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| Main Authors: | , , |
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| Format: | Recurso digital |
| Language: | |
| Published: |
Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.15412256 |
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Table of Contents:
- <p><span lang="EN-US">Voice assistants like Siri have become integral to mobile usability but introduce new attack surfaces, particularly via replay attacks. This research examines Siri’s vulnerability across various iOS versions and iPhone models when subjected to voice replay and non-owner command execution. In response, we developed a biometric-based defense mechanism using Python’s SpeechBrain library integrated with ESP32 via MQTT protocol. The solution achieved 90% accuracy in distinguishing the owner’s voice from an intruder and demonstrated low-latency response suitable for real-time prevention. This study offers forensic insights and a practical security model for voice assistant environments.</span></p>