Abstract

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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