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Anonymous authentication for circuits from correlation-relaxed two-to-one recoding

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Abstract

Anonymous authentication is very useful to protect the users’ identity privacy in distributed environment, such as in cloud computing. With the anonymous property, attribute-based signature (ABS) provides a cryptographic tool to construct a secure authentication scheme. In an attribute-based signature scheme, a signer owning a set of attributes is able to sign anonymously message with regarding to a policy, while the signatures are kept unforgeable even in the case of collusion. In this paper, we provide a novel construction of key-policy ABS for general circuits. Our construction is based on the correlation-relaxed two-to-one recoding (CR-TOR), which can be instantiated from the existence of multilinear maps. Due to the key indistinguishability property of the CR-TOR system, we prove that our scheme is selective unforgeability in the standard model under the k-Multilinear Computational Diffie-Hellman (k-MCDH) assumption. At the same time, the proposed scheme also holds the property of perfect privacy. Our framework based on CR-TOR leads to a circuit-ABS scheme that is conceptually different from the existing construction in the multilinear maps setting.

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Acknowledgments

This work has been supported by the National Natural Science Foundation of China (No. 61374180, 61373136, 61401226); the Research Foundation for Humanities and Social Sciences of Ministry of Education, China (No. 12YJAZH120, 14YJAZH023); the Natural Science Foundation of Universities of Jiangsu Province (No. 13KJB520005), the Innovation and Research Joint Funding of Jiangsu Province(No. BY2014038-03); the Changzhou Applied Basic Research projects (No. CJ20140040) and the Qinlan Projects of Jiangsu Province(No. KYQ14004), Fundamental Research Funds for the Central Universities (South China University of Technology)(No. 2014ZM0032).

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Jing, Z., Jiang, G., Gu, C. et al. Anonymous authentication for circuits from correlation-relaxed two-to-one recoding. J Ambient Intell Human Comput 7, 153–161 (2016). https://doi.org/10.1007/s12652-015-0306-7

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