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Towards Fully Homomorphic Encryption From Gentry-Peikert-Vaikuntanathan Scheme

机译:从绅士 - Peikert-Vaikuntanathan计划中完全同态加密

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Despite the convenience brought by cloud computing, internet users, meanwhile, are faced with risks of data theft, tampering, forgery, etc. Fully homomorphic encryption (FHE) has the ability to deal with the ciphertext directly, which can solve the problem of data security in cloud computing. Therefore, fully homomorphic encryption (FHE) has been widely used in cloud computing as well as multiparty computing, functional encryption and private information retrieval, etc. However, previous FHE schemes are based on standard (ring) learning with errors (LWE) assumption and the most typical schemes were created by Brakerski (CRYPTO2012) and Gentry-Sahai-Waters (GSW) (CRYPTO2013). Moreover, inspired by the work of Li et al. at ICPADS2016, they made use of Brakerski's scale-invariant technology and constructed a new FHE scheme with errorless key switching under Dual-First-is-errorless LWE (Dual-Ferr.LWE) problem. Hence, armed with Li et al.'s work, in this paper, we use Gentry-Peikert-Vaikuntanathan's scheme (i.e., under dual LWE assumption) as building block to construct a FHE scheme. Lastly, under the assumption of decisional learning with errors (LWE), we prove that our scheme is CPA (chosen-plaintext-attack) secure.
机译:尽管云计算所带来的便利性,同时互联网用户面临着数据被盗,篡改,伪造等的风险。完全同性恋加密(FHE)能够直接处理密文,这可以解决数据问题云计算中的安全性。因此,完全同性恋加密(FHE)已广泛用于云计算,以及多群计算,功能加密和私人信息检索等。然而,以前的FHE方案基于标准(环)学习,具有错误(LWE)假设和最典型的方案是由Brakerski(Crypto2012)和Gentry-Sahai-Waters(GSW)创建的方案(Crypto2013)。而且,受到李等人的作品的启发。在ICPADS2016,他们利用Brakerski的不变性技术,并在双重第一是无误的LWE(Dual-FERR.LWE)问题下的无误键切换构建了一种新的FHE方案。因此,与李等人联系起来。在本文中,我们使用Gentry-Peikert-Vaikuntanathan的计划(即双LWE假设)作为构建方案来构建FHE方案。最后,在判定果实学习的假设(LWE)的情况下,我们证明我们的计划是CPA(选定 - 明文攻击)安全。

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