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XSX: Lightweight Encryption for Data Warehousing Environments

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Big Data Analytics and Knowledge Discovery (DaWaK 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9829))

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Abstract

The use of data security solutions like encryption significantly reduces database performance in data-intensive processing environments such as Data Warehouses. To overcome this issue this paper proposes a transparent lightweight encryption technique based on alternating sequences of eXclusive Or (XOR) and bit switching operations. The technique aims to achieve high performance while providing significant levels of security strength, attaining better security-performance tradeoffs than most commercial encryption solutions and those proposed by the research community. The experimental evaluation conducted using the TPC-DS benchmark shows that the proposed technique adds lower database performance overhead when comparing with the AES standard encryption algorithm and with other encryption solutions such as OPES, Salsa20, TEA and SES-DW.

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Author information

Authors and Affiliations

  1. CISUC – Centre of Informatics and Systems of the University of Coimbra FCTUC – University of Coimbra, 3030-290, Coimbra, Portugal

    Ricardo Jorge Santos, Marco Vieira & Jorge Bernardino

  2. ISEC – Superior Institute of Engineering of Coimbra Polytechnic of Coimbra, 3030-190, Coimbra, Portugal

    Jorge Bernardino

Authors
  1. Ricardo Jorge Santos
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  2. Marco Vieira
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  3. Jorge Bernardino
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Corresponding author

Correspondence to Jorge Bernardino .

Editor information

Editors and Affiliations

  1. University of Science and Technology , Rolla, Missouri, USA

    Sanjay Madria

  2. Osaka University , Osaka, Japan

    Takahiro Hara

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© 2016 Springer International Publishing Switzerland

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Santos, R.J., Vieira, M., Bernardino, J. (2016). XSX: Lightweight Encryption for Data Warehousing Environments. In: Madria, S., Hara, T. (eds) Big Data Analytics and Knowledge Discovery. DaWaK 2016. Lecture Notes in Computer Science(), vol 9829. Springer, Cham. https://doi.org/10.1007/978-3-319-43946-4_19

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  • DOI: https://doi.org/10.1007/978-3-319-43946-4_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-43945-7

  • Online ISBN: 978-3-319-43946-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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