Search

With the increasing popularity of smart devices, users can control their mobile phones, TVs, cars, and smart furniture by using voice assistants, but voice assistants are susceptible to intrusion by outsider speakers or playback attacks. In order to address this security issue, a millimeter-wave radar-based voice security authentication system is proposed in this paper. First, the speaker's fine-grained vocal cord vibration signal is extracted by eliminating static object clutter and motion effects; second, the weighted Mel Frequency Cepstrum Coefficients (MFCCs) are obtained as biometric features; and finally, text-independent security authentication is performed by the WMHS (Weighted MFCCs and Hog-based SVM) method. This system is highly adaptable and can authenticate designated speakers, resist intrusion by other unspecified speakers as well as playback attacks, and is secure for smart devices. Extensive experiments have verified that the system achieves a 93.4% speaker verification accuracy and a 5.8% miss detection rate for playback attacks. [ABSTRACT FROM AUTHOR]

The positioning of indoor electronic devices is an essential part of human–computer interaction, and the accuracy of positioning affects the level of user experience. Most existing methods for RF-based device localization choose to ignore or remove the impact of multipath effects. However, exploiting the multipath effect caused by the complex indoor environment helps to improve the model's localization accuracy. In response to this question, this paper proposes a multipath-assisted localization (MAL) model based on millimeter-wave radar to achieve the localization of indoor electronic devices. The model fully considers the help of the multipath effect when describing the characteristics of the reflected signal and precisely locates the target position by using the MAL area formed by the reflected signal. At the same time, for the situation where the radar in the traditional Single-Input Single-Output (SISO) mode cannot obtain the 3D spatial position information of the target, the advantage of the MAL model is that the 3D information of the target can be obtained after the mining process of the multipath effect. Furthermore, based on the original hardware, it can achieve a breakthrough in angular resolution. Experiments show that our proposed MAL model enables the millimeter-wave multipath positioning model to achieve a 3D positioning error within 15 cm. [ABSTRACT FROM AUTHOR]