Every keyboard has a sound signature. Every click and clack carries information. With deep learning and a decent microphone, that information can be weaponized. In this session, we'll explore how modern AI models can identify what you're typing just from the sound of your keyboard. Using a dataset of recorded keystrokes and an open source sound classification pipeline, we'll walk through building a model that can recover text with startling accuracy. You'll see firsthand how a few lines of Python and a trained network can turn your laptop into an acoustic fingerprint.
But this talk isn't about enabling surveillance... it's about understanding it to fight back. We'll unpack why uniform keyboard layouts and consistent typing styles make these attacks so effective, then explore real countermeasures: signal masking, password entropy, and environmental noise defenses. You'll leave with a practical understanding of how these attacks work, how to reproduce them for research or awareness, and how to harden your systems (and yourself) against them. Bring your curiosity and maybe a little paranoia.
