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The Filter-Combiner Model for Memoryless Synchronous Stream Ciphers

机译:无记忆同步流密码的滤波器组合模型

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摘要

We introduce a new model - the Filter-Combiner model -for memoryless synchronous stream ciphers. The new model combines the best features of the classical models for memoryless synchronous stream ciphers - the Nonlinear-Combiner model and the Nonlinear-Filter model. In particular, we show that the Filter-Combiner model provides key length optimal resistance to correlation attacks and eliminates weaknesses of the NF model such as the the Anderson leakage and the Inversion Attacks. Further, practical length sequences extracted from the Filter-Combiner model cannot be distinguished from true random sequences based on linear complexity test. We show how to realise the Filter-Combiner model using Boolean functions and cellular automata. In the process we point out an important security advantage of sequences obtained from cellular automata over sequences obtained from LFSRs.
机译:我们引入了一种新模型-Filter-Combiner模型-用于无内存同步流密码。新模型结合了无记忆同步流密码经典模型的最佳功能-Nonlinear-Combiner模型和Nonlinear-Filter模型。特别是,我们证明了Filter-Combiner模型为关联攻击提供了最佳的密钥长度抵抗能力,并消除了NF模型的弱点,例如安德森泄漏和反演攻击。此外,基于线性复杂度测试,无法将从Filter-Combiner模型提取的实际长度序列与真正的随机序列区分开。我们展示了如何使用布尔函数和元胞自动机来实现Filter-Combiner模型。在此过程中,我们指出了从细胞自动机获得的序列相对于从LFSR获得的序列的重要安全优势。

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