@inproceedings{101a512bdb6e4319a097c38e5b371cfe,
title = "Secure statistical analysis using RLWE-based homomorphic encryption",
abstract = "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.{\textquoteright}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.",
keywords = "Homomorphic encryption, Packing methods, Ring-LWE assumption, Secure covariance and correlation",
author = "Masaya Yasuda and Takeshi Shimoyama and Jun Kogure and Kazuhiro Yokoyama and Takeshi Koshiba",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 20th Australasian Conference on Information Security and Privacy, ACISP 2015 ; Conference date: 29-06-2015 Through 01-07-2015",
year = "2015",
doi = "10.1007/978-3-319-19962-7_27",
language = "English",
isbn = "9783319199610",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "471--487",
editor = "Ernest Foo and Douglas Stebila",
booktitle = "Information Security and Privacy - 20th Australasian Conference, ACISP 2015, Proceedings",
}