Towards protecting cyber-physical and IoT systems from single- and multi-order voice spoofing attacks
Towards protecting cyber-physical and IoT systems from single- and multi-order voice spoofing attacks
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DOI：
10.1016/j.apacoust.2021.108283
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发表时间：
2021-07-17
影响因子：
3.4
通讯作者：
Malik, Hafiz
中科院分区：
文献类型：
--
作者：
Javed, Ali;Malik, Khalid Mahmood;Malik, Hafiz
语音控制系统(VCS)、新型网络物理系统(CP)和物联网(IoT)设备越来越多地使用智能扬声器(如Google Home和Amazon Alexa)以及其他语音助手，以实现对家庭和办公室各种远程操作的管理。然而，在非网络环境中以及在多跳网络设置中，这些智能扬声器以及VCS容易受到各种语音欺骗攻击，即重放、克隆等。VCS上的这些不同的欺骗威胁迫切需要为能够检测各种语音欺骗攻击的VCS开发一种强大的欺骗对策。提出了一种利用具有Gammatone倒谱系数(GTCC)特征的新型声学三元模式(ATP)来对抗单跳和多跳网络环境中VCS的语音欺骗攻击的方法。我们的实验分析表明，所提出的ATP特征与GTCC相结合，可以有效地检测重放样本中的扭曲、克隆样本中存在的非自然韵律以及克隆重放样本中的重音和语调的扭曲和非自然模式。提出的ATP-GTCC特征被用来训练支持向量机以开发欺骗对策来满足所有可能的伪造。基于高度多样化的ASVspoof 2019和VSDC数据集的实验结果表明，所提出的对策对于可靠地检测一阶和二阶重放、克隆和克隆-重放攻击是有效的。(C)2021年爱思唯尔有限公司。保留所有权利。
Voice-controlled systems (VCSs), a new class of cyber-physical systems (CPS), and Internet of Things (IoT) devices are increasingly employing smart speakers such as Google Home and Amazon Alexa, and other voice assistants to enable management of various remote operations at home and offices. However, these smart speakers and hence VCSs are susceptible to various voice spoofing attacks i.e. replay, cloning, etc., in a non-network environment as well as in a multi-hop network setup. These diverse spoofing threats on VCSs require an urgent need to develop a robust spoofing countermeasure for VCSs capable of detecting a variety of voice spoofing attacks. This paper presents a spoofing countermeasure that uses novel acoustic ternary patterns (ATP) with Gammatone cepstral coefficients (GTCC) features to counter the voice spoofing attacks on VCSs in single- and multi-hop network environments. Our experimental analysis demonstrates that the proposed ATP features when combined with GTCC can effectively detect the distortions in replayed samples, unnatural prosody present in the cloned samples, and both distortions and unnatural patterns of stress and intonation in cloned-replay samples. The proposed ATP-GTCC features are used to train the SVM for development of a spoofing countermeasure to cater all possible forgeries. Experimental results based on highly diversified ASVspoof 2019 and VSDC datasets signify the effectiveness of the proposed countermeasure for reliable detection of 1st- and 2nd-order replay, cloning, and cloned-replay attacks. (C) 2021 Elsevier Ltd. All rights reserved.