A Defense Method Based on a Novel Replay Attack

Juan Guo, Liang Chen, Haoran Sun, Aidong Xu, Zeguang Li, Yinwei Zhao, Yixin Jiang, Tengyue Zhang, Yunan Zhang
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引用次数: 1

Abstract

Replay attack is a common attack model, and we propose a novel voice replay attack against intelligent voice assistants. This is a speaker array-based attack method that modulates the attack commands onto a high-frequency carrier and uses the nonlinear self-demodulation of the speaker array and air to produce speech commands audible to the human ear that which confirm can be executed by a voice smart assistance. In this paper, a novel voice replay attack against intelligent voice assistants is proposed by characterizing the speech attack and non-attack signals generated by the loudspeaker arrays and analyze their amplitude and frequency characteristics. We also propose and validate a software defense method based on machine learning and neural networks, and the results show that the method is effective.
一种基于新型重放攻击的防御方法
语音重放攻击是一种常见的攻击模型,本文提出了一种针对智能语音助手的语音重放攻击方法。这是一种基于扬声器阵列的攻击方法,它将攻击命令调制到高频载波上,并利用扬声器阵列和空气的非线性自解调产生人耳可听的语音命令,这些语音命令确认可以由语音智能辅助执行。本文通过对扬声器阵列产生的语音攻击和非攻击信号进行表征,分析其幅值和频率特征,提出了一种针对智能语音助手的语音重放攻击方法。提出并验证了一种基于机器学习和神经网络的软件防御方法,结果表明该方法是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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