The insecurity of home digital voice assistants -amzon alexa as a case study

Alex X.Liu 团队的最新工作,发布在arxiv上。

通过亚马逊家庭数字声音设备的研究,发现其存在一定的不安全因子,并且给出了一定的解决方法。这些数字声控设备通过声音控制家里的各种设备。但是存在一个问题:就是如果有人窃取了账号,利用声音也能控制家里的设备,该怎么办呢?文中给出了一个解决方法:当设备接到声音的命令时,并不立即执行该命令,而是利用WiFi信号判断家里是否有人在,如果有人在,则才开始执行命令。

上述针对问题进行阐述了,这里主要学习一下如何侦测室内有人移动,如何识别室内室外人移动的差异性?

we believe that detecting human motions based on WiFi signals is a practical yet low-cost solution approach due to two reaons. First, home WiFi networks are commonly deployed, so no extra deployment cost is needed. Second, only a software upgrade is required for the alexa devices, since all of them have been equipped with WiFi.


从两个视角来分析人移动,在什么地方移动等问题。我感觉很有意思。
***multi-path effect for human motions detection

***multi-reflection effect for identifying where the motions are.
室内与室外衰减程度不一样,一般来说,室外信号经历两次穿墙反射,衰减程度更大。(实验结果展示室内变化比室外变化大,这个让我有点理解不了。按照常理分析,室外信号衰减大,应该信号变化大啊。经过多次理解发现,我们看的是最后结果,所以室外最后结果都是很小,即变化不大。室内信号衰减不大,但是变化相对来说比较大。)
Our results show that it makes outside motions to result in only a small variation of CSI values, compared with a significant variation caused by inside human motions. The variations degrees of CSI values can thus be leveraged to identify the human motions occuring inside and outside the wall.



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转载自blog.csdn.net/guolinlin11/article/details/79125702
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