New Techniques for Efficient Trapdoor Functions and Applications

New Techniques for Efficient Trapdoor Functions and Applications
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高效活板门功能和应用的新技术

DOI:
10.1007/978-3-030-17659-4_2
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发表时间:
2019
期刊:
Theor. Comput. Sci.
影响因子:
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通讯作者:
Mohammad Hajiabadi
Mohammad Hajiabadi
中科院分区:
--
文献类型:
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作者:
Sanjam Garg;Romain Gay;Mohammad Hajiabadi

文献摘要

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我们开发的技术,用于构建陷门函数(TDFs)与短的图像大小和先进的安全性能。我们的方法建立在Garg和Hajiabadi的最新框架上[CHTPTO 2018]。作为我们技术的应用,我们得到 基于计算Diffie-Hellman(CDH)假设的块源输入的确定性加密方案的第一个构造(对于CPA和CCA情况)。此外,通过应用我们的效率增强技术,我们得到了基于CDH的方案与密文大小的线性明文大小。 有损TDFs的第一个构造基于判定Diffie-Hellman(DDH)假设,图像大小与输入大小成线性关系,同时保留[Peikert-Waters STOC 2008]的损失率。
We develop techniques for constructing trapdoor functions (TDFs) with short image size and advanced security properties. Our approach builds on the recent framework of Garg and Hajiabadi [CRYPTO 2018]. As applications of our techniques, we obtain The first construction of deterministic-encryption schemes for block-source inputs (both for the CPA and CCA cases) based on the Computational Diffie-Hellman (CDH) assumption. Moreover, by applying our efficiency-enhancing techniques, we obtain CDH-based schemes with ciphertext size linear in plaintext size. The first construction of lossy TDFs based on the Decisional Diffie-Hellman (DDH) assumption with image size linear in input size, while retaining the lossiness rate of [Peikert-Waters STOC 2008].