TY - GEN
T1 - Secure statistical analysis using RLWE-based homomorphic encryption
AU - Yasuda, Masaya
AU - Shimoyama, Takeshi
AU - Kogure, Jun
AU - Yokoyama, Kazuhiro
AU - Koshiba, Takeshi
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - Homomorphic encryption enables various calculations while preserving the data confidentiality. Here we apply the homomorphic encryption scheme proposed by Brakerski and Vaikuntanathan (CRYPTO 2011) to secure statistical analysis between two variables. For reduction of ciphertext size and practical performance, we propose a method to pack multiple integers into a few ciphertexts so that it enables efficient computation over the packed ciphertexts. Our packing method is based on Yasuda et al.’s one (DPM 2013). While their method gives efficient secure computation only for small integers, our modification is effective for larger integers. Our implementation shows that our method is faster than the state-of-the-art work. Specifically, for one million integers of 16 bits (resp. 128 bits), it takes about 20 minutes (resp. 3.6 hours) for secure covariance and correlation on an Intel Core i7-3770 3.40 GHz CPU.
AB - Homomorphic encryption enables various calculations while preserving the data confidentiality. Here we apply the homomorphic encryption scheme proposed by Brakerski and Vaikuntanathan (CRYPTO 2011) to secure statistical analysis between two variables. For reduction of ciphertext size and practical performance, we propose a method to pack multiple integers into a few ciphertexts so that it enables efficient computation over the packed ciphertexts. Our packing method is based on Yasuda et al.’s one (DPM 2013). While their method gives efficient secure computation only for small integers, our modification is effective for larger integers. Our implementation shows that our method is faster than the state-of-the-art work. Specifically, for one million integers of 16 bits (resp. 128 bits), it takes about 20 minutes (resp. 3.6 hours) for secure covariance and correlation on an Intel Core i7-3770 3.40 GHz CPU.
UR - http://www.scopus.com/inward/record.url?scp=84947223941&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84947223941&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-19962-7_27
DO - 10.1007/978-3-319-19962-7_27
M3 - Conference contribution
AN - SCOPUS:84947223941
SN - 9783319199610
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 471
EP - 487
BT - Information Security and Privacy - 20th Australasian Conference, ACISP 2015, Proceedings
A2 - Foo, Ernest
A2 - Stebila, Douglas
PB - Springer Verlag
T2 - 20th Australasian Conference on Information Security and Privacy, ACISP 2015
Y2 - 29 June 2015 through 1 July 2015
ER -