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Public key encryption with conjunctive keyword search on lattice

机译:基于格的联合关键字搜索的公钥加密

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摘要

Outsourcing data in cloud storage is gaining popularity recently. For protecting data privacy, the data should be encrypted, and it is thus critical to provide search services for encrypted outsourced data. However, it becomes a problem about how to retrieve encrypted data while protecting data privacy at the same time. Therefore, public key encryption with keyword search (PEKS) is proposed. Nevertheless, the majority of the existing PEKS schemes are based on bilinear mappings and do not provide quantum security. Although some lattice-based PEKS schemes have been proposed, they cannot support conjunctive keyword search. In this paper, we first propose a public key encryption with conjunctive keyword search (PECK) using lattices. Our PECK scheme provides efficient search over encrypted data containing multiple keywords for a single data user. To support multiple data users, a multi-user PECK scheme is also presented. The two schemes are proved secure against indistinguishable chosen keyword attacks (IND-CKA) based on learning with errors (LWE) problem in the random oracle model. Finally, we provide performance evaluation of our proposed scheme by theoretical analysis and experimental simulation.
机译:云存储中的数据外包最近变得越来越流行。为了保护数据私密性,应该对数据进行加密,因此为加密的外包数据提供搜索服务至关重要。但是,这成为如何在保护数据隐私的同时如何检索加密数据的问题。因此,提出了利用关键字搜索(PEKS)的公共密钥加密。尽管如此,大多数现有的PEKS方案都基于双线性映射,并且不提供量子安全性。尽管已经提出了一些基于点阵的PEKS方案,但是它们不能支持联合关键字搜索。在本文中,我们首先提出一种使用格网的联合关键字搜索(PECK)进行公钥加密的方法。我们的PECK方案可为单个数据用户高效地搜索包含多个关键字的加密数据。为了支持多个数据用户,还提出了一种多用户PECK方案。基于随机预言模型中的带错误学习(LWE)问题,证明了这两种方案对于不可区分的选择关键字攻击(IND-CKA)是安全的。最后,我们通过理论分析和实验仿真对提出的方案进行性能评估。

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