【24h】

Selective Opening Security from Simulatable Data Encapsulation

机译:可用于可模拟数据封装的选择性开放安全性

获取原文

摘要

In the realm of public-key encryption, the confidentiality notion of security against selective opening (SO) attacks considers adversaries that obtain challenge ciphertexts and are allowed to adaptively open them, meaning have the corresponding message and randomness revealed. SO security is stronger than IND-CCA and often required when formally arguing towards the security of multi-user applications. While different ways of achieving SO secure schemes are known, as they generally employ expensive asymmetric building blocks like lossy trapdoor functions or lossy encryption, such constructions are routinely left aside by practitioners and standardization bodies. So far, formal arguments towards the SO security of schemes used in practice (e.g., for email encryption) are not known. In this work we shift the focus from the asymmetric to the symmetric building blocks of PKE and prove the following statement: If a PKE scheme is composed of a key encapsulation mechanism (KEM) and a blockcipher-based data encapsulation mechanism (DEM), and the DEM has specific combinatorial properties, then the PKE scheme offers SO security in the ideal cipher model. Fortunately, as we show, the required properties hold for popular modes of operation like CTR, CBC and COM. This paper not only establishes the corresponding theoretical framework of analysis, but also contributes very concretely to practical cryptography by concluding that selective opening security is given for many real-world schemes.
机译:在公钥加密的领域中,对选择性开放(SO)攻击的安全性概念认为取得挑战密文的对手,并且允许自适应地打开它们,这意味着具有相应的消息和随机性。因此,安全性强于IND-CCA,并且在正式争论多用户应用程序的安全性时通常需要。虽然已知不同的实现方式所以固定方案,但它们通常采用昂贵的不对称构建块,如损失的陷阱功能或有损加密,因此这些结构经常被从业者和标准化体留出。到目前为止,不知道在实践中使用的方案安全的正式论点(例如,用于电子邮件加密)。在这项工作中,我们将焦点从不对称的PKE的对称构建块转移,并证明了以下语句:如果PKE方案由密钥封装机制(KEM)和基于块的数据封装机制(DEM)组成,并且DEM具有特定的组合属性,然后PKE方案在理想的密码模型中提供了如此的安全性。幸运的是,正如我们所展示的那样,所需的属性适用于CTR,CBC和COM等流行的操作模式。本文不仅建立了相应的理论分析框架,而且通过结论为许多现实世界计划提供了选择性开放安全性,还贡献了实际密码。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号