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An approach to resist blind source separation attacks of speech signals

机译：一种抵抗语音信号盲源分离攻击的方法

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摘要

Recently, there has been great interest in the physical layer security technique which exploits the artificial noise (AN) to enlarge the channel condition between the legitimate receiver and the eavesdropper. However, in certain communication scenery, this strategy may suffer from some attacks in the signal processing perspective. In this paper, we consider speech signals and the scenario in which the eavesdropper has the similar channel performance compared to the legitimate receiver. We design the optimal artificial noise (AN) to resist the attack of the eavesdropper who uses the blind source separation (BSS) technology to reconstruct the secret information. The Optimal AN is obtained by making a tradeoff between results of direct eavesdropping and reconstruction. The simulation results show that the AN we proposed has better performance than that of the white Gaussian AN to resist the BSS attacks effectively.
机译：近来，对物理层安全技术引起了极大的兴趣，该技术利用人工噪声（AN）扩大了合法接收者和窃听者之间的信道条件。但是，在某些通信环境中，此策略可能会在信号处理方面遭受一些攻击。在本文中，我们考虑了语音信号以及窃听者与合法接收者相比具有相似信道性能的场景。我们设计了最佳的人工噪声（AN），以抵抗窃听者的攻击，窃听者使用盲源分离（BSS）技术来重建秘密信息。通过在直接窃听和重建的结果之间进行权衡，可以获得最佳AN。仿真结果表明，本文提出的AN具有比白高斯AN更好的抗BSS攻击性能。

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