基于小模舍入学习的(确定性)分层身份加密

Proceedings of the 11th ACM on Asia Conference on Computer and Communications Security Pub Date : 2016-05-30 DOI:10.1145/2897845.2897922

Fuyang Fang, Bao Li, Xianhui Lu, Yamin Liu, Dingding Jia, Haiyang Xue

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引用次数: 11

摘要

本文提出了一种基于小模数$q$上的舍入学习(LWR)问题的随机预估(RO)模型中的分层身份加密(HIBE)方案。与以往基于带错误学习(LWE)问题的HIBE方案相比，该方案的密文扩展比可以降低到1/2。然后，我们利用HIBE方案构造了一个基于小模数LWR问题的确定性分层身份加密(D-HIBE)方案。最后，利用二叉树加密技术(BTE)，在基于小模数LWR问题的标准模型中构造了HIBE和D-HIBE方案。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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(Deterministic) Hierarchical Identity-based Encryption from Learning with Rounding over Small Modulus

In this paper, we propose a hierarchical identity-based encryption (HIBE) scheme in the random oracle (RO) model based on the learning with rounding (LWR) problem over small modulus $q$. Compared with the previous HIBE schemes based on the learning with errors (LWE) problem, the ciphertext expansion ratio of our scheme can be decreased to 1/2. Then, we utilize the HIBE scheme to construct a deterministic hierarchical identity-based encryption (D-HIBE) scheme based on the LWR problem over small modulus. Finally, with the technique of binary tree encryption (BTE) we can construct HIBE and D-HIBE schemes in the standard model based on the LWR problem over small modulus.

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Proceedings of the 11th ACM on Asia Conference on Computer and Communications Security

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