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\(\mathsf {ELSA}\): Efficient Long-Term Secure Storage of Large Datasets

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Information Security and Cryptology – ICISC 2018 (ICISC 2018)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 11396))

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Abstract

An increasing amount of information today is generated, exchanged, and stored digitally. This also includes long-lived and highly sensitive information (e.g., electronic health records, governmental documents) whose integrity and confidentiality must be protected over decades or even centuries. While there is a vast amount of cryptography-based data protection schemes, only few are designed for long-term protection. Recently, Braun et al. (AsiaCCS’17) proposed the first long-term protection scheme that provides renewable integrity protection and information-theoretic confidentiality protection. However, computation and storage costs of their scheme increase significantly with the number of stored data items. As a result, their scheme appears suitable only for protecting databases with a small number of relatively large data items, but unsuitable for databases that hold a large number of relatively small data items (e.g., medical record databases).

In this work, we present a solution for efficient long-term integrity and confidentiality protection of large datasets consisting of relatively small data items. First, we construct a renewable vector commitment scheme that is information-theoretically hiding under selective decommitment. We then combine this scheme with renewable timestamps and information-theoretically secure secret sharing. The resulting solution requires only a single timestamp for protecting a dataset while the state of the art requires a number of timestamps linear in the number of data items. We implemented our solution and measured its performance in a scenario where 12 000 data items are aggregated, stored, protected, and verified over a time span of 100 years. Our measurements show that our new solution completes this evaluation scenario an order of magnitude faster than the state of the art.

This work has been co-funded by the DFG as part of project S6 within CRC 1119 CROSSING. This is the proceedings version as published at ICISC’18. An extended version can be found at arXiv.org [8].

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Authors and Affiliations

  1. TU Darmstadt, Darmstadt, Germany

    Matthias Geihs & Johannes Buchmann

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  1. Matthias Geihs
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  2. Johannes Buchmann
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Correspondence to Matthias Geihs .

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  1. Sejong University, Seoul, Korea (Republic of)

    Kwangsu Lee

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Geihs, M., Buchmann, J. (2019). \(\mathsf {ELSA}\): Efficient Long-Term Secure Storage of Large Datasets. In: Lee, K. (eds) Information Security and Cryptology – ICISC 2018. ICISC 2018. Lecture Notes in Computer Science(), vol 11396. Springer, Cham. https://doi.org/10.1007/978-3-030-12146-4_17

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  • DOI: https://doi.org/10.1007/978-3-030-12146-4_17

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  • Online ISBN: 978-3-030-12146-4

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