Abstract
In this study, we conduct an empirical analysis of interpretation errors made by Amazon Alexa, the speech-recognition engine that powers the Amazon Echo family of devices. We show how common misinterpretations made by Alexa can be used to build a new class of attacks, called skill squatting attacks, and discuss its security implications.
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