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Selective All-Or-Nothing Transform: Protecting Outsourced Data Against Key Exposure

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Cyberspace Safety and Security (CSS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 11161))

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Abstract

This paper presents the selective all-or-nothing transform (SAONT). It addresses the needs of users who would like to use inexpensive cloud storage services, but do not trust their providers. Encrypted data are transformed and separated into a small private fragment kept on the user’s device and a large public fragment which can be securely uploaded to a public cloud since decryption of the public fragment is infeasible without the private fragment. Therefore, outsourced data are protected even in a situation of key exposure. SAONT reduces performance overhead by combining block-wise fragmentation of a ciphertext with an application of an all-or-nothing transform only on a subset of the ciphertext.

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Notes

  1. 1.

    https://www.bloomberg.com/news/features/2017-09-29/the-equifax-hack-has-all-the-hallmarks-of-state-sponsored-pros.

  2. 2.

    https://en.wikipedia.org/wiki/Facebook-Cambridge_Analytica_data_scandal.

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Authors and Affiliations

  1. LTCI, Telecom ParisTech, Paris, France

    Katarzyna Kapusta & Gerard Memmi

Authors
  1. Katarzyna Kapusta
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  2. Gerard Memmi
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Corresponding author

Correspondence to Katarzyna Kapusta .

Editor information

Editors and Affiliations

  1. University of Salerno, Fisciano, Italy

    Arcangelo Castiglione

  2. University Politehnica of Bucharest, Bucharest, Romania

    Florin Pop

  3. University of Campania “L. Vanvitelli”, Caserta, Italy

    Massimo Ficco

  4. University of Salerno, Fisciano, Italy

    Francesco Palmieri

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Kapusta, K., Memmi, G. (2018). Selective All-Or-Nothing Transform: Protecting Outsourced Data Against Key Exposure. In: Castiglione, A., Pop, F., Ficco, M., Palmieri, F. (eds) Cyberspace Safety and Security. CSS 2018. Lecture Notes in Computer Science(), vol 11161. Springer, Cham. https://doi.org/10.1007/978-3-030-01689-0_15

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  • DOI: https://doi.org/10.1007/978-3-030-01689-0_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-01688-3

  • Online ISBN: 978-3-030-01689-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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