A survey of voice and communication protection solutions against wiretapping

Ntantogian, Christoforos; Veroni, Eleni; Καρόπουλος, Γεώργιος; Xenakis, Christos

doi:10.1016/j.compeleceng.2019.05.008

Cited by 10 publications

(13 citation statements)

References 7 publications

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“…With the rapid development of information technology, speech transmission technology brings more and more convenience to people's life. As the main form of human communication, speech information is widely used for its real-time and easy identification [1][2][3]. Whether it is indoor communication or outdoor transmission, the process of sending and receiving speech information will inevitably be affected by the effect of multipath transmission [4].…”

Section: Introductionmentioning

confidence: 99%

An Efficient Convolutional Blind Source Separation Algorithm for Speech Signals under Chaotic Masking

et al. 2021

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As the main method of information transmission, it is particularly important to ensure the security of speech communication. Considering the more complex multipath channel transmission situation in the wireless communication of speech signals and separating or extracting the source signal from the convolutional signal are crucial steps in obtaining source information. In this paper, chaotic masking technology is used to guarantee the transmission safety of speech signals, and a fast fixed-point independent vector analysis algorithm is used to solve the problem of convolutional blind source separation. First, the chaotic masking is performed before the speech signal is sent, and the convolutional mixing process of multiple signals is simulated by impulse response filter. Then, the observed signal is transformed to the frequency domain by short-time Fourier transform, and instantaneous blind source separation is performed using a fast fixed-point independent vector analysis algorithm. The algorithm can preserve the high-order statistical correlation between frequencies to solve the permutation ambiguity problem in independent component analysis. Simulation experiments show that this algorithm can efficiently complete the blind extraction of convolutional signals, and the quality of recovered speech signals is better. It provides a solution for the secure transmission and effective separation of speech signals in multipath transmission channels.

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Section: Introductionmentioning

confidence: 99%

An Efficient Convolutional Blind Source Separation Algorithm for Speech Signals under Chaotic Masking

et al. 2021

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“…As a result, secret calls need to be implemented by end‐to‐end voice encryption schemes. [6] But during the over‐the‐air transmission stage, only the signals with speech characteristics can pass through the vocoders located at the mobile terminals and the base stations. [1] Therefore, the encrypted voice data that lose speech characteristics needs to be transmitted over the voice channels of cellular mobile networks by the data over voice (DoV) technique.…”

Section: Introductionmentioning

confidence: 99%

“…[1] Therefore, the encrypted voice data that lose speech characteristics needs to be transmitted over the voice channels of cellular mobile networks by the data over voice (DoV) technique. [6] In a regular implementation of DoV, data are modulated into speech‐like signals and transmitted over voice channels of cellular mobile networks transparently in camouflage, which would be demodulated at the receiving end. For convenience of description, the voice channels of cellular mobile networks will be referred to as voice channels in the following.…”

Section: Introductionmentioning

confidence: 99%

“…[7] These reconstructed speech signals just sound like the original ones, but have inevitable waveform distortions. [7] At the same time, in order to improve the voice channel efficiency, techniques such as voice activation detection (VAD), discontinuous transmission (DTX), noise cancellation and echo cancellation are widely employed in vocoders, [1, 6] which will further aggravate the signals' waveform distortions or even suppress their transmission. Thus, there are two important issues to address in order to implement DoV.…”

Section: Introductionmentioning

confidence: 99%

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A universal data transfer technique over voice channels of cellular mobile communication networks

Zhang

2020

IET Communications

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A universal technique for transmitting data over voice (DoV) links that can be applied to various cellular networks is proposed. In the scheme, a generic modulation model is established based on waveform symbol mapping, where the data to be transmitted are mapped into finite waveform symbols of a codebook generated offline and demodulated with soft decision results at the receiving end. To make the proposed scheme applicable to various kinds of cellular networks, first sinusoidal signals are selected to synthesise waveform symbols due to their stable transmission characteristics over various voice channels. Then, an analytical method based on Surface Packing is proposed to optimise modulation codebooks. Finally, the target demodulation codebook is obtained through learning from the modulation codebook online. Simulation results show that the proposed scheme performs well over voice channels with different vocoders and has low symbol error rate on various vocoders. Compared with previous schemes designed for some specific vocoders in global system for mobile communication (GSM), the proposed scheme can extend the application scope of DoV to cross‐network scenarios consisting of GSM, universal mobile telecommunications system (UMTS) and long‐term evolution (LTE).

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“…With the rapid development of information technology, voice transmission technology introduces an increasing amount of convenience to people's live. As the main form of human communication, a voice message is used for its strong realtime performance and easy identification [1]- [3]. Whether it is indoor or outdoor transmission, the transmission and reception of voice information will inevitably be affected by the multipath transmission effect [4], that is, after a voice message was sent, it needs to reach the receiver end via multiple transmission paths.…”

Section: Introductionmentioning

confidence: 99%

Blind Source Separation Algorithm for Chaotic Masking Multipath Signals Based on Spectral Peak Search Counter Permutation

Guo

et al. 2020

IEEE Access

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Since voice communication is the main method of information transmission, it is important to ensure the safety and efficiency of voice communication. In this paper, a more complex multipath channel model in a wireless environment is considered, and chaotic masking technology is used to ensure the security of voice signal transmission. Based on this, a multipath blind source separation algorithm based on cross-correlation permutation of spectral peak search counters is proposed. First, chaotic masking is performed between multiple voice signals and chaotic signal, and an impulse response filter is used to simulate the multipath transmission process. Next, the short-time Fourier transform is employed to convert the observation signal into a frequency-domain signal. Then, the joint approximate diagonalization of eigenmatrix algorithm is used to perform linear instantaneous blind source separation at each frequency. And to solve the permutation uncertainty problem in the frequency domain method, a cross-correlation permutation algorithm based on a spectral peak search counter is proposed. Finally, the permuted signal is transformed back to the time domain to get the estimated source signal by the inverse short-time Fourier transform. And simulation experiments show that the algorithm greatly reduces the calculation amount of the autocorrelation coefficient in the traditional permutation algorithm. Moreover, the permutation algorithm has stability and accuracy, and provides a solution for the secure transmission and effective separation of voice signals in multipath transmission channels. INDEX TERMS Chaotic masking, convolutive mixture blind source separation, cross-correlation permutation, short-time Fourier transform.

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A survey of voice and communication protection solutions against wiretapping

Cited by 10 publications

References 7 publications

An Efficient Convolutional Blind Source Separation Algorithm for Speech Signals under Chaotic Masking

An Efficient Convolutional Blind Source Separation Algorithm for Speech Signals under Chaotic Masking

A universal data transfer technique over voice channels of cellular mobile communication networks

Blind Source Separation Algorithm for Chaotic Masking Multipath Signals Based on Spectral Peak Search Counter Permutation

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