Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Yongha Son"'
Publikováno v:
BMC Medical Genomics, Vol 13, Iss S7, Pp 1-12 (2020)
Abstract Background One of three tasks in a secure genome analysis competition called iDASH 2018 was to develop a solution for privacy-preserving GWAS computation based on homomorphic encryption. The scenario is that a data holder encrypts a number o
Externí odkaz:
https://doaj.org/article/7194f7ee8a4d4336a2262e6ad8baba08
Publikováno v:
IEEE Access, Vol 7, Pp 50595-50604 (2019)
HElib is a C++ library that implements fully homomorphic encryption (FHE). This supports homomorphic linear transformations on plaintext slots which consist of many rotation operations on plaintext slots, and currently, each rotation involves one or
Externí odkaz:
https://doaj.org/article/85aacd45a7da42aeadf6d30c2cae5506
Publikováno v:
IEEE Access, Vol 7, Pp 89497-89506 (2019)
The dual attack is one of the most efficient attack algorithms for learning with errors (LWE) problem. Recently, an efficient variant of the dual attack for sparse and small secret LWE was reported by Albrecht (Eurocrypt 2017), which forces some LWE-
Externí odkaz:
https://doaj.org/article/ddec110cef8f41b693d9e375721ed922
Publikováno v:
BMC Medical Genomics, Vol 13, Iss S7, Pp 1-12 (2020)
BMC Medical Genomics
BMC Medical Genomics
Background One of three tasks in a secure genome analysis competition called iDASH 2018 was to develop a solution for privacy-preserving GWAS computation based on homomorphic encryption. The scenario is that a data holder encrypts a number of individ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0e28e039d3e456332bb138d7ee740ebe
http://link.springer.com/article/10.1186/s12920-020-0722-1
http://link.springer.com/article/10.1186/s12920-020-0722-1
Autor:
David Froelicher, Wonhee Cho, Nicolas Gama, Duhyeong Kim, Miran Kim, Arif Harmanci, Jean-Pierre Hubaux, Jean-Philippe Bossuat, Sergiu Carpov, Mariya Georgieva, Yongha Son, Kristin E. Lauter, Seungwan Hong, Lucila Ohno-Machado, Yongsoo Song, Yiping Ma, Ilaria Chillotti, Jung Hee Cheon, Juan Ramón Troncoso-Pastoriza, Heidi J. Sofia, Xiaoqian Jiang
Genotype imputation is a fundamental step in genomic data analysis such as GWAS, where missing variant genotypes are predicted using the existing genotypes of nearby ‘tag’ variants. Imputation greatly decreases the genotyping cost and provides hi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::64c02307c3c5e996b072e05ece34cf97
https://doi.org/10.1101/2020.07.02.183459
https://doi.org/10.1101/2020.07.02.183459
Publikováno v:
IEEE Access, Vol 7, Pp 50595-50604 (2019)
HElib is a C++ library that implements fully homomorphic encryption (FHE). This supports homomorphic linear transformations on plaintext slots which consist of many rotation operations on plaintext slots, and currently, each rotation involves one or
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5e3b52c5a8051f1c152700f24b32741f
https://doi.org/10.1109/access.2019.2911300
https://doi.org/10.1109/access.2019.2911300
Publikováno v:
IEEE Access, Vol 7, Pp 89497-89506 (2019)
The dual attack is one of the most efficient attack algorithms for learning with errors (LWE) problem. Recently, an efficient variant of the dual attack for sparse and small secret LWE was reported by Albrecht (Eurocrypt 2017), which forces some LWE-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4e25ae21d004683a23c366734bd832b6
https://doi.org/10.1109/access.2019.2925425
https://doi.org/10.1109/access.2019.2925425
Publikováno v:
PLoS ONE
Protecting patients’ privacy is one of the most important tasks when developing medical artificial intelligence models since medical data is the most sensitive personal data. To overcome this privacy protection issue, diverse privacy-preserving met
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cba51d948fc7971fc6ed8d659d1ee771
https://doi.org/10.1371/journal.pone.0260681
https://doi.org/10.1371/journal.pone.0260681
Autor:
Yongha Son, Jung Hee Cheon
Publikováno v:
WAHC@CCS
In the practical use of the Learning With Error (LWE) based cryptosystems, it is quite common to choose the secret to be extremely small: one popular choice is ternary ((±1,0),coefficient vector, and some further use ternary vector having only small
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0f3fe001d1156f8b28d041fc3da5faf1
https://doi.org/10.1145/3338469.3358941
https://doi.org/10.1145/3338469.3358941
Publikováno v:
Information Security and Cryptology – ICISC 2016 ISBN: 9783319531762
ICISC
ICISC
The Learning with Errors $$\textsf {LWE}$$ problem has been widely used as a hardness assumption to construct public-key primitives. In this paper, we propose an efficient instantiation of a PKE scheme based on LWE with a sparse secret, named as $$\t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2fc98c4d2697384082789006a682b79f
https://doi.org/10.1007/978-3-319-53177-9_3
https://doi.org/10.1007/978-3-319-53177-9_3