Secure Computation

Secure computation is a technology that enables computation while keeping data encrypted. In the modern data analysis process, the data is transferred to, stored in, and computed by the server. During these three processes, a typical encryption protects the data only when it is transferred and stored. In contrast, secure computation protects the data during the whole processes: the data is kept secret even while it is computed. Therefore, secure computation not only prevents data leakage but also enables us to operate an analytical system that deals highly sensitive data, such as personal data and companies’ trade secrets, without data being disclosed. As a result, secure computation provides a novel analysis with integration of multiple data beyond the boundaries of companies and industries, as well as it provides highly secure data processing.

NTT’s secure computation uses secret sharing scheme that conforms to the ISO international standards as its encryption mechanism, and multiparty computation techniques based on the secret sharing scheme. Multiparty computation performs secure data processing while the data is encrypted by performing special cryptographic operations and exchanging encrypted data among multiple servers according to preliminarily defined procedures. All through these procedures, the data is processed in an encrypted fashion: each server only has a piece of the data called a share in the context of secret sharing scheme. Therefore, no server can obtain information about the data. Furthermore, we have achieved highly efficient data processing in secure computation, which is nearly as efficient as an ordinary (non-encrypted) data processing is.

San-Shi, the secure computation system developed by NTT, consists of three or four servers and a client that registers data via secret sharing scheme and instructs the servers to analyze the data. By using San-Shi, you can securely compute and obtain basic statistics and cross tabulation, etc. Furthermore, San-Shi provides a secure data integration by using a special secure table-join algorithm so you can perform a cross-section analysis of multiple data.

For further information about our secure computation, please see the downloadable material.

Secure Computation System
Secure Computation System


Promotion Videos

Related Articles

  • Naoto Kiribuchi, Dai Ikarashi, Koki Hamada, and Ryo Kikuchi: "MEVAL3: A Library for Programmable Secure Computation," Symposium on Cryptography and Information Security (SCIS), 2018.
  • Koki Hamada, Satoshi Hasegawa, Kazuharu Misawa, Koji Chida, Soichi Ogishima, and Masao Nagasaki: "Privacy-Preserving Fisher's Exact Test for Genome-Wide Association Study," International Workshop on Genome Privacy and Security (GenoPri), 2017.
  • Eizen Kimura, Koki Hamada, Ryo Kikuchi, Koji Chida, Kazuya Okamoto, Shirou Manabe, Tomohiro Kuroda, Yasushi Matsumura, Toshihiro Takeda, and Naoki Mihara: "Evaluation of Secure Computation in a Distributed Healthcare Setting," Medical Informatics Europe (MIE) 2016: 152-156.
  • Koji Chida, Gembu Morohashi, Hitoshi Fuji, Fumihiko Magata, Akiko Fujimura, Koki Hamada, Dai Ikarashi, Ryuichi Yamamoto: "Implementation and evaluation of an efficient secure computation system using 'R' for healthcare statistics," J Am Med Inform Assoc. 21, pp.326-331, 2014.
  • Satoshi Tanaka, Yutaka Abe, Satoshi Takahashi, Ryo Kikuchi, Atsushi Doi, Koji Chida, and Kiyomi Shirakawa: "Secure statistical computation system on encrypted data: An empirical study of secure regression analysis for official statistics," UNECE Work session on Statistical Data Confidentiality (SDC), 2017.
  • Koji Chida, Daniel Genkin, Koki Hamada, Dai Ikarashi, Ryo Kikuchi, Yehuda Lindell, Ariel Nof: "Fast Large-Scale Honest-Majority MPC for Malicious Adversaries," the 38th International Cryptology Conference (CRYPTO), 2018.
  • Dai Ikarashi, Ryo Kikuchi, Koki Hamada, and Koji Chida: "Actively Private and Correct MPC Scheme in t<n/2 from Passively Secure Schemes with Small Overhead," Cryptology IACR Cryptology ePrint Archive, 2014.
  • Ryo Kikuchi, Dai Ikarashi, Takahiro Matsuda, Koki Hamada, Koji Chida: "Efficient Bit-Decomposition and Modulus-Conversion Protocols with an Honest Majority," The 23rd Australasian Conference on Information Security and Privacy (ACISP), 2018.
  • Dai Ikarashi, Koki Hamada, Ryo Kikuchi, Koji Chida: "A Design and an Implementation of Super-high-speed Multi-party Sorting:The Day When Multi-party Computation Reached Scripting Languages," Computer Security Symposium (CSS), 2016 (Best Paper Award).
  • Naoto Kiribuchi, Dai Ikarashi, Gembu Morohashi, and Koki Hamada: "An Efficient Equi-join Algorithm for Secure Computation and Its Implementation toward Secure Comprehensive Analyses of Users' Attribute and History Information," Computer Security Symposium (CSS), 2016 (Best Paper Award).
  • Dai Ikarashi, Ryo Kikuchi, Katsumi Takahashi: "MEVAL2 vs. CCS Best paper on MPC-AES,"Symposium on Cryptography and Information Security (SCIS), 2017 (SCIS Innovation Paper Award).
  • Ryo Kikuchi, Koji Chida, Dai Ikarashi, Wakaha Ogata, Koki Hamada, Katsumi Takahashi: "Secret sharing with share-conversion: Achieving small share-size and extendibility to multiparty computation," IEICE Transactions, 98-A(1):213-222, 2015.

Related Information