The Insecurity of Home Digital Voice Assistants -- Amazon Alexa as a Case Study

TL;DR

This paper investigates the security vulnerabilities of Amazon Alexa, revealing access control flaws that enable remote attacks like home burglary and fake orders, and proposes a motion-based authentication solution to enhance security.

Contribution

The study identifies specific security flaws in Alexa's access control and introduces a novel motion detection system to improve authentication based on physical presence.

Findings

Disclosed three security vulnerabilities in Alexa's access control

Demonstrated proof-of-concept attacks: home burglary and fake order

Proposed and validated a WiFi-based human motion detection system

Abstract

Home Digital Voice Assistants (HDVAs) are getting popular in recent years. Users can control smart devices and get living assistance through those HDVAs (e.g., Amazon Alexa, Google Home) using voice. In this work, we study the insecurity of HDVA service by using Amazon Alexa as a case study. We disclose three security vulnerabilities which root in the insecure access control of Alexa services. We then exploit them to devise two proof-of-concept attacks, home burglary and fake order, where the adversary can remotely command the victim's Alexa device to open a door or place an order from Amazon.com. The insecure access control is that the Alexa device not only relies on a single-factor authentication but also takes voice commands even if no people are around. We thus argue that HDVAs should have another authentication factor, a physical presence based access control; that is, they can accept voice commands only when any person is detected nearby. To this end, we devise a Virtual Security Button (VSButton), which leverages the WiFi technology to detect indoor human motions. Once any indoor human motion is detected, the Alexa device is enabled to accept voice commands. Our evaluation results show that it can effectively differentiate indoor motions from the cases of no motion and outdoor motions in both the laboratory and real world settings.