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2015 | OriginalPaper | Buchkapitel

Attribute-Based Encryption Resilient to Auxiliary Input

verfasst von : Zhiwei Wang, Siu Ming Yiu

Erschienen in: Provable Security

Verlag: Springer International Publishing

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Abstract

The auxiliary input model defines a class of computationally uninvertible function families \(\mathcal {F}\) to simulate a large class of leakage. Such a function \(f\in \mathcal {F}\) can information-theoretically reveal the entire secret key SK, but it is still computationally infeasible to recover SK from f(SK). That means SK can be used for multiple tasks, since SK doesn’t need to be continually refreshed. We propose the first CP-ABE scheme based on linear secret sharing schemes, that can tolerate leakage on master key and attribute-based secret keys with auxiliary input(AI). For the security proof of our scheme, we present three modified assumptions in composite order bilinear groups, and prove their hardness. Under these modified assumptions, our scheme can be proved AI-CPA secure in the standard model. Finally, we devise a key-policy ABE scheme also resilient to auxiliary input.

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Vorheriges Kapitel Efficient Unconditionally Secure Comparison and Privacy Preserving Machine Learning Classification Protocols

Nächstes Kapitel On Provable Security of wPRF-Based Leakage-Resilient Stream Ciphers

Nur mit Berechtigung zugänglich

“non-negligible probability” means that the probability cannot be ignored.

The definitions of normal and semi-functional are only for proof, and they are not concerned with construction.

The access structure \(\mathbb {A}\) is a monotone collection of non-empty of subsets of \(\varSigma \).

\(\bar{j}\) is used to index the attributes set and the secret key.

If the key is generated randomly, then \(k_A\) equals the length of secret key.

\(g(k_A)\) is a non-negligible probability function.

In the auxiliary model, any hard-to-invert function \(f\in \mathcal {F}\) can hardly recover a secret key SK even the min-entropy of SK is 0.

\(\mathbb {S}\) is a subset of number set \(\varSigma \).

Since each attribute is mapped to a random number in \(\mathbb {Z}_N\), \(\rho \) can be defined as \(\rho : \mathbb {Z}_N^l\rightarrow \varSigma \).

Here, each attribute is mapped to a random number in \(\mathbb {Z}_N\).

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Titel: Attribute-Based Encryption Resilient to Auxiliary Input
verfasst von: Zhiwei Wang
Siu Ming Yiu
Verlag: Springer International Publishing
Buch: Provable Security
Print ISBN: 978-3-319-26058-7

Electronic ISBN: 978-3-319-26059-4

Copyright-Jahr: 2015
DOI: https://doi.org/10.1007/978-3-319-26059-4_21

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