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Semi-adaptive Attribute-Based Encryption and Improved Delegation for Boolean Formula

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Security and Cryptography for Networks (SCN 2014)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 8642))

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Abstract

We consider semi-adaptive security for attribute-based encryption, where the adversary specifies the challenge attribute vector after it sees the public parameters but before it makes any secret key queries. We present two constructions of semi-adaptive attribute-based encryption under static assumptions with short ciphertexts. Previous constructions with short ciphertexts either achieve the weaker notion of selective security, or require parameterized assumptions.

As an application, we obtain improved delegation schemes for Boolean formula with semi-adaptive soundness, where correctness of the computation is guaranteed even if the client’s input is chosen adaptively depending on its public key. Previous delegation schemes for formula achieve one of adaptive soundness, constant communication complexity, or security under static assumptions; we show how to achieve semi-adaptive soundness and the last two simultaneously.

The research leading to these results has received funding from the European Research Council under the European Community’s Seventh Framework Programme (FP7/2007-2013 Grant Agreement no. 339563 CryptoCloud). A longer version of this work appears in [11].

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Author information

Authors and Affiliations

  1. Department of Computer Science and Technology, East China Normal University, China

    Jie Chen

  2. École Normale Supérieure, Paris, France

    Hoeteck Wee

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  1. Jie Chen
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  2. Hoeteck Wee
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  1. École Normale Supérieure & CNRS, 45 rue d’Ulm, 75005, Paris, France

    Michel Abdalla

  2. Dipartimento di Informatica, Università di Salerno, via Ponte don Melillo, 84084, Fisciano, Italy

    Roberto De Prisco

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Chen, J., Wee, H. (2014). Semi-adaptive Attribute-Based Encryption and Improved Delegation for Boolean Formula. In: Abdalla, M., De Prisco, R. (eds) Security and Cryptography for Networks. SCN 2014. Lecture Notes in Computer Science, vol 8642. Springer, Cham. https://doi.org/10.1007/978-3-319-10879-7_16

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  • DOI: https://doi.org/10.1007/978-3-319-10879-7_16

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10878-0

  • Online ISBN: 978-3-319-10879-7

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