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The Impact of Applications on Mathematics pp 85–95Cite as

Cryptographic Technology for Benefiting from Big Data

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Part of the book series: Mathematics for Industry ((MFI,volume 1))

Abstract

“Big Data” technology is the process of collecting and storing large amounts and wide varieties of data sets, and extracting valuable information and/or knowledge by analyzing them. Big Data analytics plays an important role in improving business services and quality of life. However, Big Data might include personal information such as credit card data, health-related data, purchasing history, geographic location data, etc. In Big Data analytics, the data sets may be accessed not only by the data holders but also by the third parties. This indicates a potential privacy breach. In addition, when public cloud is used as a platform of Big Data analytics, the risk of privacy breach might further increase. To protect against such threats, it is desirable to develop encryption schemes which are as efficient as possible and encryption schemes which allow to perform computations on encrypted data without decrypting it. In this paper, we present some of the latest results of our research related to the above challenge for Big Data security and privacy.

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Acknowledgments

The authors would like to thank the anonymous reviewers for their careful reading of our manuscript and their many constructive comments and suggestions to improve the quality of the paper. A part of this work has been supported by Ministry of Internal Affairs and Communications of the Japanese Government.

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Authors and Affiliations

  1. Yokohama Research Laboratory, Hitachi, Ltd., 292, Yoshida-cho, Totsuka-ku, Yokohama, Kanagawa, 244-0817, Japan

    Keisuke Hakuta & Hisayoshi Sato

Authors
  1. Keisuke Hakuta
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  2. Hisayoshi Sato
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Corresponding author

Correspondence to Keisuke Hakuta .

Editor information

Editors and Affiliations

  1. Institute for Mathematics and Industry, Kyushu University, Fukuoka, Japan

    Masato Wakayama

  2. CSIRO (Commonwealth Scientific and Industrial Research Organisation), Canberra, Aust Capital Terr, Australia

    Robert S. Anderssen

  3. School of Mathematical Sciences, Fudan University, Shanghai, China

    Jin Cheng

  4. Kyushu University, Fukuoka, Japan

    Yasuhide Fukumoto

  5. Institute of Natural and Mathematical Sciences, Massey University, Palmerston North, Auckland, New Zealand

    Robert McKibbin

  6. Institute of Mathematics, Free University of Berlin, Berlin, Germany

    Konrad Polthier

  7. Kyushu University, Fukuoka, Japan

    Tsuyoshi Takagi

  8. Department of Mathematics, National University of Singapore, Singapore, Singapur, Singapore

    Kim-Chuan Toh

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© 2014 Springer Japan

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Hakuta, K., Sato, H. (2014). Cryptographic Technology for Benefiting from Big Data. In: Wakayama, M., et al. The Impact of Applications on Mathematics. Mathematics for Industry, vol 1. Springer, Tokyo. https://doi.org/10.1007/978-4-431-54907-9_6

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  • DOI: https://doi.org/10.1007/978-4-431-54907-9_6

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  • Publisher Name: Springer, Tokyo

  • Print ISBN: 978-4-431-54906-2

  • Online ISBN: 978-4-431-54907-9

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