BarrierBypass: Out-of-Sight Clean Voice Command Injection Attacks through Physical Barriers
Payton Walker, Tianfang Zhang, Cong Shi, Nitesh Saxena, Yingying Chen

TL;DR
This paper introduces BarrierBypass, a novel attack method that enables stealthy voice command injection through physical barriers, demonstrating high success rates across various scenarios and distances, highlighting significant security risks for voice-enabled devices.
Contribution
The study provides the first measurement-based analysis of physical barrier-based voice command injection attacks, quantifying success rates and demonstrating real-world feasibility with drones.
Findings
100% success in across-wall and across-window scenarios
High success rates up to 4 meters distance
Effective use of drones for command injection
Abstract
The growing adoption of voice-enabled devices (e.g., smart speakers), particularly in smart home environments, has introduced many security vulnerabilities that pose significant threats to users' privacy and safety. When multiple devices are connected to a voice assistant, an attacker can cause serious damage if they can gain control of these devices. We ask where and how can an attacker issue clean voice commands stealthily across a physical barrier, and perform the first academic measurement study of this nature on the command injection attack. We present the BarrierBypass attack that can be launched against three different barrier-based scenarios termed across-door, across-window, and across-wall. We conduct a broad set of experiments to observe the command injection attack success rates for multiple speaker samples (TTS and live human recorded) at different command audio volumes…
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