Privacy Preserving Calculation in Cloud using Fully Homomorphic Encryption with Table Lookup

研究成果: Conference contribution

抜粋

To protect data in cloud servers, fully homomorphic encryption (FHE) is an effective solution. In addition to encrypting data, FHE allows a third party to evaluate arithmetic circuits (i.e., computations) over encrypted data without decrypting it, guaranteeing protection even during the calculation. However, FHE supports only addition and multiplication. Functions that cannot be directly represented by additions or multiplications cannot be evaluated with FHE. A naïve implementation of such arithmetic operations with FHE is a bit-wise operation that encrypts numerical data as a binary string. This incurs huge computation time and storage costs, however. To overcome this limitation, we propose an efficient protocol to evaluate multi-input functions with FHE using a lookup table. We extend our previous work, which evaluates a single-integer input function, such as f(x). Our extended protocol can handle multi-input functions, such as f(x,y). Thus, we propose a new method of constructing lookup tables that can evaluate multi-input functions to handle general functions. We adopt integer encoding rather than bit-wise encoding to speed up the evaluations. By adopting both permutation operations and a private information retrieval scheme, we guarantee that no information from the underlying plaintext is leaked between two parties: a cloud computation server and a decryptor. Our experimental results show that the runtime of our protocol for a two-input function is approximately 13 minutes, when there are 8,192 input elements in the lookup table. By adopting a multi-threading technique, the runtime can be further reduced to approximately three minutes with eight threads. Our work is more practical than a previously proposed bit-wise implementation, which requires 60 minutes to evaluate a single-input function.

元の言語English
ホスト出版物のタイトル2020 5th IEEE International Conference on Big Data Analytics, ICBDA 2020
出版者Institute of Electrical and Electronics Engineers Inc.
ページ315-322
ページ数8
ISBN(電子版)9781728141114
DOI
出版物ステータスPublished - 2020 5
イベント5th IEEE International Conference on Big Data Analytics, ICBDA 2020 - Xiamen, China
継続期間: 2020 5 82020 5 11

出版物シリーズ

名前2020 5th IEEE International Conference on Big Data Analytics, ICBDA 2020

Conference

Conference5th IEEE International Conference on Big Data Analytics, ICBDA 2020
China
Xiamen
期間20/5/820/5/11

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Information Systems and Management
  • Statistics, Probability and Uncertainty

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  • これを引用

    Li, R., Ishimaki, Y., & Yamana, H. (2020). Privacy Preserving Calculation in Cloud using Fully Homomorphic Encryption with Table Lookup. : 2020 5th IEEE International Conference on Big Data Analytics, ICBDA 2020 (pp. 315-322). [9101276] (2020 5th IEEE International Conference on Big Data Analytics, ICBDA 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICBDA49040.2020.9101276