption scheme that enables computation on encrypted data while permitting small, controlled approximation errors in the decrypted results, distinguishing it from exact homomorphic encryption methods by prioritizing efficiency and scalability for applications such as privacy-preserving machine learning.
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Logistic regression model training based on the approximate homomorphic encryption
Andrey Kim, Yongsoo Song, Miran Kim et al. · BMC Medical Genomics · 2018 · 199 citations · Full text
Wonkyung Jung, Sangpyo Kim, Jung Ho Ahn et al. · IACR Transactions on Cryptographic Hardware and Embedded Systems · 2021 · 153 citations · Full text
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Seoul National University
Seoul, South Korea
7 h-index
30 publications
3.6K citations
Samsung (South Korea)
Seoul, South Korea
3 h-index
8 publications
2.3K citations
National University of Singapore
Singapore, Singapore
2 h-index
3 publications
293 citations

Chosun University
Gwangju, South Korea
2 h-index
3 publications
453 citations
University of California San Diego
San Diego, United States
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4 publications
454 citations

Ewha Womans University
Seoul, South Korea
1 h-index
1 publications
67 citations

Centre National de la Recherche Scientifique
Paris, France
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2 publications
874 citations
Microsoft (United States)
Redmond, United States
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1 publications
32 citations
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Repository · 4 publications · 112 citations
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