一种基于服务器的语音情况下自动密码分析的ASR方法

L. A. Khan, M. S. Baig
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引用次数: 3

摘要

在文本数据的情况下,流密码中的密钥流重用一直是密码分析的焦点。我们在[1]中首次使用基于隐马尔可夫模型的语音识别方法对密钥流重用情况下加密的数字化语音信号进行密码分析。在本文中,我们扩展了[1]中提出的思想,并展示了不同语音识别架构在移动环境中的适用性,以自动恢复在同一密钥流下加密的数字化语音信号。基于服务器的自动语音识别(ASR)方法及其相关架构进行了调整,使其适用于我们的攻击。从声学前端的角度比较了网络语音识别(NSR)的两种主要实现架构,并对流加密数字化语音的两个时间板进行了自动密码分析。在传统的语音识别工具上对这两种体系结构进行了仿真实验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Server Based ASR Approach to Automated Cryptanalysis of Two Time Pads in Case of Speech
Keystream reuse in stream ciphers in case of textual data has been the focus of cryptanalysis for quite some time. The first ever use of hidden Markov models based speech recognition approach to cryptanalysis of encrypted digitized speech signals in a keystream reuse situation was presented by us in [1]. In this paper, we extend the idea presented in [1] and show the applicability of different speech recognition architectures in mobile environment to automatically recover the digitized speech signals encrypted under the same keystream. The server based automatic speech recognition (ASR) approach and its associated architectures are adapted to make them applicable in our attack. The two main implementation architectures of network speech recognition (NSR) from the acoustic front-end point of view are compared with respect to automated cryptanalysis of the two time pads of stream ciphered digitized speech. The simulation experiments performed on conventional speech recognition tools are presented for both the NSR architectures.
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