Acoustic Eavesdropping

Acoustic eavesdropping research focuses on uncovering and mitigating unauthorized acquisition of sensitive information via unintended acoustic channels. Current efforts concentrate on exploiting vulnerabilities in smart devices, leveraging unintended acoustic emissions from smartphone cameras and accelerometers, and even analyzing vibrations in optical fibers. Researchers employ machine learning techniques, including generative adversarial networks and recurrent neural networks, to detect and reconstruct leaked audio, while also developing countermeasures like acoustic shielding and advanced signal processing. This field is crucial for safeguarding privacy and security in an increasingly interconnected world, impacting the design and security of smart devices, communication networks, and critical infrastructure.

Papers