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International Conference on Security and Cryptography for Networks

SCN 2014: Security and Cryptography for Networks pp 298–317Cite as

Expressive Attribute-Based Encryption with Constant-Size Ciphertexts from the Decisional Linear Assumption

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

Abstract

We propose a key-policy attribute-based encryption (KP-ABE) scheme with constant-size ciphertexts, whose selective security is proven under the decisional linear (DLIN) assumption in the standard model. The proposed scheme also has semi-adaptively security, which is a recently proposed notion of security. The access structure is expressive, that is given by non-monotone span programs. It also has fast decryption, i.e., a decryption includes only a constant number of pairing operations. As an application of our KP-ABE construction, we also propose a fully secure attribute-based signatures with constant-size secret (signing) keys from the DLIN. For achieving the above results, we employ a hierarchical reduction technique on dual pairing vector spaces and a modified form of pairwise independence lemma specific to our proposed schemes.

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Author information

Authors and Affiliations

  1. Mitsubishi Electric, 5-1-1 Ofuna, Kamakura, Kanagawa, 247-8501, Japan

    Katsuyuki Takashima

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  1. Katsuyuki Takashima
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Editor information

Editors and Affiliations

  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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Takashima, K. (2014). Expressive Attribute-Based Encryption with Constant-Size Ciphertexts from the Decisional Linear Assumption. 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_17

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  • DOI: https://doi.org/10.1007/978-3-319-10879-7_17

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10878-0

  • Online ISBN: 978-3-319-10879-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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