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New Circular Security Counterexamples from Decision Linear and Learning with Errors

机译:来自决策线性和学习的新循环安全监控器

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We investigate new constructions of n-circular counterexamples with a focus on the case of n = 2. We have a particular interest in what qualities a cryptosystem must have to be able to separate such circular security from IND-CPA or IND-CCA security. To start, we ask whether there is something special about the asymmetry in bilinear groups that is inherent in the works of [1,18] or whether it is actually the bilinearity that matters. As a further question, we explore whether such counterexamples are derivable from other assumptions such as the Learning with Errors (LWE) problem. If it were difficult to find such counterexamples, this might bolster our confidence in using 2-circular encryption as a method of bootstrapping Fully Homomorphic Encryption systems that are based on lattice assumptions. The results of this paper broadly expand the class of assumptions under which we can build 2-circular counterexamples. We first show for any constant k ≥ 2 how to build counterexamples from a bilinear group under the decision k-linear assumption. Recall that the decision k-linear assumption becomes progressively weaker as k becomes larger. This means that we can instantiate counterexamples from symmetric bilinear groups and shows that asymmetric groups do not have any inherently special property needed for this problem. We then show how to create 2-circular counterexamples from the Learning with Errors problem. This extends the reach of these systems beyond bilinear groups and obfuscation.
机译:我们调查N-CONDURING CONTEREXAMPLES的新建筑,重点是n = 2的案例。我们对密码系统必须能够从IND-CPA或IND-CCA安全性分离这种循环安全性的质量特别兴趣。要开始,我们询问是否存在关于[1,18]作品中固有的双线性群体中的不对称的特殊性,或者是否实际上是重要的。作为另一个问题,我们探讨了这些反例是从其他假设中衍生出来的,例如具有错误(LWE)问题的学习。如果难以找到这样的反例,这可能会使我们在使用基于晶格假设的完全同性恋加密系统的方法中的方法来加强我们对使用2循环加密的信心。本文的结果广泛地扩展了我们可以建立2圆形反例的假设类别。我们首先显示任何常数K≥2如何在决策k-linear假设下从双线性组构建每个副作用。回想一下,当k变大时,决定k-linear假设变得逐渐变弱。这意味着我们可以从对称Bilinear组实例化对称异常,并表明不对称组没有此问题所需的任何固有的特殊财产。然后,我们展示了如何使用错误问题从学习中创建2循环的反例。这扩展了这些系统的范围,超越双线性群体并混淆。

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