Inaudible Voice

Inaudible voice attacks exploit vulnerabilities in voice-activated devices by using sounds outside the range of human hearing to issue commands, posing a significant security risk to various systems, from smart homes to autonomous vehicles. Current research focuses on understanding the effectiveness of these attacks across different platforms and developing robust defense mechanisms, often employing deep learning models (like those in the VGG family) for multimodal fusion of audio and visual data to detect malicious activity and reinforcement learning algorithms to simulate and analyze attack scenarios. The widespread adoption of voice-activated technology necessitates the development of effective countermeasures, driving research into areas such as acoustic shielding, advanced signal processing, and improved user authentication protocols.